M7finaledefinitivo100922.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMo4xFeykAwh3Ds9SGcDoZk",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/francescopatane96/Bioactivity-prediction-with-ML/blob/main/M7finaledefinitivo100922.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rdkit"
      ],
      "metadata": {
        "id": "sTiafVkFRvo8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install lazypredict"
      ],
      "metadata": {
        "id": "npXUo4YLmFLJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/volkamerlab/teachopencadd.git"
      ],
      "metadata": {
        "id": "L10Sz7LoR5f0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "93f9e869-8184-403f-91a4-d245f653836e"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting git+https://github.com/volkamerlab/teachopencadd.git\n",
            "  Cloning https://github.com/volkamerlab/teachopencadd.git to /tmp/pip-req-build-ta02aa58\n",
            "  Running command git clone -q https://github.com/volkamerlab/teachopencadd.git /tmp/pip-req-build-ta02aa58\n",
            "\u001b[31mERROR: Operation cancelled by user\u001b[0m\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/cli/base_command.py\", line 180, in _main\n",
            "    status = self.run(options, args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/cli/req_command.py\", line 199, in wrapper\n",
            "    return func(self, options, args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/commands/install.py\", line 319, in run\n",
            "    reqs, check_supported_wheels=not options.target_dir\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/resolver.py\", line 104, in resolve\n",
            "    req, requested_extras=()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/factory.py\", line 434, in make_requirement_from_install_req\n",
            "    version=None,\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/factory.py\", line 205, in _make_candidate_from_link\n",
            "    version=version,\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/candidates.py\", line 312, in __init__\n",
            "    version=version,\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/candidates.py\", line 151, in __init__\n",
            "    self.dist = self._prepare()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/candidates.py\", line 234, in _prepare\n",
            "    dist = self._prepare_distribution()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/resolution/resolvelib/candidates.py\", line 318, in _prepare_distribution\n",
            "    self._ireq, parallel_builds=True\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/operations/prepare.py\", line 508, in prepare_linked_requirement\n",
            "    return self._prepare_linked_requirement(req, parallel_builds)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/operations/prepare.py\", line 552, in _prepare_linked_requirement\n",
            "    self.download_dir, hashes\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/operations/prepare.py\", line 208, in unpack_url\n",
            "    unpack_vcs_link(link, location)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/operations/prepare.py\", line 68, in unpack_vcs_link\n",
            "    vcs_backend.unpack(location, url=hide_url(link.url))\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/vcs/versioncontrol.py\", line 619, in unpack\n",
            "    self.obtain(location, url=url)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/vcs/versioncontrol.py\", line 527, in obtain\n",
            "    self.fetch_new(dest, url, rev_options)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/vcs/git.py\", line 250, in fetch_new\n",
            "    self.run_command(make_command('clone', '-q', url, dest))\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/vcs/versioncontrol.py\", line 670, in run_command\n",
            "    stdout_only=stdout_only)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/utils/subprocess.py\", line 194, in call_subprocess\n",
            "    line = proc.stdout.readline()  # type: str\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/bin/pip3\", line 8, in <module>\n",
            "    sys.exit(main())\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/cli/main.py\", line 71, in main\n",
            "    return command.main(cmd_args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/cli/base_command.py\", line 104, in main\n",
            "    return self._main(args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/cli/base_command.py\", line 213, in _main\n",
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            "  File \"/usr/lib/python3.7/logging/__init__.py\", line 1524, in handle\n",
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            "  File \"/usr/lib/python3.7/logging/__init__.py\", line 1586, in callHandlers\n",
            "    hdlr.handle(record)\n",
            "  File \"/usr/lib/python3.7/logging/__init__.py\", line 894, in handle\n",
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            "  File \"/usr/lib/python3.7/logging/handlers.py\", line 71, in emit\n",
            "    logging.FileHandler.emit(self, record)\n",
            "  File \"/usr/lib/python3.7/logging/__init__.py\", line 1127, in emit\n",
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            "  File \"/usr/local/lib/python3.7/dist-packages/pip/_internal/utils/logging.py\", line 130, in format\n",
            "    formatted = super().format(record)\n",
            "  File \"/usr/lib/python3.7/logging/__init__.py\", line 616, in format\n",
            "    record.exc_text = self.formatException(record.exc_info)\n",
            "  File \"/usr/lib/python3.7/logging/__init__.py\", line 566, in formatException\n",
            "    traceback.print_exception(ei[0], ei[1], tb, None, sio)\n",
            "  File \"/usr/lib/python3.7/traceback.py\", line 104, in print_exception\n",
            "    type(value), value, tb, limit=limit).format(chain=chain):\n",
            "  File \"/usr/lib/python3.7/traceback.py\", line 508, in __init__\n",
            "    capture_locals=capture_locals)\n",
            "  File \"/usr/lib/python3.7/traceback.py\", line 363, in extract\n",
            "    f.line\n",
            "  File \"/usr/lib/python3.7/traceback.py\", line 285, in line\n",
            "    self._line = linecache.getline(self.filename, self.lineno).strip()\n",
            "  File \"/usr/lib/python3.7/linecache.py\", line 16, in getline\n",
            "    lines = getlines(filename, module_globals)\n",
            "  File \"/usr/lib/python3.7/linecache.py\", line 47, in getlines\n",
            "    return updatecache(filename, module_globals)\n",
            "  File \"/usr/lib/python3.7/linecache.py\", line 136, in updatecache\n",
            "    with tokenize.open(fullname) as fp:\n",
            "  File \"/usr/lib/python3.7/tokenize.py\", line 449, in open\n",
            "    encoding, lines = detect_encoding(buffer.readline)\n",
            "  File \"/usr/lib/python3.7/tokenize.py\", line 418, in detect_encoding\n",
            "    first = read_or_stop()\n",
            "  File \"/usr/lib/python3.7/tokenize.py\", line 376, in read_or_stop\n",
            "    return readline()\n",
            "KeyboardInterrupt\n"
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    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "VqMlkn50RdJD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "91e90792-e6fe-41a4-ef66-9035dfe62167"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.utils.testing module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.utils. Anything that cannot be imported from sklearn.utils is now part of the private API.\n",
            "  warnings.warn(message, FutureWarning)\n"
          ]
        }
      ],
      "source": [
        "from pathlib import Path\n",
        "import seaborn as sns\n",
        "from warnings import filterwarnings\n",
        "import time\n",
        "import lazypredict\n",
        "from lazypredict.Supervised import LazyRegressor\n",
        "from lazypredict.Supervised import LazyClassifier\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn import svm, metrics, clone\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.neural_network import MLPClassifier\n",
        "from sklearn.model_selection import KFold, train_test_split\n",
        "from sklearn.metrics import auc, accuracy_score, recall_score\n",
        "from sklearn.metrics import roc_curve, roc_auc_score\n",
        "import matplotlib.pyplot as plt\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import MACCSkeys\n",
        "from rdkit.Chem.AllChem import GetMorganFingerprintAsBitVect\n",
        "\n",
        "from teachopencadd.utils import seed_everything\n",
        "\n",
        "# Silence some expected warnings\n",
        "filterwarnings(\"ignore\")\n",
        "# Fix seed for reproducible results\n",
        "SEED = 22\n",
        "seed_everything(SEED)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Read data (Lipinski)\n",
        "chembl_df = pd.read_csv(\n",
        "    \"IDH_compounds_lipinski.csv\",\n",
        "    index_col=0,\n",
        ")\n",
        "\n",
        "# Look at head\n",
        "print(\"Shape of dataframe : \", chembl_df.shape)\n",
        "chembl_df.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        },
        "id": "QWPd9haHSfne",
        "outputId": "d90ae681-bdee-4f57-8df3-9aaa5f14517c"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape of dataframe :  (1545, 11)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  molecule_chembl_id  IC50 units  \\\n",
              "0      CHEMBL4279047  0.04    nM   \n",
              "1      CHEMBL4278845  0.25    nM   \n",
              "2      CHEMBL4283785  0.30    nM   \n",
              "3      CHEMBL4280132  0.70    nM   \n",
              "4      CHEMBL3909586  1.00    nM   \n",
              "\n",
              "                                              smiles  pIC50  \\\n",
              "0  C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...  10.40   \n",
              "1  C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...   9.60   \n",
              "2  CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...   9.52   \n",
              "3  FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...   9.15   \n",
              "4  C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...   9.00   \n",
              "\n",
              "                                               ROMol  molecular_weight  n_hba  \\\n",
              "0  <img data-content=\"rdkit/molecule\" src=\"data:i...            414.08      6   \n",
              "1  <img data-content=\"rdkit/molecule\" src=\"data:i...            414.08      6   \n",
              "2  <img data-content=\"rdkit/molecule\" src=\"data:i...            414.08      6   \n",
              "3  <img data-content=\"rdkit/molecule\" src=\"data:i...            430.13      6   \n",
              "4  <img data-content=\"rdkit/molecule\" src=\"data:i...            446.17      7   \n",
              "\n",
              "   n_hbd  logp  ro5_fulfilled  \n",
              "0      2  4.31           True  \n",
              "1      2  4.31           True  \n",
              "2      2  4.31           True  \n",
              "3      2  4.79           True  \n",
              "4      1  4.46           True  "
            ],
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              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>IC50</th>\n",
              "      <th>units</th>\n",
              "      <th>smiles</th>\n",
              "      <th>pIC50</th>\n",
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              "      <th>0</th>\n",
              "      <td>CHEMBL4279047</td>\n",
              "      <td>0.04</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>10.40</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>414.08</td>\n",
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              "      <td>4.31</td>\n",
              "      <td>True</td>\n",
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              "      <th>1</th>\n",
              "      <td>CHEMBL4278845</td>\n",
              "      <td>0.25</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>9.60</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>414.08</td>\n",
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              "      <td>4.31</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL4283785</td>\n",
              "      <td>0.30</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...</td>\n",
              "      <td>9.52</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>414.08</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4.31</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4280132</td>\n",
              "      <td>0.70</td>\n",
              "      <td>nM</td>\n",
              "      <td>FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...</td>\n",
              "      <td>9.15</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>430.13</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4.79</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL3909586</td>\n",
              "      <td>1.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...</td>\n",
              "      <td>9.00</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>446.17</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>4.46</td>\n",
              "      <td>True</td>\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6fce58dc-2f99-4b83-b15b-ca65340c18e6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6fce58dc-2f99-4b83-b15b-ca65340c18e6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Feature for proving and Proving our data \\\\ NaN finder\n",
        "def check_missing_values(dataframe):\n",
        "    \n",
        "    if dataframe.isnull().sum().sum() > 0:\n",
        "        m_total = dataframe.isnull().sum().sort_values(ascending=False) \n",
        "        total = m_total[m_total > 0]\n",
        "\n",
        "        m_percent = dataframe.isnull().mean().sort_values(ascending=False) \n",
        "        percent = m_percent[m_percent > 0] \n",
        "\n",
        "        missing_data = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])\n",
        "    \n",
        "        print(f'Total and Percentage of NaN:\\n {missing_data}')\n",
        "    else: \n",
        "        print('No NaN found.')\n",
        "        \n",
        "        \n",
        "check_missing_values(dataframe=chembl_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YFTwK2XPnXK3",
        "outputId": "362ff44f-9c5a-49f4-f701-5d5350bdab1f"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No NaN found.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# remove NaN\n",
        "chembl_df = chembl_df.dropna()"
      ],
      "metadata": {
        "id": "B0m1hX4InpUt"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "chembl_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H_DaNn2An0wO",
        "outputId": "29aff049-e14a-4b0a-83af-ea5d80eea34e"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1545, 11)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Keep only the columns we want\n",
        "chembl_df = chembl_df[[\"molecule_chembl_id\", \"smiles\", \"pIC50\"]]\n",
        "chembl_df.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "ui_bJaycSn6u",
        "outputId": "9868b1dd-59f9-4829-8fa8-85aab0f9ae16"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  molecule_chembl_id                                             smiles  pIC50\n",
              "0      CHEMBL4279047  C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...  10.40\n",
              "1      CHEMBL4278845  C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...   9.60\n",
              "2      CHEMBL4283785  CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...   9.52\n",
              "3      CHEMBL4280132  FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...   9.15\n",
              "4      CHEMBL3909586  C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...   9.00"
            ],
            "text/html": [
              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "    }\n",
              "\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>smiles</th>\n",
              "      <th>pIC50</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL4279047</td>\n",
              "      <td>C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>10.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL4278845</td>\n",
              "      <td>C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>9.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL4283785</td>\n",
              "      <td>CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...</td>\n",
              "      <td>9.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4280132</td>\n",
              "      <td>FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...</td>\n",
              "      <td>9.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL3909586</td>\n",
              "      <td>C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...</td>\n",
              "      <td>9.00</td>\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Add column for activity\n",
        "chembl_df[\"active\"] = np.zeros(len(chembl_df))\n",
        "\n",
        "# Mark every molecule as active with an pIC50 of >= 6.3, 0 otherwise\n",
        "chembl_df.loc[chembl_df[chembl_df.pIC50 >= 6.3].index, \"active\"] = 1.0\n",
        "\n",
        "# NBVAL_CHECK_OUTPUT\n",
        "print(\"Number of active compounds:\", int(chembl_df.active.sum()))\n",
        "print(\"Number of inactive compounds:\", len(chembl_df) - int(chembl_df.active.sum()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8NqHNrxjS1Zj",
        "outputId": "b0d9c323-a364-47ab-bce5-5280faa1ca8b"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of active compounds: 978\n",
            "Number of inactive compounds: 567\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chembl_df.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "oW3bY18rS8cD",
        "outputId": "4008ef1d-95a8-41f3-cb6f-727930753db1"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  molecule_chembl_id                                             smiles  \\\n",
              "0      CHEMBL4279047  C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...   \n",
              "1      CHEMBL4278845  C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...   \n",
              "2      CHEMBL4283785  CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...   \n",
              "3      CHEMBL4280132  FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...   \n",
              "4      CHEMBL3909586  C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...   \n",
              "\n",
              "   pIC50  active  \n",
              "0  10.40    1.00  \n",
              "1   9.60    1.00  \n",
              "2   9.52    1.00  \n",
              "3   9.15    1.00  \n",
              "4   9.00    1.00  "
            ],
            "text/html": [
              "\n",
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>smiles</th>\n",
              "      <th>pIC50</th>\n",
              "      <th>active</th>\n",
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              "      <th>0</th>\n",
              "      <td>CHEMBL4279047</td>\n",
              "      <td>C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>10.40</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL4278845</td>\n",
              "      <td>C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>9.60</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL4283785</td>\n",
              "      <td>CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...</td>\n",
              "      <td>9.52</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4280132</td>\n",
              "      <td>FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...</td>\n",
              "      <td>9.15</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL3909586</td>\n",
              "      <td>C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...</td>\n",
              "      <td>9.00</td>\n",
              "      <td>1.00</td>\n",
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              "          const element = document.querySelector('#df-4610ba87-7709-4a61-9875-77ce20a791bc');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def smiles_to_fp(smiles, method=\"maccs\", n_bits=2048):\n",
        "    \"\"\"\n",
        "    Encode a molecule from a SMILES string into a fingerprint.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    smiles : str\n",
        "        The SMILES string defining the molecule.\n",
        "\n",
        "    method : str\n",
        "        The type of fingerprint to use. Default is MACCS keys.\n",
        "\n",
        "    n_bits : int\n",
        "        The length of the fingerprint.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    array\n",
        "        The fingerprint array.\n",
        "\n",
        "    \"\"\"\n",
        "\n",
        "    # convert smiles to RDKit mol object\n",
        "    mol = Chem.MolFromSmiles(smiles)\n",
        "\n",
        "    if method == \"maccs\":\n",
        "        return np.array(MACCSkeys.GenMACCSKeys(mol))\n",
        "    if method == \"morgan2\":\n",
        "        return np.array(GetMorganFingerprintAsBitVect(mol, 2, nBits=n_bits))\n",
        "    if method == \"morgan3\":\n",
        "        return np.array(GetMorganFingerprintAsBitVect(mol, 3, nBits=n_bits))\n",
        "    else:\n",
        "        # NBVAL_CHECK_OUTPUT\n",
        "        print(f\"Warning: Wrong method specified: {method}. Default will be used instead.\")\n",
        "        return np.array(MACCSkeys.GenMACCSKeys(mol))"
      ],
      "metadata": {
        "id": "O4iESr2UTAAz"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#da qui pezzo test"
      ],
      "metadata": {
        "id": "CV7aOnVe2caT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "! wget https://github.com/gromdimon/features/raw/main/padel.sh\n",
        "! wget https://github.com/gromdimon/features/raw/main/padel.zip"
      ],
      "metadata": {
        "id": "9fIJcheD2e8a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2818f0de-3871-46fc-ef43-5885c000b5bb"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-09-10 15:03:39--  https://github.com/gromdimon/features/raw/main/padel.sh\n",
            "Resolving github.com (github.com)... 192.30.255.113\n",
            "Connecting to github.com (github.com)|192.30.255.113|:443... connected.\n",
            "HTTP request sent, awaiting response... 301 Moved Permanently\n",
            "Location: https://github.com/gromdimon/Pandas_features/raw/main/padel.sh [following]\n",
            "--2022-09-10 15:03:39--  https://github.com/gromdimon/Pandas_features/raw/main/padel.sh\n",
            "Reusing existing connection to github.com:443.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://raw.githubusercontent.com/gromdimon/Pandas_features/main/padel.sh [following]\n",
            "--2022-09-10 15:03:39--  https://raw.githubusercontent.com/gromdimon/Pandas_features/main/padel.sh\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 231 [text/plain]\n",
            "Saving to: ‘padel.sh’\n",
            "\n",
            "padel.sh            100%[===================>]     231  --.-KB/s    in 0s      \n",
            "\n",
            "2022-09-10 15:03:39 (14.0 MB/s) - ‘padel.sh’ saved [231/231]\n",
            "\n",
            "--2022-09-10 15:03:39--  https://github.com/gromdimon/features/raw/main/padel.zip\n",
            "Resolving github.com (github.com)... 192.30.255.113\n",
            "Connecting to github.com (github.com)|192.30.255.113|:443... connected.\n",
            "HTTP request sent, awaiting response... 301 Moved Permanently\n",
            "Location: https://github.com/gromdimon/Pandas_features/raw/main/padel.zip [following]\n",
            "--2022-09-10 15:03:39--  https://github.com/gromdimon/Pandas_features/raw/main/padel.zip\n",
            "Reusing existing connection to github.com:443.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://raw.githubusercontent.com/gromdimon/Pandas_features/main/padel.zip [following]\n",
            "--2022-09-10 15:03:40--  https://raw.githubusercontent.com/gromdimon/Pandas_features/main/padel.zip\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 25768637 (25M) [application/zip]\n",
            "Saving to: ‘padel.zip’\n",
            "\n",
            "padel.zip           100%[===================>]  24.57M  --.-KB/s    in 0.1s    \n",
            "\n",
            "2022-09-10 15:03:40 (224 MB/s) - ‘padel.zip’ saved [25768637/25768637]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip padel.zip"
      ],
      "metadata": {
        "id": "5dfNxKNO2ktS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4c5c0f9d-a049-43f7-97f7-ef79c9c39029"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  padel.zip\n",
            "   creating: PaDEL-Descriptor/\n",
            "  inflating: __MACOSX/._PaDEL-Descriptor  \n",
            "  inflating: PaDEL-Descriptor/MACCSFingerprinter.xml  \n",
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            "  inflating: PaDEL-Descriptor/lib/guava-17.0.jar  \n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "selection = ['smiles', 'molecule_chembl_id']\n",
        "act_selected = chembl_df[selection]\n",
        "act_selected.to_csv('molecule.smi', sep='\\t', index=False, header=False )"
      ],
      "metadata": {
        "id": "5ga_3hCr2v7Z"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "! cat molecule.smi | head -5\n",
        "! cat molecule.smi | wc -l"
      ],
      "metadata": {
        "id": "SMxFKWGY3Cfs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e92d1348-444e-4370-bb92-14be09ef74ed"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F)(F)F\tCHEMBL4279047\n",
            "C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F)(F)F\tCHEMBL4278845\n",
            "CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F)(F)F\tCHEMBL4283785\n",
            "FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n3)n2)C1\tCHEMBL4280132\n",
            "C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1cn(-c2ccc(C(F)F)cc2)cn1\tCHEMBL3909586\n",
            "1545\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!cat padel.sh"
      ],
      "metadata": {
        "id": "PUPnFvOF3EAp",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b3d86a4f-1aab-49fa-de33-420496742855"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "java -Xms1G -Xmx1G -Djava.awt.headless=true -jar ./PaDEL-Descriptor/PaDEL-Descriptor.jar -removesalt -standardizenitro -fingerprints -descriptortypes ./PaDEL-Descriptor/PubchemFingerprinter.xml -dir ./ -file descriptors_output.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!bash padel.sh"
      ],
      "metadata": {
        "id": "P-xS8kRB3F9y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "428edc27-c311-4964-96fa-042f869d231f"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing CHEMBL4279047 in molecule.smi (1/1545). \n",
            "Processing CHEMBL4278845 in molecule.smi (2/1545). \n",
            "Processing CHEMBL4280132 in molecule.smi (4/1545). Average speed: 3.45 s/mol.\n",
            "Processing CHEMBL4283785 in molecule.smi (3/1545). Average speed: 3.42 s/mol.\n",
            "Processing CHEMBL3909586 in molecule.smi (5/1545). Average speed: 1.30 s/mol.\n",
            "Processing CHEMBL4277352 in molecule.smi (6/1545). Average speed: 1.10 s/mol.\n",
            "Processing CHEMBL4529476 in molecule.smi (8/1545). Average speed: 0.83 s/mol.\n",
            "Processing CHEMBL4463644 in molecule.smi (7/1545). Average speed: 0.98 s/mol.\n",
            "Processing CHEMBL3979625 in molecule.smi (9/1545). Average speed: 0.81 s/mol.\n",
            "Processing CHEMBL3980822 in molecule.smi (10/1545). Average speed: 0.74 s/mol.\n",
            "Processing CHEMBL4215717 in molecule.smi (12/1545). Average speed: 0.64 s/mol.\n",
            "Processing CHEMBL4436236 in molecule.smi (11/1545). Average speed: 0.70 s/mol.\n",
            "Processing CHEMBL3962229 in molecule.smi (13/1545). Average speed: 0.63 s/mol.\n",
            "Processing CHEMBL4170686 in molecule.smi (14/1545). Average speed: 0.62 s/mol.\n",
            "Processing CHEMBL4526035 in molecule.smi (15/1545). Average speed: 0.64 s/mol.\n",
            "Processing CHEMBL3950128 in molecule.smi (16/1545). Average speed: 0.59 s/mol.\n",
            "Processing CHEMBL3972554 in molecule.smi (17/1545). Average speed: 0.56 s/mol.\n",
            "Processing CHEMBL4214223 in molecule.smi (18/1545). Average speed: 0.56 s/mol.\n",
            "Processing CHEMBL3986241 in molecule.smi (19/1545). Average speed: 0.53 s/mol.\n",
            "Processing CHEMBL4114088 in molecule.smi (20/1545). Average speed: 0.52 s/mol.\n",
            "Processing CHEMBL4476454 in molecule.smi (21/1545). Average speed: 0.53 s/mol.\n",
            "Processing CHEMBL4106576 in molecule.smi (22/1545). Average speed: 0.50 s/mol.\n",
            "Processing CHEMBL4107257 in molecule.smi (23/1545). Average speed: 0.51 s/mol.\n",
            "Processing CHEMBL3960560 in molecule.smi (24/1545). Average speed: 0.50 s/mol.\n",
            "Processing CHEMBL4292864 in molecule.smi (25/1545). Average speed: 0.49 s/mol.\n",
            "Processing CHEMBL3342782 in molecule.smi (26/1545). Average speed: 0.48 s/mol.\n",
            "Processing CHEMBL3682123 in molecule.smi (27/1545). Average speed: 0.51 s/mol.\n",
            "Processing CHEMBL4469055 in molecule.smi (29/1545). Average speed: 0.47 s/mol.\n",
            "Processing CHEMBL3682110 in molecule.smi (28/1545). Average speed: 0.48 s/mol.\n",
            "Processing CHEMBL4456610 in molecule.smi (30/1545). Average speed: 0.47 s/mol.\n",
            "Processing CHEMBL4212374 in molecule.smi (31/1545). Average speed: 0.47 s/mol.\n",
            "Processing CHEMBL3986728 in molecule.smi (32/1545). Average speed: 0.45 s/mol.\n",
            "Processing CHEMBL3682069 in molecule.smi (34/1545). Average speed: 0.45 s/mol.\n",
            "Processing CHEMBL3682070 in molecule.smi (33/1545). Average speed: 0.46 s/mol.\n",
            "Processing CHEMBL4586919 in molecule.smi (35/1545). Average speed: 0.45 s/mol.\n",
            "Processing CHEMBL3891698 in molecule.smi (36/1545). Average speed: 0.44 s/mol.\n",
            "Processing CHEMBL4442678 in molecule.smi (37/1545). Average speed: 0.44 s/mol.\n",
            "Processing CHEMBL4452108 in molecule.smi (38/1545). Average speed: 0.43 s/mol.\n",
            "Processing CHEMBL3941791 in molecule.smi (39/1545). Average speed: 0.42 s/mol.\n",
            "Processing CHEMBL3923174 in molecule.smi (40/1545). Average speed: 0.41 s/mol.\n",
            "Processing CHEMBL3911306 in molecule.smi (41/1545). Average speed: 0.41 s/mol.\n",
            "Processing CHEMBL4585231 in molecule.smi (42/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4111021 in molecule.smi (44/1545). Average speed: 0.39 s/mol.\n",
            "Processing CHEMBL4278793 in molecule.smi (43/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4446109 in molecule.smi (45/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL3342783 in molecule.smi (46/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4282267 in molecule.smi (47/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4464313 in molecule.smi (48/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4109329 in molecule.smi (49/1545). Average speed: 0.41 s/mol.\n",
            "Processing CHEMBL3920353 in molecule.smi (50/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4552644 in molecule.smi (52/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4437754 in molecule.smi (51/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4107825 in molecule.smi (54/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL3961739 in molecule.smi (53/1545). Average speed: 0.40 s/mol.\n",
            "Processing CHEMBL4282663 in molecule.smi (56/1545). Average speed: 0.39 s/mol.\n",
            "Processing CHEMBL3946068 in molecule.smi (55/1545). Average speed: 0.39 s/mol.\n",
            "Processing CHEMBL4475715 in molecule.smi (57/1545). Average speed: 0.38 s/mol.\n",
            "Processing CHEMBL4166795 in molecule.smi (59/1545). Average speed: 0.38 s/mol.\n",
            "Processing CHEMBL4444067 in molecule.smi (58/1545). Average speed: 0.38 s/mol.\n",
            "Processing CHEMBL4216510 in molecule.smi (61/1545). Average speed: 0.37 s/mol.\n",
            "Processing CHEMBL4567882 in molecule.smi (60/1545). Average speed: 0.38 s/mol.\n",
            "Processing CHEMBL3978748 in molecule.smi (62/1545). Average speed: 0.37 s/mol.\n",
            "Processing CHEMBL3682006 in molecule.smi (64/1545). Average speed: 0.36 s/mol.\n",
            "Processing CHEMBL3980106 in molecule.smi (63/1545). Average speed: 0.37 s/mol.\n",
            "Processing CHEMBL3984447 in molecule.smi (65/1545). Average speed: 0.36 s/mol.\n",
            "Processing CHEMBL3947403 in molecule.smi (66/1545). Average speed: 0.36 s/mol.\n",
            "Processing CHEMBL3947095 in molecule.smi (68/1545). Average speed: 0.35 s/mol.\n",
            "Processing CHEMBL4172087 in molecule.smi (67/1545). Average speed: 0.36 s/mol.\n",
            "Processing CHEMBL4473772 in molecule.smi (69/1545). Average speed: 0.35 s/mol.\n",
            "Processing CHEMBL4206033 in molecule.smi (71/1545). Average speed: 0.35 s/mol.\n",
            "Processing CHEMBL3896034 in molecule.smi (70/1545). Average speed: 0.35 s/mol.\n",
            "Processing CHEMBL4208648 in molecule.smi (72/1545). Average speed: 0.35 s/mol.\n",
            "Processing CHEMBL4568616 in molecule.smi (73/1545). Average speed: 0.35 s/mol.\n",
            "Processing CHEMBL4437186 in molecule.smi (74/1545). Average speed: 0.34 s/mol.\n",
            "Processing CHEMBL4113331 in molecule.smi (75/1545). Average speed: 0.34 s/mol.\n",
            "Processing CHEMBL3946170 in molecule.smi (76/1545). Average speed: 0.34 s/mol.\n",
            "Processing CHEMBL4584648 in molecule.smi (78/1545). Average speed: 0.34 s/mol.\n",
            "Processing CHEMBL3677053 in molecule.smi (77/1545). Average speed: 0.34 s/mol.\n",
            "Processing CHEMBL3938657 in molecule.smi (79/1545). Average speed: 0.33 s/mol.\n",
            "Processing CHEMBL4109951 in molecule.smi (80/1545). Average speed: 0.33 s/mol.\n",
            "Processing CHEMBL3923366 in molecule.smi (81/1545). Average speed: 0.33 s/mol.\n",
            "Processing CHEMBL3938883 in molecule.smi (82/1545). Average speed: 0.33 s/mol.\n",
            "Processing CHEMBL3933810 in molecule.smi (83/1545). Average speed: 0.33 s/mol.\n",
            "Processing CHEMBL4531302 in molecule.smi (84/1545). Average speed: 0.32 s/mol.\n",
            "Processing CHEMBL3986279 in molecule.smi (86/1545). Average speed: 0.32 s/mol.\n",
            "Processing CHEMBL3904882 in molecule.smi (85/1545). Average speed: 0.32 s/mol.\n",
            "Processing CHEMBL3342781 in molecule.smi (87/1545). Average speed: 0.32 s/mol.\n",
            "Processing CHEMBL4114410 in molecule.smi (88/1545). Average speed: 0.32 s/mol.\n",
            "Processing CHEMBL3969682 in molecule.smi (89/1545). Average speed: 0.31 s/mol.\n",
            "Processing CHEMBL4451408 in molecule.smi (90/1545). Average speed: 0.31 s/mol.\n",
            "Processing CHEMBL3955493 in molecule.smi (91/1545). Average speed: 0.31 s/mol.\n",
            "Processing CHEMBL4474186 in molecule.smi (92/1545). Average speed: 0.31 s/mol.\n",
            "Processing CHEMBL3973220 in molecule.smi (93/1545). Average speed: 0.31 s/mol.\n",
            "Processing CHEMBL3989958 in molecule.smi (94/1545). Average speed: 0.31 s/mol.\n",
            "Processing CHEMBL3913635 in molecule.smi (95/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL3976075 in molecule.smi (97/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL3961820 in molecule.smi (96/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL3682089 in molecule.smi (99/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL4476025 in molecule.smi (98/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL4110669 in molecule.smi (100/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL4569798 in molecule.smi (101/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL4109122 in molecule.smi (102/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL3942379 in molecule.smi (103/1545). Average speed: 0.30 s/mol.\n",
            "Processing CHEMBL3964464 in molecule.smi (105/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL3960143 in molecule.smi (104/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL4169151 in molecule.smi (106/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL3977806 in molecule.smi (107/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL3927758 in molecule.smi (108/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL3945859 in molecule.smi (109/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL3981306 in molecule.smi (110/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL4297610 in molecule.smi (111/1545). Average speed: 0.29 s/mol.\n",
            "Processing CHEMBL4107555 in molecule.smi (112/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4204501 in molecule.smi (113/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4114829 in molecule.smi (114/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL3959391 in molecule.smi (115/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4216785 in molecule.smi (117/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL3937532 in molecule.smi (116/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4476345 in molecule.smi (118/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL3930450 in molecule.smi (120/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL3677013 in molecule.smi (119/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL3934745 in molecule.smi (121/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4114144 in molecule.smi (122/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4563967 in molecule.smi (123/1545). Average speed: 0.28 s/mol.\n",
            "Processing CHEMBL4113581 in molecule.smi (124/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL4108421 in molecule.smi (125/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3953545 in molecule.smi (126/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3953686 in molecule.smi (127/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3677094 in molecule.smi (128/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3899328 in molecule.smi (129/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3894881 in molecule.smi (130/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3902941 in molecule.smi (131/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL4557532 in molecule.smi (132/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL4553096 in molecule.smi (133/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL3929638 in molecule.smi (134/1545). Average speed: 0.27 s/mol.\n",
            "Processing CHEMBL4446657 in molecule.smi (135/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL4440585 in molecule.smi (136/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3963739 in molecule.smi (138/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3947537 in molecule.smi (137/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3682064 in molecule.smi (140/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3901219 in molecule.smi (139/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3948226 in molecule.smi (141/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3924568 in molecule.smi (142/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3959538 in molecule.smi (143/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3946830 in molecule.smi (144/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL3905560 in molecule.smi (145/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL4545655 in molecule.smi (147/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3981557 in molecule.smi (146/1545). Average speed: 0.26 s/mol.\n",
            "Processing CHEMBL4449563 in molecule.smi (148/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3917430 in molecule.smi (150/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3987085 in molecule.smi (149/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3968221 in molecule.smi (152/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3682055 in molecule.smi (151/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3934588 in molecule.smi (154/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3956474 in molecule.smi (153/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL4108088 in molecule.smi (155/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3677152 in molecule.smi (156/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL4462489 in molecule.smi (157/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3890377 in molecule.smi (158/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3682051 in molecule.smi (159/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL4108766 in molecule.smi (160/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3906023 in molecule.smi (161/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3922872 in molecule.smi (162/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3677069 in molecule.smi (163/1545). Average speed: 0.25 s/mol.\n",
            "Processing CHEMBL3892513 in molecule.smi (164/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4112957 in molecule.smi (165/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3677045 in molecule.smi (166/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3677079 in molecule.smi (167/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3938511 in molecule.smi (168/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3939420 in molecule.smi (169/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3909346 in molecule.smi (170/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4455045 in molecule.smi (172/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3923861 in molecule.smi (171/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4515664 in molecule.smi (173/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4113911 in molecule.smi (174/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3915232 in molecule.smi (175/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3891941 in molecule.smi (176/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4107415 in molecule.smi (177/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3974384 in molecule.smi (178/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3929833 in molecule.smi (179/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3677081 in molecule.smi (180/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4111396 in molecule.smi (181/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4445771 in molecule.smi (182/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3901690 in molecule.smi (183/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3682054 in molecule.smi (184/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3977830 in molecule.smi (185/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL4111565 in molecule.smi (186/1545). Average speed: 0.24 s/mol.\n",
            "Processing CHEMBL3677205 in molecule.smi (187/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3894775 in molecule.smi (188/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3971609 in molecule.smi (189/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4475577 in molecule.smi (190/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3951969 in molecule.smi (191/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3963108 in molecule.smi (192/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3938198 in molecule.smi (193/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3973867 in molecule.smi (195/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3949812 in molecule.smi (194/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3956110 in molecule.smi (196/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3954174 in molecule.smi (197/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4214694 in molecule.smi (199/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3908513 in molecule.smi (198/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3985154 in molecule.smi (201/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4466857 in molecule.smi (200/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4524948 in molecule.smi (203/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4114431 in molecule.smi (202/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3905290 in molecule.smi (204/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL2359350 in molecule.smi (205/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3986808 in molecule.smi (206/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4206945 in molecule.smi (207/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL4108741 in molecule.smi (208/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3941489 in molecule.smi (209/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3984884 in molecule.smi (210/1545). Average speed: 0.23 s/mol.\n",
            "Processing CHEMBL3682010 in molecule.smi (211/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3940965 in molecule.smi (212/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL4115358 in molecule.smi (213/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3677068 in molecule.smi (214/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL4216983 in molecule.smi (216/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3953091 in molecule.smi (215/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL4108034 in molecule.smi (218/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL4113027 in molecule.smi (217/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3893867 in molecule.smi (220/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL4216196 in molecule.smi (219/1545). Average speed: 0.22 s/mol.\n",
            "Processing CHEMBL3964333 in molecule.smi (222/1545). Average speed: 0.22 s/mol.\n",
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            "Processing CHEMBL4467139 in molecule.smi (1399/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4459125 in molecule.smi (1400/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4877853 in molecule.smi (1401/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4753725 in molecule.smi (1402/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672170 in molecule.smi (1403/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672123 in molecule.smi (1404/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677024 in molecule.smi (1405/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4756543 in molecule.smi (1406/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL2386128 in molecule.smi (1407/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4796967 in molecule.smi (1408/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4756473 in molecule.smi (1409/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4758833 in molecule.smi (1410/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672133 in molecule.smi (1411/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4450318 in molecule.smi (1412/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4456155 in molecule.smi (1413/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3970770 in molecule.smi (1414/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4798041 in molecule.smi (1415/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4115631 in molecule.smi (1417/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672150 in molecule.smi (1416/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL2386127 in molecule.smi (1419/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4434758 in molecule.smi (1418/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4756071 in molecule.smi (1420/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672180 in molecule.smi (1421/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672126 in molecule.smi (1423/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4114305 in molecule.smi (1422/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677067 in molecule.smi (1424/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4795564 in molecule.smi (1426/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3682013 in molecule.smi (1425/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4762117 in molecule.smi (1427/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4746487 in molecule.smi (1429/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4746470 in molecule.smi (1428/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677084 in molecule.smi (1431/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677027 in molecule.smi (1430/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4113146 in molecule.smi (1433/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3682117 in molecule.smi (1432/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3963903 in molecule.smi (1434/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4781086 in molecule.smi (1435/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4776165 in molecule.smi (1436/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672171 in molecule.smi (1437/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4110198 in molecule.smi (1438/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3676997 in molecule.smi (1439/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3682139 in molecule.smi (1440/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672225 in molecule.smi (1441/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4590233 in molecule.smi (1442/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4106771 in molecule.smi (1443/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4453488 in molecule.smi (1444/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4744150 in molecule.smi (1445/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4749372 in molecule.smi (1446/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4748371 in molecule.smi (1447/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4556155 in molecule.smi (1448/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4780998 in molecule.smi (1449/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4762637 in molecule.smi (1450/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4762125 in molecule.smi (1451/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3899743 in molecule.smi (1453/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4792668 in molecule.smi (1452/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4114215 in molecule.smi (1455/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672100 in molecule.smi (1454/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672155 in molecule.smi (1457/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3965934 in molecule.smi (1456/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4790551 in molecule.smi (1458/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672102 in molecule.smi (1459/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677160 in molecule.smi (1460/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4562901 in molecule.smi (1462/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4277739 in molecule.smi (1461/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4743023 in molecule.smi (1463/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4741682 in molecule.smi (1465/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4466687 in molecule.smi (1464/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4760373 in molecule.smi (1467/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4754534 in molecule.smi (1466/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672221 in molecule.smi (1469/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4763175 in molecule.smi (1468/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677163 in molecule.smi (1470/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4114500 in molecule.smi (1472/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3682018 in molecule.smi (1471/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4751560 in molecule.smi (1473/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677146 in molecule.smi (1474/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4764291 in molecule.smi (1475/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4777948 in molecule.smi (1476/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677145 in molecule.smi (1478/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4798140 in molecule.smi (1477/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672130 in molecule.smi (1480/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4575450 in molecule.smi (1479/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3682096 in molecule.smi (1481/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4115378 in molecule.smi (1482/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4108555 in molecule.smi (1483/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4464973 in molecule.smi (1484/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4109507 in molecule.smi (1485/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4109718 in molecule.smi (1486/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3895369 in molecule.smi (1487/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL2180739 in molecule.smi (1488/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4554259 in molecule.smi (1489/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672145 in molecule.smi (1490/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672116 in molecule.smi (1491/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4780339 in molecule.smi (1493/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL2180738 in molecule.smi (1492/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4753778 in molecule.smi (1494/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4570376 in molecule.smi (1495/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677188 in molecule.smi (1496/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672134 in molecule.smi (1497/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672165 in molecule.smi (1498/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677096 in molecule.smi (1499/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677174 in molecule.smi (1500/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677165 in molecule.smi (1501/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4797347 in molecule.smi (1502/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4759466 in molecule.smi (1503/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677183 in molecule.smi (1504/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4286032 in molecule.smi (1506/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677173 in molecule.smi (1505/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4109729 in molecule.smi (1507/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672146 in molecule.smi (1509/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672107 in molecule.smi (1508/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3682097 in molecule.smi (1510/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4533443 in molecule.smi (1512/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4586529 in molecule.smi (1511/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4788997 in molecule.smi (1514/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677166 in molecule.smi (1513/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4745354 in molecule.smi (1516/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677187 in molecule.smi (1515/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677190 in molecule.smi (1517/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672172 in molecule.smi (1518/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672222 in molecule.smi (1520/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4740824 in molecule.smi (1519/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677154 in molecule.smi (1522/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4278116 in molecule.smi (1521/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4109986 in molecule.smi (1523/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672119 in molecule.smi (1525/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677159 in molecule.smi (1524/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677115 in molecule.smi (1526/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677137 in molecule.smi (1527/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3672166 in molecule.smi (1528/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4764880 in molecule.smi (1530/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL167779 in molecule.smi (1529/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4576887 in molecule.smi (1532/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4800266 in molecule.smi (1531/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL3677167 in molecule.smi (1533/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4753677 in molecule.smi (1535/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4107386 in molecule.smi (1534/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4580009 in molecule.smi (1536/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL2095003 in molecule.smi (1537/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4579725 in molecule.smi (1538/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4080497 in molecule.smi (1540/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4063125 in molecule.smi (1539/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4059985 in molecule.smi (1541/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4217951 in molecule.smi (1542/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4450414 in molecule.smi (1543/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL2180737 in molecule.smi (1544/1545). Average speed: 0.16 s/mol.\n",
            "Processing CHEMBL4473801 in molecule.smi (1545/1545). Average speed: 0.16 s/mol.\n",
            "Descriptor calculation completed in 4 mins 1.889 secs . Average speed: 0.16 s/mol.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls -l"
      ],
      "metadata": {
        "id": "p4ION5gP3IQb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c503e244-21e9-46c2-91c8-47d6b88df517"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 46456\n",
            "-rw-r--r-- 1 root root  2758352 Sep 10 15:08 descriptors_output.csv\n",
            "-rw-r--r-- 1 root root 18897550 Sep 10 15:03 IDH_compounds_lipinski.csv\n",
            "drwxr-xr-x 3 root root     4096 Sep 10 15:03 __MACOSX\n",
            "-rw-r--r-- 1 root root   118166 Sep 10 15:03 molecule.smi\n",
            "drwxrwxr-x 4 root root     4096 May 30  2020 PaDEL-Descriptor\n",
            "-rw-r--r-- 1 root root      231 Sep 10 15:03 padel.sh\n",
            "-rw-r--r-- 1 root root 25768637 Sep 10 15:03 padel.zip\n",
            "drwxr-xr-x 1 root root     4096 Aug 31 13:47 sample_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "actx = pd.read_csv('descriptors_output.csv')\n",
        "actx"
      ],
      "metadata": {
        "id": "yvObjIU33gYa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "outputId": "ac0bc330-3f7e-45b4-d04c-fe1bad65a56e"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               Name  PubchemFP0  PubchemFP1  PubchemFP2  PubchemFP3  \\\n",
              "0     CHEMBL4278845           1           1           0           0   \n",
              "1     CHEMBL4279047           1           1           0           0   \n",
              "2     CHEMBL4283785           1           1           0           0   \n",
              "3     CHEMBL4280132           1           1           1           0   \n",
              "4     CHEMBL3909586           1           1           1           0   \n",
              "...             ...         ...         ...         ...         ...   \n",
              "1540  CHEMBL4217951           1           1           1           0   \n",
              "1541  CHEMBL4059985           1           1           1           0   \n",
              "1542  CHEMBL4450414           1           1           1           0   \n",
              "1543  CHEMBL2180737           1           1           1           0   \n",
              "1544  CHEMBL4473801           1           1           1           0   \n",
              "\n",
              "      PubchemFP4  PubchemFP5  PubchemFP6  PubchemFP7  PubchemFP8  ...  \\\n",
              "0              0           0           0           0           0  ...   \n",
              "1              0           0           0           0           0  ...   \n",
              "2              0           0           0           0           0  ...   \n",
              "3              0           0           0           0           0  ...   \n",
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              "1540           0           0           0           0           0  ...   \n",
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              "1542           0           0           0           0           0  ...   \n",
              "1543           0           0           0           0           0  ...   \n",
              "1544           0           0           0           0           0  ...   \n",
              "\n",
              "      PubchemFP871  PubchemFP872  PubchemFP873  PubchemFP874  PubchemFP875  \\\n",
              "0                0             0             0             0             0   \n",
              "1                0             0             0             0             0   \n",
              "2                0             0             0             0             0   \n",
              "3                0             0             0             0             0   \n",
              "4                0             0             0             0             0   \n",
              "...            ...           ...           ...           ...           ...   \n",
              "1540             0             0             0             0             0   \n",
              "1541             0             0             0             0             0   \n",
              "1542             0             0             0             0             0   \n",
              "1543             0             0             0             0             0   \n",
              "1544             0             0             0             0             0   \n",
              "\n",
              "      PubchemFP876  PubchemFP877  PubchemFP878  PubchemFP879  PubchemFP880  \n",
              "0                0             0             0             0             0  \n",
              "1                0             0             0             0             0  \n",
              "2                0             0             0             0             0  \n",
              "3                0             0             0             0             0  \n",
              "4                0             0             0             0             0  \n",
              "...            ...           ...           ...           ...           ...  \n",
              "1540             0             0             0             0             0  \n",
              "1541             0             0             0             0             0  \n",
              "1542             0             0             0             0             0  \n",
              "1543             0             0             0             0             0  \n",
              "1544             0             0             0             0             0  \n",
              "\n",
              "[1545 rows x 882 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e9ecc08c-e8f8-4c0e-91ff-28e5c4b7477b\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>PubchemFP0</th>\n",
              "      <th>PubchemFP1</th>\n",
              "      <th>PubchemFP2</th>\n",
              "      <th>PubchemFP3</th>\n",
              "      <th>PubchemFP4</th>\n",
              "      <th>PubchemFP5</th>\n",
              "      <th>PubchemFP6</th>\n",
              "      <th>PubchemFP7</th>\n",
              "      <th>PubchemFP8</th>\n",
              "      <th>...</th>\n",
              "      <th>PubchemFP871</th>\n",
              "      <th>PubchemFP872</th>\n",
              "      <th>PubchemFP873</th>\n",
              "      <th>PubchemFP874</th>\n",
              "      <th>PubchemFP875</th>\n",
              "      <th>PubchemFP876</th>\n",
              "      <th>PubchemFP877</th>\n",
              "      <th>PubchemFP878</th>\n",
              "      <th>PubchemFP879</th>\n",
              "      <th>PubchemFP880</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL4278845</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL4279047</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL4283785</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4280132</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL3909586</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1540</th>\n",
              "      <td>CHEMBL4217951</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1541</th>\n",
              "      <td>CHEMBL4059985</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1542</th>\n",
              "      <td>CHEMBL4450414</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1543</th>\n",
              "      <td>CHEMBL2180737</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1544</th>\n",
              "      <td>CHEMBL4473801</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1545 rows × 882 columns</p>\n",
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          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#fine test"
      ],
      "metadata": {
        "id": "4SOpNHXf2utJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Read data (Lipinski)\n",
        "chembl_df = pd.read_csv(\n",
        "    \"IDH_compounds_lipinski.csv\",\n",
        "    index_col=0,\n",
        ")"
      ],
      "metadata": {
        "id": "wKt24N8W_eHB"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "chembl_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 834
        },
        "id": "sBTUfDdP--8m",
        "outputId": "88f644e3-da84-4c9d-f0a6-c878e05a54e0"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     molecule_chembl_id     IC50 units  \\\n",
              "0         CHEMBL4279047     0.04    nM   \n",
              "1         CHEMBL4278845     0.25    nM   \n",
              "2         CHEMBL4283785     0.30    nM   \n",
              "3         CHEMBL4280132     0.70    nM   \n",
              "4         CHEMBL3909586     1.00    nM   \n",
              "...                 ...      ...   ...   \n",
              "1695      CHEMBL4059985 47400.00    nM   \n",
              "1696      CHEMBL4217951 50000.00    nM   \n",
              "1697      CHEMBL4450414 51400.00    nM   \n",
              "1698      CHEMBL2180737 53100.00    nM   \n",
              "1699      CHEMBL4473801 55500.00    nM   \n",
              "\n",
              "                                                 smiles  pIC50  \\\n",
              "0     C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...  10.40   \n",
              "1     C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...   9.60   \n",
              "2     CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...   9.52   \n",
              "3     FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...   9.15   \n",
              "4     C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...   9.00   \n",
              "...                                                 ...    ...   \n",
              "1695  NS(=O)(=O)c1ccc(Cc2c(-c3ccccc3)nn(-c3nc(C(=O)O...   4.32   \n",
              "1696  COC(=O)C1C(=O)C2=C(CC1C)Nc1ccccc1NC2c1c[nH]c2c...   4.30   \n",
              "1697            COc1cccc(NCc2cc3cc(C)c(C)cc3[nH]c2=O)c1   4.29   \n",
              "1698  Cc1ccccc1C(C(=O)NC1CCNCC1)N(C(=O)Cc1cccs1)c1cc...   4.27   \n",
              "1699  COC(=O)C1C(=O)C2=C(C[C@@H]1C)Nc1ccccc1N[C@H]2c...   4.26   \n",
              "\n",
              "                                                  ROMol  molecular_weight  \\\n",
              "0     <img data-content=\"rdkit/molecule\" src=\"data:i...            414.08   \n",
              "1     <img data-content=\"rdkit/molecule\" src=\"data:i...            414.08   \n",
              "2     <img data-content=\"rdkit/molecule\" src=\"data:i...            414.08   \n",
              "3     <img data-content=\"rdkit/molecule\" src=\"data:i...            430.13   \n",
              "4     <img data-content=\"rdkit/molecule\" src=\"data:i...            446.17   \n",
              "...                                                 ...               ...   \n",
              "1695  <img data-content=\"rdkit/molecule\" src=\"data:i...            494.11   \n",
              "1696  <img data-content=\"rdkit/molecule\" src=\"data:i...            401.17   \n",
              "1697  <img data-content=\"rdkit/molecule\" src=\"data:i...            308.15   \n",
              "1698  <img data-content=\"rdkit/molecule\" src=\"data:i...            465.19   \n",
              "1699  <img data-content=\"rdkit/molecule\" src=\"data:i...            401.17   \n",
              "\n",
              "      n_hba  n_hbd  logp  ro5_fulfilled  \n",
              "0         6      2  4.31           True  \n",
              "1         6      2  4.31           True  \n",
              "2         6      2  4.31           True  \n",
              "3         6      2  4.79           True  \n",
              "4         7      1  4.46           True  \n",
              "...     ...    ...   ...            ...  \n",
              "1695      7      2  3.88           True  \n",
              "1696      5      3  4.40           True  \n",
              "1697      3      2  3.77           True  \n",
              "1698      4      2  4.38           True  \n",
              "1699      5      3  4.40           True  \n",
              "\n",
              "[1545 rows x 11 columns]"
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              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>IC50</th>\n",
              "      <th>units</th>\n",
              "      <th>smiles</th>\n",
              "      <th>pIC50</th>\n",
              "      <th>ROMol</th>\n",
              "      <th>molecular_weight</th>\n",
              "      <th>n_hba</th>\n",
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              "      <th>0</th>\n",
              "      <td>CHEMBL4279047</td>\n",
              "      <td>0.04</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@@H](Nc1nc(N[C@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>10.40</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>414.08</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL4278845</td>\n",
              "      <td>0.25</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@H](Nc1nc(N[C@@H](C)C(F)(F)F)nc(-c2cccc(Cl)...</td>\n",
              "      <td>9.60</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>414.08</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4.31</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL4283785</td>\n",
              "      <td>0.30</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC(Nc1nc(NC(C)C(F)(F)F)nc(-c2cccc(Cl)n2)n1)C(F...</td>\n",
              "      <td>9.52</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>414.08</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4.31</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4280132</td>\n",
              "      <td>0.70</td>\n",
              "      <td>nM</td>\n",
              "      <td>FC1(F)CCC(Nc2nc(NC3CCC(F)(F)C3)nc(-c3cccc(Cl)n...</td>\n",
              "      <td>9.15</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>430.13</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4.79</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL3909586</td>\n",
              "      <td>1.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@H](Nc1nccc(N2C(=O)OC[C@@H]2[C@H](C)F)n1)c1...</td>\n",
              "      <td>9.00</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>446.17</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>4.46</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1695</th>\n",
              "      <td>CHEMBL4059985</td>\n",
              "      <td>47400.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>NS(=O)(=O)c1ccc(Cc2c(-c3ccccc3)nn(-c3nc(C(=O)O...</td>\n",
              "      <td>4.32</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>494.11</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>3.88</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1696</th>\n",
              "      <td>CHEMBL4217951</td>\n",
              "      <td>50000.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>COC(=O)C1C(=O)C2=C(CC1C)Nc1ccccc1NC2c1c[nH]c2c...</td>\n",
              "      <td>4.30</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>401.17</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>4.40</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1697</th>\n",
              "      <td>CHEMBL4450414</td>\n",
              "      <td>51400.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>COc1cccc(NCc2cc3cc(C)c(C)cc3[nH]c2=O)c1</td>\n",
              "      <td>4.29</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>308.15</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>3.77</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1698</th>\n",
              "      <td>CHEMBL2180737</td>\n",
              "      <td>53100.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>Cc1ccccc1C(C(=O)NC1CCNCC1)N(C(=O)Cc1cccs1)c1cc...</td>\n",
              "      <td>4.27</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>465.19</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4.38</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1699</th>\n",
              "      <td>CHEMBL4473801</td>\n",
              "      <td>55500.00</td>\n",
              "      <td>nM</td>\n",
              "      <td>COC(=O)C1C(=O)C2=C(C[C@@H]1C)Nc1ccccc1N[C@H]2c...</td>\n",
              "      <td>4.26</td>\n",
              "      <td>&lt;img data-content=\"rdkit/molecule\" src=\"data:i...</td>\n",
              "      <td>401.17</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>4.40</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1545 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b75d99d7-1646-4124-8ed0-9193d2768783')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b75d99d7-1646-4124-8ed0-9193d2768783');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chembl_df = chembl_df[[\"ro5_fulfilled\"]]\n",
        "chembl_df.head()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "sYlNV1I3950q",
        "outputId": "e45fe50f-745e-4f37-eca6-3fb41f090026"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   ro5_fulfilled\n",
              "0           True\n",
              "1           True\n",
              "2           True\n",
              "3           True\n",
              "4           True"
            ],
            "text/html": [
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ro5_fulfilled</th>\n",
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              "  <tbody>\n",
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              "      <td>True</td>\n",
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              "      <th>4</th>\n",
              "      <td>True</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "      background-color: #E2EBFA;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e7d16d21-8eae-4da1-8dc7-65ade21ea612 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e7d16d21-8eae-4da1-8dc7-65ade21ea612');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "extracted_col = chembl_df[\"ro5_fulfilled\"]\n",
        "print(\"column to added from first dataframe to second:\")\n",
        "display(extracted_col)\n",
        "  \n",
        "actx = actx.join(extracted_col)\n",
        "print(\"Second dataframe after adding column from first dataframe:\")\n",
        "display(actx)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 740
        },
        "id": "mTHDKC17AQiU",
        "outputId": "2d7b671b-3a1f-48c5-fb21-d407e90ae362"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "column to added from first dataframe to second:\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0       True\n",
              "1       True\n",
              "2       True\n",
              "3       True\n",
              "4       True\n",
              "        ... \n",
              "1695    True\n",
              "1696    True\n",
              "1697    True\n",
              "1698    True\n",
              "1699    True\n",
              "Name: ro5_fulfilled, Length: 1545, dtype: bool"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Second dataframe after adding column from first dataframe:\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "               Name  PubchemFP0  PubchemFP1  PubchemFP2  PubchemFP3  \\\n",
              "0     CHEMBL4278845           1           1           0           0   \n",
              "1     CHEMBL4279047           1           1           0           0   \n",
              "2     CHEMBL4283785           1           1           0           0   \n",
              "3     CHEMBL4280132           1           1           1           0   \n",
              "4     CHEMBL3909586           1           1           1           0   \n",
              "...             ...         ...         ...         ...         ...   \n",
              "1540  CHEMBL4217951           1           1           1           0   \n",
              "1541  CHEMBL4059985           1           1           1           0   \n",
              "1542  CHEMBL4450414           1           1           1           0   \n",
              "1543  CHEMBL2180737           1           1           1           0   \n",
              "1544  CHEMBL4473801           1           1           1           0   \n",
              "\n",
              "      PubchemFP4  PubchemFP5  PubchemFP6  PubchemFP7  PubchemFP8  ...  \\\n",
              "0              0           0           0           0           0  ...   \n",
              "1              0           0           0           0           0  ...   \n",
              "2              0           0           0           0           0  ...   \n",
              "3              0           0           0           0           0  ...   \n",
              "4              0           0           0           0           0  ...   \n",
              "...          ...         ...         ...         ...         ...  ...   \n",
              "1540           0           0           0           0           0  ...   \n",
              "1541           0           0           0           0           0  ...   \n",
              "1542           0           0           0           0           0  ...   \n",
              "1543           0           0           0           0           0  ...   \n",
              "1544           0           0           0           0           0  ...   \n",
              "\n",
              "      PubchemFP872  PubchemFP873  PubchemFP874  PubchemFP875  PubchemFP876  \\\n",
              "0                0             0             0             0             0   \n",
              "1                0             0             0             0             0   \n",
              "2                0             0             0             0             0   \n",
              "3                0             0             0             0             0   \n",
              "4                0             0             0             0             0   \n",
              "...            ...           ...           ...           ...           ...   \n",
              "1540             0             0             0             0             0   \n",
              "1541             0             0             0             0             0   \n",
              "1542             0             0             0             0             0   \n",
              "1543             0             0             0             0             0   \n",
              "1544             0             0             0             0             0   \n",
              "\n",
              "      PubchemFP877  PubchemFP878  PubchemFP879  PubchemFP880  ro5_fulfilled  \n",
              "0                0             0             0             0           True  \n",
              "1                0             0             0             0           True  \n",
              "2                0             0             0             0           True  \n",
              "3                0             0             0             0           True  \n",
              "4                0             0             0             0           True  \n",
              "...            ...           ...           ...           ...            ...  \n",
              "1540             0             0             0             0           True  \n",
              "1541             0             0             0             0           True  \n",
              "1542             0             0             0             0           True  \n",
              "1543             0             0             0             0           True  \n",
              "1544             0             0             0             0           True  \n",
              "\n",
              "[1545 rows x 883 columns]"
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              "      <td>CHEMBL4278845</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL4279047</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL4283785</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4280132</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL3909586</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1540</th>\n",
              "      <td>CHEMBL4217951</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1541</th>\n",
              "      <td>CHEMBL4059985</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1542</th>\n",
              "      <td>CHEMBL4450414</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1543</th>\n",
              "      <td>CHEMBL2180737</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1544</th>\n",
              "      <td>CHEMBL4473801</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1545 rows × 883 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-04cd9717-e4bf-4a1e-ab17-c08bad7f591d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-04cd9717-e4bf-4a1e-ab17-c08bad7f591d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chembl_df = actx"
      ],
      "metadata": {
        "id": "yThLetm0A9Ca"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_roc_curves_for_models(models, test_x, test_y, save_png=False):\n",
        "    \"\"\"\n",
        "    Helper function to plot customized roc curve.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    models: dict\n",
        "        Dictionary of pretrained machine learning models.\n",
        "    test_x: list\n",
        "        Molecular fingerprints for test set.\n",
        "    test_y: list\n",
        "        Associated activity labels for test set.\n",
        "    save_png: bool\n",
        "        Save image to disk (default = False)\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    fig:\n",
        "        Figure.\n",
        "    \"\"\"\n",
        "\n",
        "    fig, ax = plt.subplots()\n",
        "\n",
        "    # Below for loop iterates through your models list\n",
        "    for model in models:\n",
        "        # Select the model\n",
        "        ml_model = model[\"model\"]\n",
        "        # Prediction probability on test set\n",
        "        test_prob = ml_model.predict_proba(test_x)[:, 1]\n",
        "        # Prediction class on test set\n",
        "        test_pred = ml_model.predict(test_x)\n",
        "        # Compute False postive rate and True positive rate\n",
        "        fpr, tpr, thresholds = metrics.roc_curve(test_y, test_prob)\n",
        "        # Calculate Area under the curve to display on the plot\n",
        "        auc = roc_auc_score(test_y, test_prob)\n",
        "        # Plot the computed values\n",
        "        ax.plot(fpr, tpr, label=(f\"{model['label']} AUC area = {auc:.2f}\"))\n",
        "\n",
        "    # Custom settings for the plot\n",
        "    ax.plot([0, 1], [0, 1], \"r--\")\n",
        "    ax.set_xlabel(\"False Positive Rate\")\n",
        "    ax.set_ylabel(\"True Positive Rate\")\n",
        "    ax.set_title(\"Receiver Operating Characteristic\")\n",
        "    ax.legend(loc=\"lower right\")\n",
        "    # Save plot\n",
        "    if save_png:\n",
        "        fig.savefig(f\"{DATA}/roc_auc\", dpi=300, bbox_inches=\"tight\", transparent=True)\n",
        "    return fig"
      ],
      "metadata": {
        "id": "COhODkg0TiVk"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def model_performance(ml_model, test_x, test_y, verbose=True):\n",
        "    \"\"\"\n",
        "    Helper function to calculate model performance\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    ml_model: sklearn model object\n",
        "        The machine learning model to train.\n",
        "    test_x: list\n",
        "        Molecular fingerprints for test set.\n",
        "    test_y: list\n",
        "        Associated activity labels for test set.\n",
        "    verbose: bool\n",
        "        Print performance measure (default = True)\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    tuple:\n",
        "        Accuracy, sensitivity, specificity, auc on test set.\n",
        "    \"\"\"\n",
        "\n",
        "    # Prediction probability on test set\n",
        "    test_prob = ml_model.predict_proba(test_x)[:, 1]\n",
        "\n",
        "    # Prediction class on test set\n",
        "    test_pred = ml_model.predict(test_x)\n",
        "\n",
        "    # Performance of model on test set\n",
        "    accuracy = accuracy_score(test_y, test_pred)\n",
        "    sens = recall_score(test_y, test_pred)\n",
        "    spec = recall_score(test_y, test_pred, pos_label=0)\n",
        "    auc = roc_auc_score(test_y, test_prob)\n",
        "\n",
        "    if verbose:\n",
        "        # Print performance results\n",
        "        # NBVAL_CHECK_OUTPUT        print(f\"Accuracy: {accuracy:.2}\")\n",
        "        print(f\"Sensitivity: {sens:.2f}\")\n",
        "        print(f\"Specificity: {spec:.2f}\")\n",
        "        print(f\"AUC: {auc:.2f}\")\n",
        "\n",
        "    return accuracy, sens, spec, auc"
      ],
      "metadata": {
        "id": "lyGpuP7BTlyF"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def model_training_and_validation(ml_model, name, splits, verbose=True):\n",
        "    \"\"\"\n",
        "    Fit a machine learning model on a random train-test split of the data\n",
        "    and return the performance measures.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    ml_model: sklearn model object\n",
        "        The machine learning model to train.\n",
        "    name: str\n",
        "        Name of machine learning algorithm: RF, SVM, ANN\n",
        "    splits: list\n",
        "        List of desciptor and label data: train_x, test_x, train_y, test_y.\n",
        "    verbose: bool\n",
        "        Print performance info (default = True)\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    tuple:\n",
        "        Accuracy, sensitivity, specificity, auc on test set.\n",
        "\n",
        "    \"\"\"\n",
        "    train_x, test_x, train_y, test_y = splits\n",
        "\n",
        "    # Fit the model\n",
        "    ml_model.fit(train_x, train_y)\n",
        "\n",
        "    # Calculate model performance results\n",
        "    accuracy, sens, spec, auc = model_performance(ml_model, test_x, test_y, verbose)\n",
        "\n",
        "    return accuracy, sens, spec, auc"
      ],
      "metadata": {
        "id": "nGak5nNLTpOh"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "actx_final = actx.drop('Name', axis=1)\n",
        "actx_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "QFjG5IPQB6cC",
        "outputId": "fb193478-83b0-424a-f776-5fc0d509b4c2"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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    {
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        "actx_df = actx_final.drop('ro5_fulfilled', axis=1)\n",
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      "execution_count": 24,
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              "      <th>PubchemFP872</th>\n",
              "      <th>PubchemFP873</th>\n",
              "      <th>PubchemFP874</th>\n",
              "      <th>PubchemFP875</th>\n",
              "      <th>PubchemFP876</th>\n",
              "      <th>PubchemFP877</th>\n",
              "      <th>PubchemFP878</th>\n",
              "      <th>PubchemFP879</th>\n",
              "      <th>PubchemFP880</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1540</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1541</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1542</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1543</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1544</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1545 rows × 881 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6f2e5077-1d22-4f6d-983c-eceffbeddc14')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-6f2e5077-1d22-4f6d-983c-eceffbeddc14 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6f2e5077-1d22-4f6d-983c-eceffbeddc14');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chembl_df['ro5_fulfilled']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lb1KnsZIFMHv",
        "outputId": "377ec0ee-0c22-4005-e9ec-87c5735fd67c"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       True\n",
              "1       True\n",
              "2       True\n",
              "3       True\n",
              "4       True\n",
              "        ... \n",
              "1540    True\n",
              "1541    True\n",
              "1542    True\n",
              "1543    True\n",
              "1544    True\n",
              "Name: ro5_fulfilled, Length: 1545, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Read data (Lipinski)\n",
        "chembl_df = pd.read_csv(\n",
        "    \"IDH_compounds_lipinski.csv\",\n",
        "    index_col=0,\n",
        ")\n"
      ],
      "metadata": {
        "id": "E5KBLpzUG-ft"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X = actx_df\n",
        "Y = chembl_df.pIC50"
      ],
      "metadata": {
        "id": "vAEvKNRjHq8h"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Spliting data in 80\\20 ratio\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=.2, random_state=42)"
      ],
      "metadata": {
        "id": "_crBdOZvHzfJ"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Seeing the data that was prepared\n",
        "X_train.shape, Y_train.shape, X_test.shape, Y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ms4H8KktILlb",
        "outputId": "12ea2625-3d9e-485b-e224-1c7415fe5733"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1236, 881), (1236,), (309, 881), (309,))"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Defines and builds the lazyclassifier\n",
        "reg = LazyRegressor(verbose=0,ignore_warnings=True, custom_metric=None)\n",
        "models_train,predictions_train = reg.fit(X_train, X_train, Y_train, Y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hj5D9uZAIPNS",
        "outputId": "66ff0bcc-7494-44ba-a184-a9cf496fbb0f"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 42/42 [02:37<00:00,  3.75s/it]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Performance table of the training set (80% subset)\n",
        "models_train"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "FZBL_doEI4qi",
        "outputId": "13b54531-4b49-420f-e191-a2077064d77c"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                         Adjusted R-Squared  \\\n",
              "Model                                                         \n",
              "DecisionTreeRegressor                                  0.65   \n",
              "ExtraTreeRegressor                                     0.65   \n",
              "ExtraTreesRegressor                                    0.65   \n",
              "GaussianProcessRegressor                               0.65   \n",
              "XGBRegressor                                           0.50   \n",
              "RandomForestRegressor                                  0.49   \n",
              "BaggingRegressor                                       0.43   \n",
              "MLPRegressor                                           0.32   \n",
              "HistGradientBoostingRegressor                          0.25   \n",
              "LGBMRegressor                                          0.25   \n",
              "TransformedTargetRegressor                            -0.07   \n",
              "LinearRegression                                      -0.07   \n",
              "Ridge                                                 -0.08   \n",
              "SVR                                                   -0.12   \n",
              "RidgeCV                                               -0.13   \n",
              "NuSVR                                                 -0.16   \n",
              "HuberRegressor                                        -0.21   \n",
              "KNeighborsRegressor                                   -0.23   \n",
              "GradientBoostingRegressor                             -0.30   \n",
              "PoissonRegressor                                      -0.31   \n",
              "OrthogonalMatchingPursuit                             -0.37   \n",
              "BayesianRidge                                         -0.38   \n",
              "ElasticNetCV                                          -0.45   \n",
              "LassoCV                                               -0.48   \n",
              "GeneralizedLinearRegressor                            -0.59   \n",
              "TweedieRegressor                                      -0.59   \n",
              "GammaRegressor                                        -0.59   \n",
              "OrthogonalMatchingPursuitCV                           -0.62   \n",
              "LinearSVR                                             -0.67   \n",
              "AdaBoostRegressor                                     -1.03   \n",
              "PassiveAggressiveRegressor                            -1.40   \n",
              "LassoLarsIC                                           -1.63   \n",
              "LassoLarsCV                                           -1.63   \n",
              "LarsCV                                                -2.27   \n",
              "Lasso                                                 -2.49   \n",
              "ElasticNet                                            -2.49   \n",
              "DummyRegressor                                        -2.49   \n",
              "LassoLars                                             -2.49   \n",
              "KernelRidge                                         -165.88   \n",
              "Lars                               -26751289493140955136.00   \n",
              "SGDRegressor                  -1484518672855795236864000.00   \n",
              "RANSACRegressor               -1790853454476792725241856.00   \n",
              "\n",
              "                                                 R-Squared            RMSE  \\\n",
              "Model                                                                        \n",
              "DecisionTreeRegressor                                 0.90            0.30   \n",
              "ExtraTreeRegressor                                    0.90            0.30   \n",
              "ExtraTreesRegressor                                   0.90            0.30   \n",
              "GaussianProcessRegressor                              0.90            0.30   \n",
              "XGBRegressor                                          0.86            0.36   \n",
              "RandomForestRegressor                                 0.85            0.36   \n",
              "BaggingRegressor                                      0.84            0.38   \n",
              "MLPRegressor                                          0.81            0.42   \n",
              "HistGradientBoostingRegressor                         0.78            0.44   \n",
              "LGBMRegressor                                         0.78            0.44   \n",
              "TransformedTargetRegressor                            0.69            0.52   \n",
              "LinearRegression                                      0.69            0.52   \n",
              "Ridge                                                 0.69            0.53   \n",
              "SVR                                                   0.68            0.54   \n",
              "RidgeCV                                               0.68            0.54   \n",
              "NuSVR                                                 0.67            0.55   \n",
              "HuberRegressor                                        0.65            0.56   \n",
              "KNeighborsRegressor                                   0.65            0.56   \n",
              "GradientBoostingRegressor                             0.63            0.58   \n",
              "PoissonRegressor                                      0.62            0.58   \n",
              "OrthogonalMatchingPursuit                             0.61            0.59   \n",
              "BayesianRidge                                         0.60            0.60   \n",
              "ElasticNetCV                                          0.58            0.61   \n",
              "LassoCV                                               0.58            0.62   \n",
              "GeneralizedLinearRegressor                            0.54            0.64   \n",
              "TweedieRegressor                                      0.54            0.64   \n",
              "GammaRegressor                                        0.54            0.64   \n",
              "OrthogonalMatchingPursuitCV                           0.54            0.65   \n",
              "LinearSVR                                             0.52            0.66   \n",
              "AdaBoostRegressor                                     0.42            0.72   \n",
              "PassiveAggressiveRegressor                            0.31            0.79   \n",
              "LassoLarsIC                                           0.25            0.82   \n",
              "LassoLarsCV                                           0.25            0.82   \n",
              "LarsCV                                                0.06            0.92   \n",
              "Lasso                                                 0.00            0.95   \n",
              "ElasticNet                                            0.00            0.95   \n",
              "DummyRegressor                                        0.00            0.95   \n",
              "LassoLars                                             0.00            0.95   \n",
              "KernelRidge                                         -46.84            6.55   \n",
              "Lars                               -7667980955928663040.00   2623638379.26   \n",
              "SGDRegressor                  -425521951571620694851584.00 618051190076.70   \n",
              "RANSACRegressor               -513329654157720372117504.00 678830956618.44   \n",
              "\n",
              "                               Time Taken  \n",
              "Model                                      \n",
              "DecisionTreeRegressor                0.16  \n",
              "ExtraTreeRegressor                   0.18  \n",
              "ExtraTreesRegressor                  4.80  \n",
              "GaussianProcessRegressor             2.60  \n",
              "XGBRegressor                         3.26  \n",
              "RandomForestRegressor                3.60  \n",
              "BaggingRegressor                     0.49  \n",
              "MLPRegressor                         3.62  \n",
              "HistGradientBoostingRegressor       16.03  \n",
              "LGBMRegressor                        0.45  \n",
              "TransformedTargetRegressor           0.46  \n",
              "LinearRegression                     0.48  \n",
              "Ridge                                0.18  \n",
              "SVR                                  3.32  \n",
              "RidgeCV                              0.73  \n",
              "NuSVR                                2.65  \n",
              "HuberRegressor                       1.03  \n",
              "KNeighborsRegressor                  2.62  \n",
              "GradientBoostingRegressor            1.21  \n",
              "PoissonRegressor                     0.18  \n",
              "OrthogonalMatchingPursuit            0.13  \n",
              "BayesianRidge                        1.29  \n",
              "ElasticNetCV                        33.42  \n",
              "LassoCV                             27.91  \n",
              "GeneralizedLinearRegressor           0.15  \n",
              "TweedieRegressor                     0.14  \n",
              "GammaRegressor                       0.12  \n",
              "OrthogonalMatchingPursuitCV          0.47  \n",
              "LinearSVR                            1.48  \n",
              "AdaBoostRegressor                    0.95  \n",
              "PassiveAggressiveRegressor           0.16  \n",
              "LassoLarsIC                          0.14  \n",
              "LassoLarsCV                          0.58  \n",
              "LarsCV                              10.14  \n",
              "Lasso                                0.13  \n",
              "ElasticNet                           0.08  \n",
              "DummyRegressor                       0.07  \n",
              "LassoLars                            0.17  \n",
              "KernelRidge                          0.28  \n",
              "Lars                                 0.67  \n",
              "SGDRegressor                         0.13  \n",
              "RANSACRegressor                     30.66  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d76d79b4-d7fd-437c-b7d0-7f6299732d14\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Adjusted R-Squared</th>\n",
              "      <th>R-Squared</th>\n",
              "      <th>RMSE</th>\n",
              "      <th>Time Taken</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Model</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>DecisionTreeRegressor</th>\n",
              "      <td>0.65</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ExtraTreeRegressor</th>\n",
              "      <td>0.65</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ExtraTreesRegressor</th>\n",
              "      <td>0.65</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.30</td>\n",
              "      <td>4.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GaussianProcessRegressor</th>\n",
              "      <td>0.65</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.30</td>\n",
              "      <td>2.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XGBRegressor</th>\n",
              "      <td>0.50</td>\n",
              "      <td>0.86</td>\n",
              "      <td>0.36</td>\n",
              "      <td>3.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RandomForestRegressor</th>\n",
              "      <td>0.49</td>\n",
              "      <td>0.85</td>\n",
              "      <td>0.36</td>\n",
              "      <td>3.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BaggingRegressor</th>\n",
              "      <td>0.43</td>\n",
              "      <td>0.84</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MLPRegressor</th>\n",
              "      <td>0.32</td>\n",
              "      <td>0.81</td>\n",
              "      <td>0.42</td>\n",
              "      <td>3.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HistGradientBoostingRegressor</th>\n",
              "      <td>0.25</td>\n",
              "      <td>0.78</td>\n",
              "      <td>0.44</td>\n",
              "      <td>16.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LGBMRegressor</th>\n",
              "      <td>0.25</td>\n",
              "      <td>0.78</td>\n",
              "      <td>0.44</td>\n",
              "      <td>0.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TransformedTargetRegressor</th>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.52</td>\n",
              "      <td>0.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LinearRegression</th>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.52</td>\n",
              "      <td>0.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ridge</th>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SVR</th>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.54</td>\n",
              "      <td>3.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RidgeCV</th>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NuSVR</th>\n",
              "      <td>-0.16</td>\n",
              "      <td>0.67</td>\n",
              "      <td>0.55</td>\n",
              "      <td>2.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HuberRegressor</th>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.56</td>\n",
              "      <td>1.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KNeighborsRegressor</th>\n",
              "      <td>-0.23</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GradientBoostingRegressor</th>\n",
              "      <td>-0.30</td>\n",
              "      <td>0.63</td>\n",
              "      <td>0.58</td>\n",
              "      <td>1.21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PoissonRegressor</th>\n",
              "      <td>-0.31</td>\n",
              "      <td>0.62</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OrthogonalMatchingPursuit</th>\n",
              "      <td>-0.37</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.59</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BayesianRidge</th>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.60</td>\n",
              "      <td>1.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ElasticNetCV</th>\n",
              "      <td>-0.45</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.61</td>\n",
              "      <td>33.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LassoCV</th>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.62</td>\n",
              "      <td>27.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GeneralizedLinearRegressor</th>\n",
              "      <td>-0.59</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.64</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TweedieRegressor</th>\n",
              "      <td>-0.59</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.64</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GammaRegressor</th>\n",
              "      <td>-0.59</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.64</td>\n",
              "      <td>0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OrthogonalMatchingPursuitCV</th>\n",
              "      <td>-0.62</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LinearSVR</th>\n",
              "      <td>-0.67</td>\n",
              "      <td>0.52</td>\n",
              "      <td>0.66</td>\n",
              "      <td>1.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AdaBoostRegressor</th>\n",
              "      <td>-1.03</td>\n",
              "      <td>0.42</td>\n",
              "      <td>0.72</td>\n",
              "      <td>0.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PassiveAggressiveRegressor</th>\n",
              "      <td>-1.40</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.79</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LassoLarsIC</th>\n",
              "      <td>-1.63</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LassoLarsCV</th>\n",
              "      <td>-1.63</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LarsCV</th>\n",
              "      <td>-2.27</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.92</td>\n",
              "      <td>10.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lasso</th>\n",
              "      <td>-2.49</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ElasticNet</th>\n",
              "      <td>-2.49</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DummyRegressor</th>\n",
              "      <td>-2.49</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LassoLars</th>\n",
              "      <td>-2.49</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KernelRidge</th>\n",
              "      <td>-165.88</td>\n",
              "      <td>-46.84</td>\n",
              "      <td>6.55</td>\n",
              "      <td>0.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lars</th>\n",
              "      <td>-26751289493140955136.00</td>\n",
              "      <td>-7667980955928663040.00</td>\n",
              "      <td>2623638379.26</td>\n",
              "      <td>0.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SGDRegressor</th>\n",
              "      <td>-1484518672855795236864000.00</td>\n",
              "      <td>-425521951571620694851584.00</td>\n",
              "      <td>618051190076.70</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RANSACRegressor</th>\n",
              "      <td>-1790853454476792725241856.00</td>\n",
              "      <td>-513329654157720372117504.00</td>\n",
              "      <td>678830956618.44</td>\n",
              "      <td>30.66</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Checking the study on a test sample\n",
        "reg = LazyRegressor(verbose=0,ignore_warnings=True, custom_metric=None)\n",
        "models_test,predictions_test = reg.fit(X_train,X_test,Y_train,Y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qHNtZTdoJEJD",
        "outputId": "0ff8274a-da3f-4c55-e050-3a279a40694e"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 42/42 [02:24<00:00,  3.45s/it]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "mxCFrrI_JU7h",
        "outputId": "f2748e93-8fcd-464e-81bd-a09086e94b28"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                   Adjusted R-Squared  \\\n",
              "Model                                                                   \n",
              "Lars                          633212450295463665343799527169064960.00   \n",
              "RANSACRegressor                           343678282839387237515264.00   \n",
              "SGDRegressor                              144480431532956121563136.00   \n",
              "TransformedTargetRegressor                135672652845232980754432.00   \n",
              "LinearRegression                          135672652845232980754432.00   \n",
              "KernelRidge                                                     26.99   \n",
              "GaussianProcessRegressor                                        18.85   \n",
              "LinearSVR                                                        1.59   \n",
              "MLPRegressor                                                     1.58   \n",
              "PassiveAggressiveRegressor                                       1.56   \n",
              "Lasso                                                            1.54   \n",
              "LassoLars                                                        1.54   \n",
              "ElasticNet                                                       1.54   \n",
              "DummyRegressor                                                   1.54   \n",
              "LarsCV                                                           1.50   \n",
              "Ridge                                                            1.47   \n",
              "LassoLarsCV                                                      1.39   \n",
              "LassoLarsIC                                                      1.39   \n",
              "HuberRegressor                                                   1.38   \n",
              "ExtraTreeRegressor                                               1.38   \n",
              "DecisionTreeRegressor                                            1.38   \n",
              "ExtraTreesRegressor                                              1.36   \n",
              "AdaBoostRegressor                                                1.34   \n",
              "RidgeCV                                                          1.34   \n",
              "OrthogonalMatchingPursuitCV                                      1.29   \n",
              "OrthogonalMatchingPursuit                                        1.28   \n",
              "BaggingRegressor                                                 1.27   \n",
              "KNeighborsRegressor                                              1.26   \n",
              "RandomForestRegressor                                            1.26   \n",
              "TweedieRegressor                                                 1.26   \n",
              "GeneralizedLinearRegressor                                       1.26   \n",
              "GammaRegressor                                                   1.26   \n",
              "PoissonRegressor                                                 1.25   \n",
              "LassoCV                                                          1.25   \n",
              "ElasticNetCV                                                     1.25   \n",
              "XGBRegressor                                                     1.25   \n",
              "BayesianRidge                                                    1.25   \n",
              "GradientBoostingRegressor                                        1.24   \n",
              "SVR                                                              1.24   \n",
              "NuSVR                                                            1.24   \n",
              "HistGradientBoostingRegressor                                    1.22   \n",
              "LGBMRegressor                                                    1.22   \n",
              "\n",
              "                                                              R-Squared  \\\n",
              "Model                                                                     \n",
              "Lars                          -1178021863699028304304484048200269824.00   \n",
              "RANSACRegressor                            -639375506710937930301440.00   \n",
              "SGDRegressor                               -268789893728519044726784.00   \n",
              "TransformedTargetRegressor                 -252403993767267857858560.00   \n",
              "LinearRegression                           -252403993767267857858560.00   \n",
              "KernelRidge                                                      -47.34   \n",
              "GaussianProcessRegressor                                         -32.22   \n",
              "LinearSVR                                                         -0.10   \n",
              "MLPRegressor                                                      -0.09   \n",
              "PassiveAggressiveRegressor                                        -0.04   \n",
              "Lasso                                                             -0.00   \n",
              "LassoLars                                                         -0.00   \n",
              "ElasticNet                                                        -0.00   \n",
              "DummyRegressor                                                    -0.00   \n",
              "LarsCV                                                             0.07   \n",
              "Ridge                                                              0.13   \n",
              "LassoLarsCV                                                        0.27   \n",
              "LassoLarsIC                                                        0.27   \n",
              "HuberRegressor                                                     0.28   \n",
              "ExtraTreeRegressor                                                 0.29   \n",
              "DecisionTreeRegressor                                              0.29   \n",
              "ExtraTreesRegressor                                                0.32   \n",
              "AdaBoostRegressor                                                  0.37   \n",
              "RidgeCV                                                            0.37   \n",
              "OrthogonalMatchingPursuitCV                                        0.47   \n",
              "OrthogonalMatchingPursuit                                          0.49   \n",
              "BaggingRegressor                                                   0.50   \n",
              "KNeighborsRegressor                                                0.51   \n",
              "RandomForestRegressor                                              0.51   \n",
              "TweedieRegressor                                                   0.51   \n",
              "GeneralizedLinearRegressor                                         0.51   \n",
              "GammaRegressor                                                     0.52   \n",
              "PoissonRegressor                                                   0.53   \n",
              "LassoCV                                                            0.53   \n",
              "ElasticNetCV                                                       0.53   \n",
              "XGBRegressor                                                       0.53   \n",
              "BayesianRidge                                                      0.54   \n",
              "GradientBoostingRegressor                                          0.55   \n",
              "SVR                                                                0.55   \n",
              "NuSVR                                                              0.55   \n",
              "HistGradientBoostingRegressor                                      0.58   \n",
              "LGBMRegressor                                                      0.58   \n",
              "\n",
              "                                                RMSE  Time Taken  \n",
              "Model                                                             \n",
              "Lars                          1021405320329878912.00        0.66  \n",
              "RANSACRegressor                      752487756185.03       31.33  \n",
              "SGDRegressor                         487896730746.13        0.14  \n",
              "TransformedTargetRegressor           472791381783.18        0.44  \n",
              "LinearRegression                     472791381783.18        0.48  \n",
              "KernelRidge                                     6.54        0.20  \n",
              "GaussianProcessRegressor                        5.42        1.87  \n",
              "LinearSVR                                       0.99        1.48  \n",
              "MLPRegressor                                    0.98        3.79  \n",
              "PassiveAggressiveRegressor                      0.96        0.15  \n",
              "Lasso                                           0.94        0.12  \n",
              "LassoLars                                       0.94        0.17  \n",
              "ElasticNet                                      0.94        0.07  \n",
              "DummyRegressor                                  0.94        0.06  \n",
              "LarsCV                                          0.91        2.94  \n",
              "Ridge                                           0.88        0.13  \n",
              "LassoLarsCV                                     0.81        0.59  \n",
              "LassoLarsIC                                     0.81        0.14  \n",
              "HuberRegressor                                  0.80        0.92  \n",
              "ExtraTreeRegressor                              0.79        0.17  \n",
              "DecisionTreeRegressor                           0.79        0.15  \n",
              "ExtraTreesRegressor                             0.77        4.57  \n",
              "AdaBoostRegressor                               0.75        0.79  \n",
              "RidgeCV                                         0.75        0.68  \n",
              "OrthogonalMatchingPursuitCV                     0.69        0.46  \n",
              "OrthogonalMatchingPursuit                       0.67        0.12  \n",
              "BaggingRegressor                                0.67        0.45  \n",
              "KNeighborsRegressor                             0.66        0.81  \n",
              "RandomForestRegressor                           0.66        3.51  \n",
              "TweedieRegressor                                0.66        0.16  \n",
              "GeneralizedLinearRegressor                      0.66        0.12  \n",
              "GammaRegressor                                  0.65        0.18  \n",
              "PoissonRegressor                                0.65        0.16  \n",
              "LassoCV                                         0.64       32.64  \n",
              "ElasticNetCV                                    0.64       32.89  \n",
              "XGBRegressor                                    0.64        3.14  \n",
              "BayesianRidge                                   0.64        1.27  \n",
              "GradientBoostingRegressor                       0.63        1.19  \n",
              "SVR                                             0.63        2.09  \n",
              "NuSVR                                           0.63        1.80  \n",
              "HistGradientBoostingRegressor                   0.61       11.39  \n",
              "LGBMRegressor                                   0.61        0.42  "
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Adjusted R-Squared</th>\n",
              "      <th>R-Squared</th>\n",
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              "      <th>Time Taken</th>\n",
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              "    <tr>\n",
              "      <th>Model</th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Lars</th>\n",
              "      <td>633212450295463665343799527169064960.00</td>\n",
              "      <td>-1178021863699028304304484048200269824.00</td>\n",
              "      <td>1021405320329878912.00</td>\n",
              "      <td>0.66</td>\n",
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              "      <th>RANSACRegressor</th>\n",
              "      <td>343678282839387237515264.00</td>\n",
              "      <td>-639375506710937930301440.00</td>\n",
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              "      <td>31.33</td>\n",
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              "      <td>144480431532956121563136.00</td>\n",
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              "      <th>LinearRegression</th>\n",
              "      <td>135672652845232980754432.00</td>\n",
              "      <td>-252403993767267857858560.00</td>\n",
              "      <td>472791381783.18</td>\n",
              "      <td>0.48</td>\n",
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              "      <th>KernelRidge</th>\n",
              "      <td>26.99</td>\n",
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              "      <td>-32.22</td>\n",
              "      <td>5.42</td>\n",
              "      <td>1.87</td>\n",
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              "      <th>LinearSVR</th>\n",
              "      <td>1.59</td>\n",
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              "      <td>0.99</td>\n",
              "      <td>1.48</td>\n",
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              "      <th>MLPRegressor</th>\n",
              "      <td>1.58</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>0.98</td>\n",
              "      <td>3.79</td>\n",
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              "    <tr>\n",
              "      <th>PassiveAggressiveRegressor</th>\n",
              "      <td>1.56</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lasso</th>\n",
              "      <td>1.54</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.12</td>\n",
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              "    <tr>\n",
              "      <th>LassoLars</th>\n",
              "      <td>1.54</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ElasticNet</th>\n",
              "      <td>1.54</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.07</td>\n",
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              "      <th>DummyRegressor</th>\n",
              "      <td>1.54</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.06</td>\n",
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              "    <tr>\n",
              "      <th>LarsCV</th>\n",
              "      <td>1.50</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.91</td>\n",
              "      <td>2.94</td>\n",
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              "    <tr>\n",
              "      <th>Ridge</th>\n",
              "      <td>1.47</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.88</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LassoLarsCV</th>\n",
              "      <td>1.39</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.81</td>\n",
              "      <td>0.59</td>\n",
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              "    <tr>\n",
              "      <th>LassoLarsIC</th>\n",
              "      <td>1.39</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.81</td>\n",
              "      <td>0.14</td>\n",
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              "      <th>HuberRegressor</th>\n",
              "      <td>1.38</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.80</td>\n",
              "      <td>0.92</td>\n",
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              "      <th>ExtraTreeRegressor</th>\n",
              "      <td>1.38</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.79</td>\n",
              "      <td>0.17</td>\n",
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              "      <th>DecisionTreeRegressor</th>\n",
              "      <td>1.38</td>\n",
              "      <td>0.29</td>\n",
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              "      <th>ExtraTreesRegressor</th>\n",
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              "      <td>0.32</td>\n",
              "      <td>0.77</td>\n",
              "      <td>4.57</td>\n",
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              "      <th>AdaBoostRegressor</th>\n",
              "      <td>1.34</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.79</td>\n",
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              "      <th>RidgeCV</th>\n",
              "      <td>1.34</td>\n",
              "      <td>0.37</td>\n",
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              "      <th>OrthogonalMatchingPursuitCV</th>\n",
              "      <td>1.29</td>\n",
              "      <td>0.47</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.46</td>\n",
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              "    <tr>\n",
              "      <th>OrthogonalMatchingPursuit</th>\n",
              "      <td>1.28</td>\n",
              "      <td>0.49</td>\n",
              "      <td>0.67</td>\n",
              "      <td>0.12</td>\n",
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              "      <th>BaggingRegressor</th>\n",
              "      <td>1.27</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.67</td>\n",
              "      <td>0.45</td>\n",
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              "      <th>KNeighborsRegressor</th>\n",
              "      <td>1.26</td>\n",
              "      <td>0.51</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.81</td>\n",
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              "      <td>1.26</td>\n",
              "      <td>0.51</td>\n",
              "      <td>0.66</td>\n",
              "      <td>3.51</td>\n",
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              "      <td>1.26</td>\n",
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              "      <td>0.66</td>\n",
              "      <td>0.16</td>\n",
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              "      <td>1.26</td>\n",
              "      <td>0.51</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.12</td>\n",
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              "    <tr>\n",
              "      <th>GammaRegressor</th>\n",
              "      <td>1.26</td>\n",
              "      <td>0.52</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.18</td>\n",
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              "      <th>PoissonRegressor</th>\n",
              "      <td>1.25</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.16</td>\n",
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              "      <th>LassoCV</th>\n",
              "      <td>1.25</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.64</td>\n",
              "      <td>32.64</td>\n",
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              "      <td>0.53</td>\n",
              "      <td>0.64</td>\n",
              "      <td>32.89</td>\n",
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              "      <td>1.25</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.64</td>\n",
              "      <td>3.14</td>\n",
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              "      <th>BayesianRidge</th>\n",
              "      <td>1.25</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.64</td>\n",
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              "      <td>1.24</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.63</td>\n",
              "      <td>1.19</td>\n",
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              "      <th>SVR</th>\n",
              "      <td>1.24</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.63</td>\n",
              "      <td>2.09</td>\n",
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              "      <th>NuSVR</th>\n",
              "      <td>1.24</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.63</td>\n",
              "      <td>1.80</td>\n",
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              "      <td>1.22</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.61</td>\n",
              "      <td>11.39</td>\n",
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              "      <td>0.58</td>\n",
              "      <td>0.61</td>\n",
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              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-dea9d96c-4bfe-4b3e-a738-37c44c694cdc button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-dea9d96c-4bfe-4b3e-a738-37c44c694cdc');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train = X_train.astype('int32')\n",
        "Y_train = Y_train.astype('float64')"
      ],
      "metadata": {
        "id": "ekoYHjCWJ85J"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestRegressor"
      ],
      "metadata": {
        "id": "_XihFXnfKF2c"
      },
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
        "model.fit(X_train, Y_train)\n",
        "r2 = model.score(X_test, Y_test)\n",
        "r2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jQRueafWKCGK",
        "outputId": "3f03cdfd-5dae-407f-db0f-574d64e69e0c"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.510691268495264"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Try data with test sample\n",
        "\n",
        "Y_pred = model.predict(X_test)\n",
        "print(Y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IFcYvrWIKLvZ",
        "outputId": "3f5b86d6-b947-40c4-97a0-a920223ac6dd"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4.58498254 8.43111923 5.2576164  5.83708014 6.41639852 5.85292287\n",
            " 4.87983157 5.35062734 5.57683558 5.99596143 6.86435798 5.57791009\n",
            " 5.25683436 7.16168644 6.49257128 6.17729433 7.13432406 6.06704579\n",
            " 6.98649606 7.27280054 6.94950021 6.98233933 7.01257306 7.12892291\n",
            " 6.64313311 7.01828239 5.94673311 5.80227749 5.82100922 6.67523118\n",
            " 6.43446884 4.91450013 7.4509863  5.2757592  5.81382747 6.58818223\n",
            " 5.81849624 6.26641821 6.85672579 6.17248209 7.25094766 7.58812827\n",
            " 7.56636463 7.16241915 5.29946486 6.71494004 7.53686347 5.78848766\n",
            " 5.57343583 6.25568844 6.57072576 7.36076997 6.6409613  6.28954117\n",
            " 7.11551499 6.80046984 6.0326932  7.16767069 6.8656832  5.75041133\n",
            " 6.68499748 6.56100672 6.57573867 6.99266775 7.21104179 7.24493807\n",
            " 7.20727315 6.61625883 5.82188687 5.96705379 8.12693261 7.5261656\n",
            " 5.65498773 5.53679191 7.87102143 7.86292441 5.7279558  7.25885999\n",
            " 6.23235691 6.13042951 6.87547417 7.24548031 7.53686347 6.61958922\n",
            " 7.3232724  5.25727645 6.99450049 7.10700222 6.15378118 6.92202512\n",
            " 5.60588943 6.94370846 5.10750529 5.57112594 6.43004286 5.75161143\n",
            " 6.60503747 7.20196297 4.79102204 7.71351391 7.09018061 6.09886759\n",
            " 6.16736707 6.97356144 6.03183339 6.24563508 4.94150459 6.23856558\n",
            " 6.88317438 7.92083338 7.5243704  7.05865623 6.25568844 5.89697894\n",
            " 7.50743101 6.02767103 7.63253566 6.11869319 6.50012086 5.38714957\n",
            " 7.52236502 7.39663215 6.71198886 5.39146336 7.16308806 4.87983157\n",
            " 4.97488644 6.87285145 6.71198886 7.07701297 7.01288472 6.90320605\n",
            " 5.69774893 6.27377067 7.45944389 6.72793456 5.19033495 5.9468362\n",
            " 6.92070455 6.75275574 5.55751304 7.17159405 6.82468474 6.71198886\n",
            " 6.13922636 7.14506163 6.23990096 7.25500342 6.31868685 5.49031971\n",
            " 5.82611116 7.73172415 7.24492547 6.4934905  7.13638643 6.95514928\n",
            " 6.15380096 5.1141614  7.13224835 7.70145182 7.27743158 6.49892482\n",
            " 6.95074438 5.39807922 6.99648069 6.96554062 7.15597869 6.28693392\n",
            " 6.17470365 6.2384066  6.7437885  5.39423651 6.77002838 5.44134349\n",
            " 6.0051624  7.56094697 5.83021564 6.07235031 5.19844774 6.67059375\n",
            " 6.24795359 5.66277586 5.98836313 4.96779076 5.75027131 7.03578706\n",
            " 6.29561306 6.87673323 7.72713984 6.10377967 5.72593811 4.96458186\n",
            " 5.26674548 7.59827265 7.61333745 5.19795165 6.79104534 6.82942455\n",
            " 7.4509863  6.42478571 7.03960222 7.16061204 7.4276014  6.0051624\n",
            " 6.41531528 6.9712993  7.23507775 6.77836045 6.40375576 7.14312767\n",
            " 6.6859347  7.45944389 7.4509863  6.21442958 7.24648295 6.3793895\n",
            " 4.97488644 6.63438926 5.25989541 6.08327022 6.41355745 7.05567736\n",
            " 6.42478571 7.15349822 7.3834654  7.09100924 4.96933763 7.20065864\n",
            " 6.5888828  6.75522139 5.92714894 7.2799579  7.18039271 4.92257363\n",
            " 6.13377315 6.29759612 5.39146336 6.50157062 7.08813267 7.29659312\n",
            " 7.20645514 6.64569061 5.21256347 6.78469961 4.82361751 7.12996098\n",
            " 5.08659897 6.89316378 6.5532583  7.15727138 7.45345231 7.03369158\n",
            " 7.25500342 7.35246982 5.69735294 6.60905883 6.42661368 5.63888404\n",
            " 6.20996305 5.41612459 6.96631397 7.23637544 6.70724072 6.7522122\n",
            " 5.85292287 5.91459202 5.34612038 7.19446538 5.8670833  6.35820639\n",
            " 6.79022578 7.31084938 6.90028883 5.70062982 6.88993326 7.19351977\n",
            " 5.2757592  7.08145539 7.0701872  6.5532583  6.58475038 4.94150459\n",
            " 6.85857669 7.20545297 5.99292429 6.95626488 6.171382   6.09032679\n",
            " 5.08299222 6.84390368 5.95364454 5.96446814 5.96177314 7.49037524\n",
            " 6.26732955 6.57666592 6.25070572 6.87820943 6.9739297  7.20196297\n",
            " 6.55312844 4.92328871 6.47516997 6.26732955 6.53499799 6.5967169\n",
            " 6.46852915 6.35690266 5.96325691]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the absolute errors\n",
        "\n",
        "errors = abs(Y_pred - Y_test)\n",
        "print('Mean absolute errors:', round(np.mean(errors), 2), 'degrees.')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dlf0wLSZKOqY",
        "outputId": "983d8f65-aeb8-4505-afbf-bafc3640bd96"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean absolute errors: 0.49 degrees.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate percentage of errors\n",
        "mape = 100 * (errors / Y_test)\n",
        "accuracy = 100 - np.mean(mape)\n",
        "print('Accuracy:', round(accuracy, 2), '%.')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4BR6pPliKSdp",
        "outputId": "3c1e2a0c-c065-48a9-f7c8-a72392a2497f"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 92.04 %.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Novel drugs prediction"
      ],
      "metadata": {
        "id": "d2JHkKTYrhO-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv('drugs.csv')"
      ],
      "metadata": {
        "id": "7IzoN5Rouiw5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pred = model_RF.predict([df])\n",
        "print(\"pIC50 prediction\", pred)"
      ],
      "metadata": {
        "id": "58LYkwX3sqn1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "drugs = pd.read_csv('drugs.csv')\n",
        "pred = model_RF.predict([drugs])\n",
        "print(\"pIC50 prediction\", pred)"
      ],
      "metadata": {
        "id": "0kkaWU7Yrg4o"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "generate model as Pickle Object"
      ],
      "metadata": {
        "id": "LaTzuIhrviJf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pickle"
      ],
      "metadata": {
        "id": "ffuVsyvmvWyt"
      },
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pickle.dump(model, open('IDH_model.pkl', 'wb'))"
      ],
      "metadata": {
        "id": "qV5fj0rovYW9"
      },
      "execution_count": 59,
      "outputs": []
    }
  ]
}