Similarity_ligandbased_screening4.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyO/Pafq/n0HsCJL97lqmyPJ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "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/Similarity_ligandbased_screening4.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Virtual screening"
      ],
      "metadata": {
        "id": "IwnuqmRtAmlY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rdkit"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wS_ngR5dEm9p",
        "outputId": "3b388298-3d54-4fa2-f644-0d80b5cfd943"
      },
      "execution_count": 2,
      "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 rdkit\n",
            "  Downloading rdkit-2022.3.5-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (36.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 36.8 MB 1.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from rdkit) (7.1.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from rdkit) (1.21.6)\n",
            "Installing collected packages: rdkit\n",
            "Successfully installed rdkit-2022.3.5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "PMKUrKwU_N6_"
      },
      "outputs": [],
      "source": [
        "from pathlib import Path\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from rdkit import Chem, DataStructs\n",
        "from rdkit.Chem import (\n",
        "    PandasTools,\n",
        "    Draw,\n",
        "    Descriptors,\n",
        "    MACCSkeys,\n",
        "    rdFingerprintGenerator,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Molecules in SMILES format\n",
        "molecule_smiles = [\n",
        "    \"CC1C2C(C3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4O)O)O)O)C(=O)N)N(C)C)O\",\n",
        "    \"CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=C(C=C3)O)N)C(=O)O)C\",\n",
        "    \"C1=COC(=C1)CNC2=CC(=C(C=C2C(=O)O)S(=O)(=O)N)Cl\",\n",
        "    \"CCCCCCCCCCCC(=O)OCCOC(=O)CCCCCCCCCCC\",\n",
        "    \"C1NC2=CC(=C(C=C2S(=O)(=O)N1)S(=O)(=O)N)Cl\",\n",
        "    \"CC1=C(C(CCC1)(C)C)C=CC(=CC=CC(=CC(=O)O)C)C\",\n",
        "    \"CC1(C2CC3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4O)O)O)O)C(=O)N)N(C)C)O\",\n",
        "    \"CC1C(CC(=O)C2=C1C=CC=C2O)C(=O)O\",\n",
        "]\n",
        "\n",
        "# List of molecule names\n",
        "molecule_names = [\n",
        "    \"Doxycycline\",\n",
        "    \"Amoxicilline\",\n",
        "    \"Furosemide\",\n",
        "    \"Glycol dilaurate\",\n",
        "    \"Hydrochlorothiazide\",\n",
        "    \"Isotretinoin\",\n",
        "    \"Tetracycline\",\n",
        "    \"Hemi-cycline D\",\n",
        "]"
      ],
      "metadata": {
        "id": "9M3RgOqhEvfE"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "molecules = pd.DataFrame({\"smiles\": molecule_smiles, \"name\": molecule_names})\n",
        "PandasTools.AddMoleculeColumnToFrame(molecules, smilesCol=\"smiles\")\n",
        "# Show first 2 molecules\n",
        "molecules.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "id": "iJBPaUowEx7y",
        "outputId": "0de8ba19-08be-4485-e68e-fcd8fea10a06"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                              smiles          name  \\\n",
              "0  CC1C2C(C3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...   Doxycycline   \n",
              "1  CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=C(C=C3)O)N)C...  Amoxicilline   \n",
              "\n",
              "                                               ROMol  \n",
              "0  <img data-content=\"rdkit/molecule\" src=\"data:i...  \n",
              "1  <img data-content=\"rdkit/molecule\" src=\"data:i...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8c042de5-eb53-457f-a84e-229067868f08\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>smiles</th>\n",
              "      <th>name</th>\n",
              "      <th>ROMol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CC1C2C(C3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...</td>\n",
              "      <td>Doxycycline</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" 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\" alt=\"Mol\"/></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=C(C=C3)O)N)C...</td>\n",
              "      <td>Amoxicilline</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8c042de5-eb53-457f-a84e-229067868f08')\"\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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              "  </svg>\n",
              "      </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",
              "      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-8c042de5-eb53-457f-a84e-229067868f08 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-8c042de5-eb53-457f-a84e-229067868f08');\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": [
        "Draw.MolsToGridImage(\n",
        "    molecules[\"ROMol\"].to_list(),\n",
        "    molsPerRow=3,\n",
        "    subImgSize=(450, 150),\n",
        "    legends=molecules[\"name\"].to_list(),\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "NqrhlCJzE3no",
        "outputId": "c17fb572-d48a-4607-e5b6-1546e448dafe"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1350x450 at 0x7F7AD36FECD0>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Note -- we use pandas apply function to apply the MolWt function\n",
        "# to all ROMol objects in the DataFrame\n",
        "molecules[\"molecule_weight\"] = molecules.ROMol.apply(Descriptors.MolWt)\n",
        "# Sort molecules by molecular weight\n",
        "molecules.sort_values([\"molecule_weight\"], ascending=False, inplace=True)"
      ],
      "metadata": {
        "id": "L3BUmluyFA24"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Show only molecule names and molecular weights\n",
        "molecules[[\"smiles\", \"name\", \"molecule_weight\"]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "4ndk80ByFEHw",
        "outputId": "5b8d7bf1-9030-48c4-a9d3-bf264d966bd4"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                              smiles                 name  \\\n",
              "0  CC1C2C(C3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...          Doxycycline   \n",
              "6  CC1(C2CC3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...         Tetracycline   \n",
              "3               CCCCCCCCCCCC(=O)OCCOC(=O)CCCCCCCCCCC     Glycol dilaurate   \n",
              "1  CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=C(C=C3)O)N)C...         Amoxicilline   \n",
              "2     C1=COC(=C1)CNC2=CC(=C(C=C2C(=O)O)S(=O)(=O)N)Cl           Furosemide   \n",
              "5         CC1=C(C(CCC1)(C)C)C=CC(=CC=CC(=CC(=O)O)C)C         Isotretinoin   \n",
              "4          C1NC2=CC(=C(C=C2S(=O)(=O)N1)S(=O)(=O)N)Cl  Hydrochlorothiazide   \n",
              "7                    CC1C(CC(=O)C2=C1C=CC=C2O)C(=O)O       Hemi-cycline D   \n",
              "\n",
              "   molecule_weight  \n",
              "0          444.440  \n",
              "6          444.440  \n",
              "3          426.682  \n",
              "1          365.411  \n",
              "2          330.749  \n",
              "5          300.442  \n",
              "4          297.745  \n",
              "7          220.224  "
            ],
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              "      <td>CC1C2C(C3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...</td>\n",
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              "      <th>6</th>\n",
              "      <td>CC1(C2CC3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...</td>\n",
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              "      <td>426.682</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=C(C=C3)O)N)C...</td>\n",
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              "      <td>365.411</td>\n",
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              "    <tr>\n",
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              "      <td>C1=COC(=C1)CNC2=CC(=C(C=C2C(=O)O)S(=O)(=O)N)Cl</td>\n",
              "      <td>Furosemide</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>CC1=C(C(CCC1)(C)C)C=CC(=CC=CC(=CC(=O)O)C)C</td>\n",
              "      <td>Isotretinoin</td>\n",
              "      <td>300.442</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>C1NC2=CC(=C(C=C2S(=O)(=O)N1)S(=O)(=O)N)Cl</td>\n",
              "      <td>Hydrochlorothiazide</td>\n",
              "      <td>297.745</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>CC1C(CC(=O)C2=C1C=CC=C2O)C(=O)O</td>\n",
              "      <td>Hemi-cycline D</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Draw.MolsToGridImage(\n",
        "    molecules[\"ROMol\"],\n",
        "    legends=[\n",
        "        f\"{molecule['name']}: {molecule['molecule_weight']:.2f} Da\"\n",
        "        for index, molecule in molecules.iterrows()\n",
        "    ],\n",
        "    subImgSize=(450, 150),\n",
        "    molsPerRow=3,\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "QMDormacFJkh",
        "outputId": "3b6486e3-39bd-44b9-c54b-a9e6550215b3"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1350x450 at 0x7F7ADC85A2D0>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "molecule = molecules[\"ROMol\"][0]\n",
        "molecule"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EdmfQDZKFPmx",
        "outputId": "8d6f0066-28da-47df-c51c-790e158ceaf0"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<rdkit.Chem.rdchem.Mol at 0x7f7ad3a09670>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "maccs_fp = MACCSkeys.GenMACCSKeys(molecule)"
      ],
      "metadata": {
        "id": "oYpCd1wnFV4p"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "molecules[\"maccs\"] = molecules.ROMol.apply(MACCSkeys.GenMACCSKeys)"
      ],
      "metadata": {
        "id": "Akm0V6NrFaji"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "circular_int_fp = rdFingerprintGenerator.GetCountFPs([molecule])[0]\n",
        "circular_int_fp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XhIpW23cFgoR",
        "outputId": "cae74d1c-9ee6-441a-e9f7-1ab8a4b34756"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<rdkit.DataStructs.cDataStructs.UIntSparseIntVect at 0x7f7ad1de8210>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"Print non-zero elements:\\n{circular_int_fp.GetNonzeroElements()}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PUdhmhz9FkSB",
        "outputId": "bb83f0d8-8c61-47d1-9733-489ee3e8ed99"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Print non-zero elements:\n",
            "{45: 1, 118: 1, 140: 1, 163: 1, 276: 1, 303: 1, 309: 1, 314: 2, 371: 1, 438: 1, 525: 1, 557: 1, 650: 3, 673: 1, 699: 1, 807: 6, 824: 1, 829: 1, 881: 1, 1009: 1, 1019: 5, 1027: 1, 1039: 1, 1057: 3, 1060: 1, 1061: 1, 1070: 1, 1082: 1, 1088: 1, 1119: 1, 1154: 1, 1163: 2, 1171: 1, 1257: 1, 1296: 1, 1309: 1, 1341: 1, 1380: 9, 1389: 1, 1457: 1, 1471: 1, 1487: 1, 1582: 1, 1602: 3, 1607: 1, 1630: 1, 1747: 1, 1750: 2, 1831: 1, 1833: 1, 1857: 1, 1873: 3, 1917: 1, 1932: 1, 2000: 1, 2029: 1}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Note that the function takes a list as input parameter\n",
        "# (even if we only want to pass one molecule)\n",
        "circular_bit_fp = rdFingerprintGenerator.GetFPs([molecule])[0]\n",
        "circular_bit_fp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5wY0TR5DFocC",
        "outputId": "cd04694b-fbf1-40b6-f7c6-a7b1d82ea52c"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<rdkit.DataStructs.cDataStructs.ExplicitBitVect at 0x7f7ad1de89f0>"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"Print top 400 fingerprint bits:\\n{circular_bit_fp.ToBitString()[:400]}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kcc-7JeIFspR",
        "outputId": "aefd8e9f-3dc1-4dbb-db97-9a3cf262a2c4"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Print top 400 fingerprint bits:\n",
            "0000000000000000000000000000000000000000000001000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000010000000000000000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001000000000000000000000000001000001000010000000000000000000000000000000000000000000000000000000010000000000000000000000000000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "molecules[\"morgan\"] = rdFingerprintGenerator.GetFPs(molecules[\"ROMol\"].tolist())"
      ],
      "metadata": {
        "id": "wdt0ZnleFx5q"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Example molecules\n",
        "molecule1 = molecules[\"ROMol\"][0]\n",
        "molecule2 = molecules[\"ROMol\"][1]\n",
        "\n",
        "# Example fingerprints\n",
        "maccs_fp1 = MACCSkeys.GenMACCSKeys(molecule1)\n",
        "maccs_fp2 = MACCSkeys.GenMACCSKeys(molecule2)"
      ],
      "metadata": {
        "id": "-QcPiu3QF3Eh"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "DataStructs.TanimotoSimilarity(maccs_fp1, maccs_fp2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y_DmsFphF5vj",
        "outputId": "9f0d9f22-08da-4e44-d752-bb1928f84bdd"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.5909090909090909"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Define molecule query and list\n",
        "molecule_query = molecules[\"maccs\"][0]\n",
        "molecule_list = molecules[\"maccs\"].to_list()\n",
        "# Calculate similarty values between query and list elements\n",
        "molecules[\"tanimoto_maccs\"] = DataStructs.BulkTanimotoSimilarity(molecule_query, molecule_list)\n",
        "molecules[\"dice_maccs\"] = DataStructs.BulkDiceSimilarity(molecule_query, molecule_list)"
      ],
      "metadata": {
        "id": "KXZq_0ghGDyK"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "preview = molecules.sort_values([\"tanimoto_maccs\"], ascending=False).reset_index()\n",
        "preview[[\"name\", \"tanimoto_maccs\", \"dice_maccs\"]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "oLBgsIQDGIrB",
        "outputId": "b7e964ec-8be6-4ca5-fe1d-0bcdce5be20b"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  name  tanimoto_maccs  dice_maccs\n",
              "0          Doxycycline        1.000000    1.000000\n",
              "1         Tetracycline        0.928571    0.962963\n",
              "2         Amoxicilline        0.590909    0.742857\n",
              "3       Hemi-cycline D        0.403509    0.575000\n",
              "4           Furosemide        0.321839    0.486957\n",
              "5  Hydrochlorothiazide        0.306818    0.469565\n",
              "6         Isotretinoin        0.288136    0.447368\n",
              "7     Glycol dilaurate        0.149254    0.259740"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1bf41da3-e78a-434b-8f47-ee369fd907d3\">\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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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>tanimoto_maccs</th>\n",
              "      <th>dice_maccs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Doxycycline</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Tetracycline</td>\n",
              "      <td>0.928571</td>\n",
              "      <td>0.962963</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Amoxicilline</td>\n",
              "      <td>0.590909</td>\n",
              "      <td>0.742857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Hemi-cycline D</td>\n",
              "      <td>0.403509</td>\n",
              "      <td>0.575000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Furosemide</td>\n",
              "      <td>0.321839</td>\n",
              "      <td>0.486957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Hydrochlorothiazide</td>\n",
              "      <td>0.306818</td>\n",
              "      <td>0.469565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Isotretinoin</td>\n",
              "      <td>0.288136</td>\n",
              "      <td>0.447368</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Glycol dilaurate</td>\n",
              "      <td>0.149254</td>\n",
              "      <td>0.259740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-1bf41da3-e78a-434b-8f47-ee369fd907d3 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-1bf41da3-e78a-434b-8f47-ee369fd907d3');\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",
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            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def draw_ranked_molecules(molecules, sort_by_column):\n",
        "    \"\"\"\n",
        "    Draw molecules sorted by a given column.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    molecules : pandas.DataFrame\n",
        "        Molecules (with \"ROMol\" and \"name\" columns and a column to sort by.\n",
        "    sort_by_column : str\n",
        "        Name of the column used to sort the molecules by.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Draw.MolsToGridImage\n",
        "        2D visualization of sorted molecules.\n",
        "    \"\"\"\n",
        "\n",
        "    molecules_sorted = molecules.sort_values([sort_by_column], ascending=False).reset_index()\n",
        "    return Draw.MolsToGridImage(\n",
        "        molecules_sorted[\"ROMol\"],\n",
        "        legends=[\n",
        "            f\"#{index+1} {molecule['name']}, similarity={molecule[sort_by_column]:.2f}\"\n",
        "            for index, molecule in molecules_sorted.iterrows()\n",
        "        ],\n",
        "        molsPerRow=3,\n",
        "        subImgSize=(450, 150),\n",
        "    )"
      ],
      "metadata": {
        "id": "3XGUf57tGRHI"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "draw_ranked_molecules(molecules, \"tanimoto_maccs\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "1GaWEV_xGV8I",
        "outputId": "21a57a6c-76cf-4b12-a43a-78333889280d"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1350x450 at 0x7F7AD1DEC590>"
            ],
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iYikpqeTk5A4dOnh4eGzevLlbt241d798+TIvztOnT4nI2tp6/vz5bDedjo7OggUL3r596+joSEQRERGurq5Dhgzx9vbW1taWkZGJjY3lhWKH9NfsUJKTk6s7Svbo0aMWFhaqqqrz5s1btGjRvHnzIiIinjx50qtXr4b9MgGg5QkICBw/fnzWrFmLFy/u37+/p6fnuXPnREVFs7OzlZSUfv/999DQ0EWLFqmpqdXc6/3796qqqrwf/fz82GUyiGjKlCnr1q3Lz8+XlZW9evXq5cuXBw0a5OHhYWxsXFVVJSgo2K5du7t375qamlZUVGhqas6YMaNWSm/evDl37lxCQoKUlBQ7l77WBuwplE3D3d39k+9r8+bNAwYMIKI7d+6wz7x48SIgIGD58uXnz59fuHDhoEGDDh06pK+vf/r0aSIaPHjwvXv3pkyZUiuTNm3a7Nu3jy2kedavXz9kyJDk5OROnTplZ2fLyMh069bt/PnzEydOrPnB8g79/PnzgIAAIlq5cuWECROuXr366tUrIyOjmTNnnjt3jj3NTp061dXV1djY+N69e/369RMSEiooKOBFKy8vr3ua/dwCBFpaWnp6etnZ2bGxsb/++mtoaGjdpRAAAAC+VyjpvyuRkZG+vr6+vr6dOnVKTEz88OHD5cuXhwwZ0qlTJyL6888/582bJyUlVXdHCwuLgQMHdurU6aeffvr9999jY2Pnz5/PvmRkZFSzmmWxl1nJycnV1dWzZs1in/zcJRSvMpeUlCwtLY2NjZ09ezb7jLGxcc3LU3YRJkFBQTExsdLS0lpxevToMXny5M6dO48ZM+aPP/7gPc92l7FrzrGJSUhIlJWV1dp9z549ly9fFhERiY+PZ6ce1BrkWdPMmTONjY2PHj165cqVGTNm9O3bt9Y6f+7u7jWvPvPz82s1QLi5uR08eJBtO/jjjz+uX78eFxc3ffr0hISExi4ECAAtKCIiIiAgICAgwMjIKCIioqCgwMXFZfjw4StWrJg8efK2bduSkpImTpy4e/fuLVu28PZSVVWt2Wx35coVXke9nJzcwIEDb9++bWpqyhbwubm5bJOikJBQUVFReno6+6OIiIi+vn5CQkLdlIyNjT95cmYdPnz47NmzwsLCb9++rdVYycOe0LhcroODg5ubm5iYWHR0dFFRUc1t4uLiQkND2ZFEgoKCNVebYw0aNIj9ypg4ceLvv//Oe553mhUQEGCrfQkJiVpnaS6X++uvv969e7fmoes/zY4dO9bR0ZE9zQ4aNIhdpJAnKSmp/tMsT/fu3dmVEYgoJSXl0qVLGIQPAAA/DpT035WKigqGYXJychQVFRMTEzU1NYlIRESEiAoLC8+ePfu59ZyEhYXPnj2bn58/a9asI0eOqKqqpqSksC+lpKSww8s5HA6Xy625l4qKCofDuXPnTs0l3OtuVkut4KqqqjUHW9ZDQEDg2LFje/bssba23r9/f0N24fHz83N2dn7x4oWEhASvDaIWDodTXV3NPu7QoUPXrl0fPHhw7969nTt3Hj169MyZM7wt2Qm3cXFxWVlZSkpKBQUFr1+/NjEx4W1w+PDho0ePPnr0iG1M4XA4bFdYVlZWUFDQJwdKAMDXUVFRUVVVVVRUJCsrGxMTo62tTUSioqLR0dFLliwhInV19Z9++unNmzc19+rZs+fly5d5E3lqmTVrlrOzc3x8/IwZM2RkZERERFJTU9mlQyQlJaWkpFJTU9kTckpKSt1h4TX7n4uLi2u9GhERsXfvXrb/nM1QUFCQd7LiPWDdv3//77//DgkJERERGTVqFPsk77Ssqqo6dOjQ48ePf+7DERUVdXJycnR0nD59ej2bfdL9+/cfPXrEHnrkyJGf3KbmadbIyEhGRsbT05NdLX/Xrl3Xr1/nbTlv3rzhw4eHhYUVFxdLSkqmpaWlpaWxCxPUVV5eLioqyvux7uQyAACA7xhK+u+KsbGxrKzspUuXbGxs/vrrLyKysbFhXzpz5szIkSM/15EeEhLi4+Ojrq6enZ2toqJia2u7bNkySUnJnJycO3fuBAcHE1Hnzp2dnZ151TgRKSgoTJ48ed68efPmzUtLS5OTk5s4caKuru61a9ekpKQ+t07yokWLJk2a1K5du6qqqtOnTz969GjRokV1N6uqqlq0aNG+fft4Ewdev3597949HR2dzMxMMzOzRn0y4uLixcXFT58+TU5OZmfL191GW1s7JibmypUrOjo6JiYms2bNWrNmjbGxsYKCgq2tra2tba3tZ86cydb2f/3114QJE9TV1Tds2GBlZbVr1647d+5s2rSJHTExdOjQpKSkhIQEhmGOHj06f/58XV3dRiUPAC3I1NRUQkLizp07NjY2p06dkpaWZs+TU6dO3bRpU3l5eUlJyYkTJ44ePVpzr7Vr1/bp02f8+PETJ05k14cbO3Ys79WxVkwQbAAABMlJREFUY8cuWbIkKirq6dOnAgICy5Ytmz9//qpVq7Kzszt37mxra7tw4cJVq1Y9efJESkrK1NS0VkoDBgzIy8vbvn27sbExOympJjExsfLych8fnw8fPri5ua1cudLY2NjV1VVNTe3evXsZGRk1N5aQkPj48aOXl1d0dHRQUBA73qpz584uLi45OTlz5szp1auXoaGhhoZGYGCgtbX1rl27jh07xquBAwMD/f39O3TokJOT09gZ6eLi4gUFBV5eXlFRUcHBwZ9s/tDV1Q0NDb1+/bqenl7Xrl1nzpy5aNGiYcOGiYuLb9y4cePGjbW2HzJkyKRJk6ZPn37y5Elra2t5efnly5evXbs2MTExLi6upKTkypUrPXv2fPjwYVxc3OTJk6Ojo0NDQ0+cONGozAEAAPgaSvrvjYCAwLp164iIt9IyS0lJqeYgUp6RI0cKCwsrKytXVlY+e/bM1tbWysqKw+FcvHjx7t27kpKS7OUdETk5OZ06dSo9PX3mzJlsvxYRnTt37sKFC56enmpqasOHDyeiTZs2HT9+PCkpqU+fPmJiYqKiorzafubMmZqamt26dbt///7NmzcFBAQ8PT319fUXLFigpaW1dOlSHR0ddsutW7fKycnFxcUxDMNLVV5eXlBQ0MfHx8rKat68eTIyMpqamra2tmwyHA7H0dGRHZKgoaGxYsWKLl26zJ49W19ff/bs2SYmJgcPHnzw4IGRkdHNmzclJSVlZWUNDAzYD4q99FRXV79x44avry/7fqdMmXLo0KG6s155Tpw4ce7cuVevXk2ZMoW9bm7fvr24uHi3bt3YkbF5eXlEVFFRoaCg8OTJk7Kysl27dn3ydgMA8DWJioquWrWKiDp37sxrH9y+fbupqamPjw+Hw7ly5QpvVVEWe5uMa9euvXr1SlpaesOGDWPHjr137x57/hEXF1+9evX9+/fZrvi9e/feunUrMDBQQUFBXV199+7d169f9/Hx0dDQ2LZtG8MwtYaFi4mJBQUFOTs7h4WFnTlzxtfXV0tLy9raulOnTvPnz9fR0Tlz5szDhw/19fVv3bpFREZGRpKSkk+ePJk2bdrgwYM7dOiwfv16dvn3IUOGbN68+e7du717975x4wb75MGDB52cnNLT01VUVAICAi5duvT06dPevXtLS0tHRUXVHH6vqqpaXl7u6+u7YsWK2bNnFxYWqqiorFu3jl1ZQFJScufOneyW+vr6NjY2enp67HtUVlYeOnQoe2gzM7Pr16+rqanZ2dmx69ix1TububOz8/Pnz9nn58yZc/LkyXpOs66urs7OzuHh4TY2NlZWVkTUsWNHUVHR4uLivLw8tgmgqKho3759t27dev78uYKCwvPnz7E8HgAA/FA4NUsmgG/K+fPnf/7559Y6emVlpZaWVlRUVD0TXAEAWPb29u3bt1++fHlrJ9I4rXua/fjxY9euXRMSEoSFhVsrBwAAAH6Hkh7g0+7du3fx4kVXV9fWTgQAvnUMw+jo6Pj6+tZcFR/+k4uLS3BwcK05DgAAANAoKOkBPo3tOGIXuAIAqEdFRUVoaGit+2LAf4qOjpaRkWFnBwAAAEDToKQHAAAAAAAA4EsCrZ0AAAAAAAAAADQFSnoAAAAAAAAAvvR/qp3jlx/bZoAAAAAASUVORK5CYII=\n"
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Define molecule query and list\n",
        "molecule_query = molecules[\"morgan\"][0]\n",
        "molecule_list = molecules[\"morgan\"].to_list()\n",
        "# Calculate similarty values between query and list elements\n",
        "molecules[\"tanimoto_morgan\"] = DataStructs.BulkTanimotoSimilarity(molecule_query, molecule_list)\n",
        "molecules[\"dice_morgan\"] = DataStructs.BulkDiceSimilarity(molecule_query, molecule_list)"
      ],
      "metadata": {
        "id": "IODdVQqKGgMB"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "preview = molecules.sort_values([\"tanimoto_morgan\"], ascending=False).reset_index()\n",
        "preview[[\"name\", \"tanimoto_morgan\", \"dice_morgan\", \"tanimoto_maccs\", \"dice_maccs\"]]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "fivuZHjlGipq",
        "outputId": "bb1dce1d-e7ee-44cf-ab22-5ec7a863120c"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  name  tanimoto_morgan  dice_morgan  tanimoto_maccs  \\\n",
              "0          Doxycycline         1.000000     1.000000        1.000000   \n",
              "1         Tetracycline         0.534247     0.696429        0.928571   \n",
              "2       Hemi-cycline D         0.308824     0.471910        0.403509   \n",
              "3         Amoxicilline         0.144444     0.252427        0.590909   \n",
              "4           Furosemide         0.098901     0.180000        0.321839   \n",
              "5         Isotretinoin         0.067416     0.126316        0.288136   \n",
              "6  Hydrochlorothiazide         0.058824     0.111111        0.306818   \n",
              "7     Glycol dilaurate         0.054795     0.103896        0.149254   \n",
              "\n",
              "   dice_maccs  \n",
              "0    1.000000  \n",
              "1    0.962963  \n",
              "2    0.575000  \n",
              "3    0.742857  \n",
              "4    0.486957  \n",
              "5    0.447368  \n",
              "6    0.469565  \n",
              "7    0.259740  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b4733148-5b06-4da9-8097-acbb5459478c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        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>name</th>\n",
              "      <th>tanimoto_morgan</th>\n",
              "      <th>dice_morgan</th>\n",
              "      <th>tanimoto_maccs</th>\n",
              "      <th>dice_maccs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Doxycycline</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Tetracycline</td>\n",
              "      <td>0.534247</td>\n",
              "      <td>0.696429</td>\n",
              "      <td>0.928571</td>\n",
              "      <td>0.962963</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Hemi-cycline D</td>\n",
              "      <td>0.308824</td>\n",
              "      <td>0.471910</td>\n",
              "      <td>0.403509</td>\n",
              "      <td>0.575000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Amoxicilline</td>\n",
              "      <td>0.144444</td>\n",
              "      <td>0.252427</td>\n",
              "      <td>0.590909</td>\n",
              "      <td>0.742857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Furosemide</td>\n",
              "      <td>0.098901</td>\n",
              "      <td>0.180000</td>\n",
              "      <td>0.321839</td>\n",
              "      <td>0.486957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Isotretinoin</td>\n",
              "      <td>0.067416</td>\n",
              "      <td>0.126316</td>\n",
              "      <td>0.288136</td>\n",
              "      <td>0.447368</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Hydrochlorothiazide</td>\n",
              "      <td>0.058824</td>\n",
              "      <td>0.111111</td>\n",
              "      <td>0.306818</td>\n",
              "      <td>0.469565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Glycol dilaurate</td>\n",
              "      <td>0.054795</td>\n",
              "      <td>0.103896</td>\n",
              "      <td>0.149254</td>\n",
              "      <td>0.259740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b4733148-5b06-4da9-8097-acbb5459478c')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </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",
              "      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-b4733148-5b06-4da9-8097-acbb5459478c 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-b4733148-5b06-4da9-8097-acbb5459478c');\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": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "draw_ranked_molecules(molecules, \"tanimoto_morgan\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "UHv5-rSKGqbt",
        "outputId": "85c69163-cbc0-4d92-97be-7eb99405f616"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1350x450 at 0x7F7AD1DECC10>"
            ],
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\n"
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(figsize=(6, 6))\n",
        "molecules.plot(\"tanimoto_maccs\", \"tanimoto_morgan\", kind=\"scatter\", ax=ax)\n",
        "ax.plot([0, 1], [0, 1], \"k--\")\n",
        "ax.set_xlabel(\"Tanimoto (MACCS)\")\n",
        "ax.set_ylabel(\"Tanimoto (Morgan)\")\n",
        "fig;"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "id": "3o5w6sDyGwYN",
        "outputId": "c8aca69b-18b5-4660-e939-de038c80adfa"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "molecule_dataset = pd.read_csv(\n",
        "    \"TNFB_compounds_lipinski.csv\",\n",
        "    usecols=[\"molecule_chembl_id\", \"smiles\", \"pIC50\"],\n",
        ")\n",
        "print(f\"Number of molecules in dataset: {len(molecule_dataset)}\")\n",
        "molecule_dataset.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "id": "wH-Q8hyv9XZn",
        "outputId": "5daa6710-bb7e-4ad2-af32-91106f0d659f"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of molecules in dataset: 49\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  molecule_chembl_id                                             smiles  \\\n",
              "0       CHEMBL336546  O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...   \n",
              "1       CHEMBL131636  CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...   \n",
              "2       CHEMBL134490  CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...   \n",
              "3       CHEMBL135133       O=C(Nc1ccc(C(F)(F)F)cc1)c1cnc(Cl)nc1C(F)(F)F   \n",
              "4       CHEMBL334485         O=C(Nc1cc(Cl)cc(Cl)c1)c1cnc(Cl)nc1C(F)(F)F   \n",
              "\n",
              "      pIC50  \n",
              "0  7.301030  \n",
              "1  6.769551  \n",
              "2  6.552842  \n",
              "3  6.420216  \n",
              "4  6.301030  "
            ],
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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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL336546</td>\n",
              "      <td>O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...</td>\n",
              "      <td>7.301030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL131636</td>\n",
              "      <td>CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...</td>\n",
              "      <td>6.769551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL134490</td>\n",
              "      <td>CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...</td>\n",
              "      <td>6.552842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL135133</td>\n",
              "      <td>O=C(Nc1ccc(C(F)(F)F)cc1)c1cnc(Cl)nc1C(F)(F)F</td>\n",
              "      <td>6.420216</td>\n",
              "    </tr>\n",
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              "      <th>4</th>\n",
              "      <td>CHEMBL334485</td>\n",
              "      <td>O=C(Nc1cc(Cl)cc(Cl)c1)c1cnc(Cl)nc1C(F)(F)F</td>\n",
              "      <td>6.301030</td>\n",
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              "                                                     [key], {});\n",
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              "\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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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "query = Chem.MolFromSmiles(\"O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1C(F)(F)F\")\n",
        "query"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3WmxmCzj97WQ",
        "outputId": "9dfbae64-fc68-4a4f-8da8-61d86dee9049"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<rdkit.Chem.rdchem.Mol at 0x7fdbdfb218a0>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "maccs_fp_query = MACCSkeys.GenMACCSKeys(query)\n",
        "circular_fp_query = rdFingerprintGenerator.GetCountFPs([query])[0]"
      ],
      "metadata": {
        "id": "GkcDaxez-OuP"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PandasTools.AddMoleculeColumnToFrame(molecule_dataset, \"smiles\")\n",
        "circular_fp_list = rdFingerprintGenerator.GetCountFPs(molecule_dataset[\"ROMol\"].tolist())\n",
        "maccs_fp_list = molecule_dataset[\"ROMol\"].apply(MACCSkeys.GenMACCSKeys).tolist()"
      ],
      "metadata": {
        "id": "n2bzjaPD-SfH"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "molecule_dataset[\"tanimoto_maccs\"] = DataStructs.BulkTanimotoSimilarity(\n",
        "    maccs_fp_query, maccs_fp_list\n",
        ")\n",
        "molecule_dataset[\"tanimoto_morgan\"] = DataStructs.BulkTanimotoSimilarity(\n",
        "    circular_fp_query, circular_fp_list\n",
        ")"
      ],
      "metadata": {
        "id": "fxxsJrac-WAw"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "molecule_dataset[\"dice_maccs\"] = DataStructs.BulkDiceSimilarity(maccs_fp_query, maccs_fp_list)\n",
        "molecule_dataset[\"dice_morgan\"] = DataStructs.BulkDiceSimilarity(\n",
        "    circular_fp_query, circular_fp_list\n",
        ")"
      ],
      "metadata": {
        "id": "PQT4ako_-YoL"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# NBVAL_CHECK_OUTPUT\n",
        "molecule_dataset[\n",
        "    [\"smiles\", \"tanimoto_maccs\", \"tanimoto_morgan\", \"dice_maccs\", \"dice_morgan\"]\n",
        "].head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "6ESskO7s-aVb",
        "outputId": "7eb31db8-af3c-4281-b51e-6eca2a4b1142"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                              smiles  tanimoto_maccs  \\\n",
              "0  O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...        1.000000   \n",
              "1  CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...        0.680000   \n",
              "2  CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...        0.755556   \n",
              "3       O=C(Nc1ccc(C(F)(F)F)cc1)c1cnc(Cl)nc1C(F)(F)F        1.000000   \n",
              "4         O=C(Nc1cc(Cl)cc(Cl)c1)c1cnc(Cl)nc1C(F)(F)F        1.000000   \n",
              "\n",
              "   tanimoto_morgan  dice_maccs  dice_morgan  \n",
              "0         1.000000    1.000000     1.000000  \n",
              "1         0.625000    0.809524     0.769231  \n",
              "2         0.666667    0.860759     0.800000  \n",
              "3         0.630952    1.000000     0.773723  \n",
              "4         0.571429    1.000000     0.727273  "
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              "                                                     [key], {});\n",
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              "\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "# Show all columns\n",
        "molecule_dataset.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 767
        },
        "id": "4lvx2Tx--fkQ",
        "outputId": "e52833d8-fff0-4c9f-f93e-8ca321622050"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  molecule_chembl_id                                             smiles  \\\n",
              "0       CHEMBL336546  O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...   \n",
              "1       CHEMBL131636  CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...   \n",
              "2       CHEMBL134490  CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...   \n",
              "\n",
              "      pIC50                                              ROMol  \\\n",
              "0  7.301030  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "1  6.769551  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "2  6.552842  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "\n",
              "   tanimoto_maccs  tanimoto_morgan  dice_maccs  dice_morgan  \n",
              "0        1.000000         1.000000    1.000000     1.000000  \n",
              "1        0.680000         0.625000    0.809524     0.769231  \n",
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              "      <td>7.301030</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" 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\" alt=\"Mol\"/></td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL131636</td>\n",
              "      <td>CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...</td>\n",
              "      <td>6.769551</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>0.680000</td>\n",
              "      <td>0.625000</td>\n",
              "      <td>0.809524</td>\n",
              "      <td>0.769231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL134490</td>\n",
              "      <td>CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...</td>\n",
              "      <td>6.552842</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>0.755556</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.860759</td>\n",
              "      <td>0.800000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-60336623-78fe-4558-832f-aa4b9f328689')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </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",
              "      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-60336623-78fe-4558-832f-aa4b9f328689 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-60336623-78fe-4558-832f-aa4b9f328689');\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": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axes = plt.subplots(figsize=(10, 6), nrows=2, ncols=2)\n",
        "molecule_dataset.hist([\"tanimoto_maccs\"], ax=axes[0, 0])\n",
        "molecule_dataset.hist([\"tanimoto_morgan\"], ax=axes[0, 1])\n",
        "molecule_dataset.hist([\"dice_maccs\"], ax=axes[1, 0])\n",
        "molecule_dataset.hist([\"dice_morgan\"], ax=axes[1, 1])\n",
        "axes[1, 0].set_xlabel(\"similarity value\")\n",
        "axes[1, 0].set_ylabel(\"# molecules\")\n",
        "fig;"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "id": "7mySir-w-kah",
        "outputId": "0a559dad-5206-4410-9611-db50444b433c"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 4 Axes>"
            ],
            "image/png": 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OiNcWGZuZWbdIOgcYBmZKWg0cDwxL2p3ksuYq4KjSAjSzyij7suZ+wK0RcXvJcZiZdVVEHNZk9ZmFB2JmlVd2cnYocE6LbS+RdB1wJ/DBiLi+WaHGm2Tz3oTXrZtkAQY26fz+i74xss43Y47rhTpAb9SjF+pgZlaU0pIzSRsDBwEfabL5GmD7iBhNn5h9AbBTs/003iSb9ya8bt0kC0liduqKzr61k735drLqfDPmuF6oA/RGPXqhDmZmRSnzOWevAa7J9lYaFxEPRcRoOn8RsJGkmUUHaGZmZla0MpOzw2hxSVPScyUpnd+LJM57C4zNzMzMrBSlXNaUNA14FZmeSZLeAxARZwCHAEdLGgN+BxwaEVFGrGZmZmZFKiU5i4hHgGc3rDsjM386cHrRcZmZmZmVzWNrmpmZmVWIkzMzMzOzCnFyZmZmZlYhTs7MzMzMKsTJmZmZmVmFODkzMzMzqxAnZ2ZmZmYV4uTMzMzMrEKcnJmZmZlVSCkjBJhVzeBxS7uy31WnHNiV/ZqZWe/ymTMzMzOzCnFyZmZWAEmLJK2TtDKzbgtJl0i6Of27eZkxmlk1ODkzMyvGYmBOw7rjgB9GxE7AD9NlM+tzTs7MzAoQEcuA+xpWHwyclc6fBby+0KDMrJKcnJmZlWcgItam83cBA2UGY2bVUFpvTUmrgIeBx4CxiBhq2C7gP4G5wKPAvIi4pug4zcyKEBEhKVptlzQfmA8wMDDA6OgoIyMjE+53weyxjsWYlefYzeSNu2ocd7HqGjd0JvayH6Xxyoi4p8W21wA7pdPewBfSv2ZmveJuSVtFxFpJWwHrWhWMiIXAQoChoaGYPn06w8PDEx5gXrceE3P4xMduZmRkJFfcVeO4i1XXuKEzsVf5subBwFcicTmwWdp4mZn1iiXAEen8EcC3S4zFzCqizDNnAXw/PY3/xfRXYdY2wB2Z5dXpurXZQo2n+vOeSuzWqX6AgU06v/+iT+/W+ZTyuHbqULVLP1lFfhYr1jzYlf0+b9MNav99mipJ5wDDwExJq4HjgVOAb0g6ErgdeHN5EZpZVZSZnO0bEWskPQe4RNJNaW+mtjSe6s97KrFbp/oh+Y/+1BWdfWsnewlhsup8SnlcO3Wo2qWfrCI/i269D4vnTKv992mqIuKwFpv2KzQQM6u80i5rRsSa9O864Hxgr4Yia4BZmeVt03VmZmZmPauU5EzSNEkzxueBA4CVDcWWAG9XYh/gwUyXczMzM7OeVNZlzQHg/ORpGWwIfC0ivifpPQARcQZwEcljNG4heZTGO0qK1czMzKwwpSRnEXEb8KIm68/IzAfwviLjMjMzMytblR+lYWZmZtZ3nJyZmZmZVYiTMzMzM7MKcXJmZmZmViFlj61p1tMGO/BQ1wWzx57ycNhVpxw45f2amVk1+cyZmZmZWYX4zJmZmbVtsmeFm50JzvJZYTOfOTMzMzOrFCdnZmZmZhXi5MzMzMysQpycmZmZmVWIkzMzMzOzCnFyZmZmZlYhfpSGmVnJJK0CHgYeA8YiYqjciMysTE7O+lyrZxVN9CyiifhZRd3ViZEHrHJeGRH3lB2EmZWv8MuakmZJulTSDZKul/T+JmWGJT0oaXk6faLoOM3MzMzKUMaZszFgQURcI2kGcLWkSyLihoZyP46I15YQn5lZ0QL4vqQAvhgRCxsLSJoPzAcYGBhgdHSUkZGRCXe8YPZYh0OdmoFN1h9TnjqVIe/73Skr1jzYkf0MbAL/dfa3/7w8e5tNO7Lfbiv6/e6kTsReeHIWEWuBten8w5JuBLYBGpMzM7N+sW9ErJH0HOASSTdFxLJsgTRhWwgwNDQU06dPZ3h4eMIdT+X2hG5YMHuMU1e0/q9n1eHDxQXThpGRkVzvd6d06nNrfL+r+v42Kvr97qROxF7qPWeSBoE9gCuabH6JpOuAO4EPRsT1LfbxpF+TebPVbv6anOiX4WR06xdEqzinWocq/OJp59dL1c4uZHXj+1S0Ov8KLkJErEn/rpN0PrAXsGz9rzKzXlVaciZpOvAt4AMR8VDD5muA7SNiVNJc4AJgp2b7afw1mTdb7eavyYl+GU5Gt37ttHofplqHKvw6a+fXS9XOLmR14/tUtMVzptX2V3C3SZoGPC29kjANOAA4seSwzKxEpTznTNJGJInZ2RFxXuP2iHgoIkbT+YuAjSTNLDhMM7MiDACXpVcKrgSWRsT3So7JzEpU+M9xSQLOBG6MiE+3KPNc4O6ICEl7kSSR9xYYpplZISLiNuBFZcdhZtVRxrWSlwJvA1ZIWp6u+yiwHUBEnAEcAhwtaQz4HXBoREQJsZqZmbXkZw5aN5TRW/MyQBOUOR04vZiI6qFuDUAV4p3qg3TNzMzK4LE1zczMzCrEyZmZmZlZhTg5MzMzM6uQej88yczMzHLr1v3Aq045sCv77Vc+c2ZmZmZWIU7OzMzMzCrEyZmZmZlZhTg5MzMzM6sQdwgwM7OeN9Ub4f1QayuSz5yZmZmZVYiTMzMzM7MKcXJmZmZmViFOzszMzMwqxB0CzMzMbEo6PfLAeAeMbo080K2REgAWz5k25X34zJmZmZlZhZSSnEmaI+mXkm6RdFyT7U+XdG66/QpJg8VHaWZWjInaRDPrL4UnZ5I2AD4HvAbYBThM0i4NxY4E7o+IHYHTgE8WG6WZWTFytolm1kfKOHO2F3BLRNwWEX8Evg4c3FDmYOCsdP5/gf0kqcAYzcyKkqdNNLM+oogo9oDSIcCciHhXuvw2YO+IOCZTZmVaZnW6fGta5p4m+5sPzE8XdwZ+2eUq5DETeEqsNeM6VEcv1KOdOmwfEVt2M5gqydMmpusb27p7qef3oq7fZ8ddrLrGDR1o72rfWzMiFgILy44jS9JVETFUdhxT4TpURy/UoxfqULbGtq6u76njLpbjLl4nYi/jsuYaYFZmedt0XdMykjYENiX5lWhm1mvytIlm1kfKSM5+Duwk6XmSNgYOBZY0lFkCHJHOHwL8KIq+/mpmVow8baKZ9ZHCL2tGxJikY4CLgQ2ARRFxvaQTgasiYglwJvBVSbcA95E0VnVSqcusk+Q6VEcv1KMX6tAVrdrEHC+t63vquIvluIs35dgL7xBgZmZmZq15hAAzMzOzCnFyZmZmZlYhTs4mKccQVP8o6QZJv5D0Q0nblxHnRPIOGyPpbyWFpMp1bc5TB0lvTj+P6yV9regY88jxndpO0qWSrk2/V3PLiLMVSYskrUufU9hsuyR9Nq3fLyTtWXSMdVPnoe7q2kbWtU2saztY13av6+1dRHhqcyK5afdWYAdgY+A6YJeGMq8EnpnOHw2cW3bck6lHWm4GsAy4HBgqO+5JfBY7AdcCm6fLzyk77knWYyFwdDq/C7Cq7Lgb4ns5sCewssX2ucB3AQH7AFeUHXOVp5zfifcCZ6Tzh1alnalrG1nXNrGu7WCd271ut3c+czY5Ew63EhGXRsSj6eLlJM8uqpq8w8acRDK+6e+LDC6nPHV4N/C5iLgfICLWFRxjHnnqEcCz0vlNgTsLjG9CEbGMpHd1KwcDX4nE5cBmkrYqJrpaqvNQd3VtI+vaJta1Haxtu9ft9s7J2eRsA9yRWV6drmvlSJIMumomrEd6KnZWRCwtMrA25PksXgC8QNJPJF0uaU5h0eWXpx4nAG+VtBq4CPi7YkLrmHb/3fS7PO/Xn8tExBjwIPDsQqJbv7q2kXVtE+vaDvZyuzel9q72wzdVnaS3AkPAK8qOpV2SngZ8GphXcihTtSHJKf1hkl/nyyTNjogHSo2qfYcBiyPiVEkvIXkW4G4R8XjZgZlNVp3ayJq3iXVtB/uy3fOZs8nJNdyKpP2BjwEHRcQfCoqtHRPVYwawGzAiaRXJdfMlVbkBNpXns1gNLImIP0XEr4FfkTRSVZKnHkcC3wCIiJ8BzyAZYLcuPExRe+o81F1d28i6tol1bQd7ud2bWntX9k11dZxIfoHcBjyPJ25i3LWhzB4kNzruVHa8U6lHQ/kRKnDz6yQ+iznAWen8TJJTzc8uO/ZJ1OO7wLx0/oUk916o7NgbYhyk9Q2yB/LkG2SvLDveKk85vxPv48kdAr5RdtxtxF65NrKubWJd28G6t3vdbO9Kr1xdJ5KeGL9KG5ePpetOJPkFCPAD4G5geTotKTvmydSjoWwlGqJJfBYiuRRxA7ACOLTsmCdZj12An6QN2HLggLJjboj/HGAt8CeSX+lHAu8B3pP5HD6X1m9FFb9LVZtyfCeeAXwTuAW4Etih7JjbiL2SbWRd28S6toN1bfe63d55+CYzMzOzCvE9Z2ZmZmYV4uTMzMzMrEKcnJmZmZlViJMzMzMzswpxcmZmZmZWIU7OzMzMzCrEyZmZmZlZhTg5MzMzM6sQJ2dmZmZmFeLkzMzMzKxCnJyZmZmZVYiTMzMzswxJiyWdLOllkn5ZdjzWf5yc2aS5ATOzXhYRP46IncuOw/qPkzObMjdgZmbVIWnDsmOwqXFyZmZmfU3SHpKukfSwpHOBZ6TrhyWtzpSbJek8Sb+VdK+k0zPb3inpRkn3S7pY0vY5jhuS3ivp5vTYJ0l6vqSfSnpI0jckbZwp/25Jt0i6T9ISSVs37Ot9km4Gbk7XHStpraQ7Jb0rLbNjuu1ASdemx7lD0gmZfQ2mZY+Q9BtJ90j62JTeZGuLkzPLrQ4NmKTNJV2YHvv+dH7bzL62kPTfaWN1v6QLMtsOlrQ83eetkuak6+dJui099q8lHd6RN9TMSpe2HRcAXwW2AL4J/G2TchsAFwK3A4PANsDX020HAx8F3ghsCfwYOCdnCK8G/grYBzgWWAi8FZgF7AYclh7jb4B/A94MbJXG8fWGfb0e2BvYJW2//hHYH9gRGG4o+wjwdmAz4EDgaEmvbyizL7AzsB/wCUkvzFknm6qI8ORpwgnYmKQx+AdgI+AQ4E/AyST/6Fen5TYArgNOA6aRJHD7ptsOBm4BXghsCHwc+GmOYwfwbeBZwK7AH4AfAjsAmwI3AEekZZ9N0rA+E5hB0tBekNnXUuBcYPO0Hq9I1+8FPAi8iuRHyzbAX6R1eAjYOS23FbBr2Z+HJ0+eOjMBLwfuBJRZ99MmbdtLgN8CGzbZx3eBIzPLTwMeBbaf4NgBvDSzfDXw4czyqcBn0vkzgX/PbJuetsGDmX39TWb7IuDfMss7pmV2bBHLZ4DT0vnBtOy2me1XAoeW/Xn1y+QzZ5bXPiTJzGci4k8R8b/Az5uU2wvYGvhQRDwSEb+PiMvSbe8haSxujIgx4F+B3fOcPSNplB6KiOuBlcD3I+K2iHiQpGHcAyAi7o2Ib0XEoxHxMPAvwCsAJG0FvAZ4T0Tcn9bj/9L9HwksiohLIuLxiFgTETel2x4HdpO0SUSsTWMws96wNbAm0gwkdXuTcrOA29O2q9H2wH9KekDSA8B9gEh+5E3k7sz875osT8/E+ee4ImIUuLfhGHdk5rduWM7OI2lvSZemVxkeJGmfZzbEdldm/tFMLNZlTs4sr1o0YJKeKemLkm6X9BCwDNgsvSQxC7gvIu5vEfetjSsj4hHgLSQN11pJSyX9RY54zawe1gLbSFJm3XZNyt0BbNfiZvs7gKMiYrPMtElE/LSDcd5J0oYCIGkayZWCNZky2fZ5LbBtZnlWw/6+BiwBZkXEpsAZJO2xVYCTM8urLg3YApJ7JPaOiGeRXLKApNG5A9hC0mYtYnt+sx1GxMUR8SqSS5o3AV/qYLxmVq6fAWPA30vaSNIbSa4ANLqSpB08RdI0Sc+Q9NJ02xnARyTtCiBpU0lv6nCc5wDvkLS7pKeTXHm4IiJWtSj/jbT8CyU9E/inhu0zSH6s/l7SXsD/63C8NgVOziyvujRgM0jOpD0gaQvg+PENEbGW5BLo59OOAxtJGk/eziRpyPaT9DRJ20j6C0kDaUeBaST3uo2SXOY0sx4QEX8kuZF/HsnZ/LcA5zUp9xjwOpJ7t34DrE7LEhHnA58Evp6esV9JcgtFJ+P8AUmC9S2SNvb5wKHrKf9d4LPApST3+l6ebvpD+ve9wImSHgY+QZLMWUXoyVepzFqTNERy1mhH4KJ09c3AD4D/iYht03LbkTQKLyM5zf61iPj7dNvbSHokbU9yA/4lEfHOCZembjUAABnnSURBVI4bwE4RcUu6fBnw5YhYnC6fDDw3It6lpGv514AhkssAp5IkhRtFxFiasJ0GzCHp5HBpRLwx3c8bgH8Gnkdy2fR9wC9IekTtntZlOfDeiLhhMu+hmVkZ0p6WK4Gnt7jtxCrEyZmZmVkPSn9wXkTSe/0s4PGIaHxchlWQL2uamZl1gZKh7UabTQWFcBSwjqSz02PA0QUd16bIZ86sdJJeRnIv2FNEhLtum5lZX3FyZmZmZlYhPTU46syZM2NwcLCt1zzyyCNMmzatOwGVqFfrBa5bHbVTr6uvvvqeiNiyyyHV2mTauqLU/Tvs+MtV9/ihM+1dTyVng4ODXHXVVW29ZmRkhOHh4e4EVKJerRe4bnXUTr0kNXu4sWVMpq0rSt2/w46/XHWPHzrT3rlDgJmZmVmFODkzMzMzqxAnZ2ZmZmYV4uTMzMzMrEKcnJmZmZlVSE/11qyCweOWdmW/q045sCv7NTObjFZt3YLZY8ybQjvots7MZ87MzMzMKsXJmZmZmVmFODkzMzMzqxAnZ2ZmZmYV0rXkTNIiSeskrcysO0HSGknL02lui9fOkfRLSbdIOq5bMZqZmZlVTTfPnC0G5jRZf1pE7J5OFzVulLQB8DngNcAuwGGSdulinGZmZmaV0bXkLCKWAfdN4qV7AbdExG0R8Ufg68DBHQ3OzMzMrKLKeM7ZMZLeDlwFLIiI+xu2bwPckVleDezdameS5gPzAQYGBhgZGWkrmNHR0bZfsz4LZo91bF9ZZderSly3+unVepmZdUPRydkXgJOASP+eCrxzKjuMiIXAQoChoaEYHh5u6/UjIyO0+5r1mcrDF9dn1eHDbZXvdL2qxHWrn16tl5lZNxTaWzMi7o6IxyLiceBLJJcwG60BZmWWt03XmZmZmfW8QpMzSVtlFt8ArGxS7OfATpKeJ2lj4FBgSRHxmZmZmZWta5c1JZ0DDAMzJa0GjgeGJe1OcllzFXBUWnZr4MsRMTcixiQdA1wMbAAsiojruxWnmZmZWZV0LTmLiMOarD6zRdk7gbmZ5YuApzxmw8zMzKzXeYQAMzMzswpxcmZmZmZWIU7OzMzMzCrEyZmZmZlZhTg5MzMzM6sQJ2dmZgWQtEjSOkkrM+tOkLRG0vJ0mru+fZhZf3ByZmZWjMXAnCbrT4uI3dPJjxAyMydnZmZFiIhlwH1lx2Fm1Vf0wOdmZvZkx0h6O3AVsCAi7m9WSNJ8YD7AwMAAIyMjxUXYxILZY03XD2zSelseZddrdHS09BimwvGXrxN1cHJmZlaeLwAnkQxpdxJwKvDOZgUjYiGwEGBoaCiGh4cLCrG5ecctbbp+wewxTl0x+f9aVh0+POnXdsLIyAhlv7dT4fjL14k6+LKmmVlJIuLuiHgsIh4HvgTsVXZMZlY+J2dmZiWRtFVm8Q3AylZlzax/dO2ypqRFwGuBdRGxW7ruP4DXAX8EbgXeEREPNHntKuBh4DFgLCKGuhWnmVkRJJ0DDAMzJa0GjgeGJe1OcllzFXBUaQGaWWV0856zxcDpwFcy6y4BPhIRY5I+CXwE+HCL178yIu7pYnxmZoWJiMOarD6z8EDMrPK6dlmzWbfxiPh+RIx347kc2LZbxzczMzOrozJ7a74TOLfFtgC+LymAL6a9lJqaavfyTnfbnUoX8vUpu15V4rrVT6/Wy8ysG0pJziR9DBgDzm5RZN+IWCPpOcAlkm5Kz8Q9xVS7l3e6226r7uVT1W738l7ojtyK61Y/vVovM7NuKLy3pqR5JB0FDo+IaFYmItakf9cB5+Pu5WZmZtYnCk3OJM0BjgUOiohHW5SZJmnG+DxwAO5ebmZmZn2ia8lZ2m38Z8DOklZLOpKk9+YMkkuVyyWdkZbdWtL4gL8DwGWSrgOuBJZGxPe6FaeZmZlZlXTtnrN2uo1HxJ3A3HT+NuBF3YrLzMzMrMomPHMm6U2Zy4wfl3SepD27H5qZmZlZ/8lzWfOfIuJhSfsC+5Oc/fpCd8MyMzMz6095krPH0r8HAgsjYimwcfdCMjMzM+tfeZKzNZK+CLwFuEjS03O+zszMzMzalCfJejNwMfDqdJDyLYAPdTUqMzMzsz41YXKWPo9sHbBvumoMuLmbQZmZmZn1qzy9NY8HPgx8JF21EfA/3QzKzMzMrF/luaz5BuAg4BH48zPJZnQzKDMzM7N+lSc5+2M6BmbAn4dUMjMzM7MuyJOcfSPtrbmZpHcDPwC+1N2wzMzMzPrThMM3RcSnJL0KeAjYGfhERFzS9cjMzMzM+lCusTXTZMwJmZmZmVmXtbysKelhSQ9l/j6UXc6zc0mLJK2TtDKzbgtJl0i6Of27eYvXHpGWuVnSEe1XzczMzKx+WiZnETEjIp6V+fus7HLO/S8G5jSsOw74YUTsBPwwXX4SSVsAxwN7A3sBx7dK4szMzMx6SZ7nnG3XbMqz84hYBtzXsPpg4Kx0/izg9U1e+mrgkoi4LyLuJ7mk2pjkmZmZmfWcPPecLc3MPwN4HvBLYNdJHnMgItam83cBA03KbAPckVlena57CknzgfkAAwMDjIyMtBXM6Oho269ZnwWzxzq2r6yy61Ulrlv99Gq9zMy6IU9vzdnZZUl7Au/txMEjIiTFFPexEFgIMDQ0FMPDw229fmRkhHZfsz7zjls6caFJWHX4cFvlO12vKnHd6qdX62Vm1g15nnP2JBFxDcm9YJN1t6StANK/65qUWQPMyixvm64zMzMz62kTnjmT9I+ZxacBewJ3TuGYS4AjgFPSv99uUuZi4F8znQAO4ImxPc3MzMx6Vp4zZzMy09NJ7kE7OM/OJZ0D/AzYWdJqSUeSJGWvknQzsH+6jKQhSV8GiIj7gJOAn6fTiek6MzMzs56W556zf57sziPisBab9mtS9irgXZnlRcCiyR7bzMzMrI7yPErjEkmbZZY3l3Rxd8MyM+stU3kot5n1lzyXNbeMiAfGF9Lnjj2neyGZmfWkxUziodxm1n/yJGePZR86K2l7YEqPvzAz6zdTeCi3mfWZPA+h/RhwmaT/AwS8jPShr2ZmNiV5HsptZn0mT4eA76UPnt0nXfWBiLinu2GZmfWXiR7KPdXRUDqt1WgoA5tMbaSUsutV99EsHH/5OlGHPM85E8l9EjtExInp2Jp7RcSVUzqymZndLWmriFi7nodyA1MfDaXTWo2GsmD2GKeuyHNRprl2R0PptLqPZuH4y9eJOuS55+zzwEuA8cdiPAx8bkpHNTMzeOKh3ND6odxm1mfyJGd7R8T7gN/Dn3trbtzVqMzMekw7D+U2s/6W59zznyRtQNpDU9KWwONdjcrMrMe081BuM+tvec6cfRY4H3iOpH8BLgP+tatRmZmZmfWpPL01z5Z0NcmvOwGvj4gbux6ZmZmZWR9qmZxJ2iKzuA44J7vNA5GbTWywRY+2VhbMHmvZCy5r1SkHTjYkMzOruPWdObua5D4zNdkWwA6TOaCknYFzM6t2AD4REZ/JlBkm6bX063TVeRFx4mSOZ2ZmZlYnLZOziHheNw4YEb8EdgdIOxqsIbmnrdGPI+K13YjBzMzMrKpyPSlQ0kHAy9PFkYi4sEPH3w+4NSJu79D+zMzMzGotzwgBpwAvBs5OV71f0l9HxEc7cPxDydzL1uAlkq4D7gQ+GBHXt4hvSkOadHqoiKkMW7I+ZderSupUt3a/D3mHvqlL/cfV6TMzMytbnjNnc4HdI+JxAElnAdcCU0rOJG0MHAR8pMnma4DtI2JU0lzgAmCnZvuZ6pAmnR4qIs/N3JPR7pAmvTAERit1qlu734e8Q9+UPcRNu+r0mZmZlS3Pc84ANsvMb9qhY78GuCYi7m7cEBEPRcRoOn8RsJGkmR06rpmZmVll5Tlz9m/AtZIuJem5+XLguA4c+zBaXNKU9Fzg7ogISXuRJJH3duCYZmZmZpWW5yG050gaIbnvDODDEXHXVA4qaRrwKuCozLr3pMc7AzgEOFrSGPA74NCIiKkc08ysH7X7rD0zK1+u3prAlpnyfy2JiDhvsgeNiEeAZzesOyMzfzpw+mT3b2ZmZlZXeXprLgL+ErieJwY8D2DSyZmZmZmZNZfnzNk+EbFL1yMxMzMzs1y9NX8mycmZmZmZWQHynDn7CkmCdhfwB5IemxERf9nVyMzMzMz6UJ7k7EzgbcAKnrjnzMzMzMy6IE9y9tuIWNL1SMzMzMwsV3J2raSvAd8huawJMKVHaZiZmZlZc3mSs01IkrIDMuv8KA2zEtXtwaKL50wrOwQzs9rIM0LAO4oIxMzMzMzyD3xuZmZmZgVwcmZmZmZWIU7OzMzMzCpkwuRM0scz80/v1IElrZK0QtJySVc12S5Jn5V0i6RfSNqzU8c2MzMzq6qWHQIkfRhYBhwCnJyu/hnQySTplRFxT4ttrwF2Sqe9gS+kf83MrEd1qyfyqlMO7Mp+LdGpz23B7DHmZfbVr5/b+s6c3QS8CdhB0o8lfQl4tqSdiwmNg4GvROJyYDNJWxV0bDMzM7NSrC85ewD4KHALMAz8Z7r+OEk/7cCxA/i+pKslzW+yfRvgjszy6nSdmZmZWc9a33POXg18Ang+8GngF8AjHXzu2b4RsUbSc4BLJN0UEcva3Uma2M0HGBgYYGRkpK3Xj46Otv2a9Vkwe6xj+8oqu15VUqe6tft9GNike9+hMtXpMzMzK1vL5CwiPgog6TrgqyT3mm0p6TLg/oh43VQOHBFr0r/rJJ0P7EVyj9u4NcCszPK26brG/SwEFgIMDQ3F8PBwW3GMjIzQ7mvWZ1637pc4fLit8p2uV5XUqW7tfh8WzB7j1BV5Bu6ol8VzptXmMyuDpFXAw8BjwFhEDJUbkZmVKc+jNC6OiKvSJGh1ROwLTOnsmaRpkmaMz5MMDbWyodgS4O1pr819gAcjYu1UjmtmVmGvjIjdnZiZWZ7hm47NLM5L17XqYZnXAHC+pPEYvhYR35P0nnT/ZwAXAXNJ7nl7lCkmhGZmZmZ10Nb1k4i4rhMHjYjbgBc1WX9GZj6A93XieGZmFTfeQSqAL6ZXKp5ksvfXFn0PY1Xvm8z7flXl/sgVax6c1OsGNoH/OvvbLbfP3mbTyYa0Xp36zBu/P1X4LNrVie9Q793cYmZWPxN2kJrs/bXdug+2lareN5n3vt2q3NM62c9tove/3fuX8+rU96wx/m7F202d+A55+CYzs5JlO0gB4x2kzKxPOTkzMytRzg5SZtZHqnfuuSDjQ000DhVhZlawph2kyg3JzMrUt8mZmVkVtOogZWb9y5c1zczMzCrEyZmZmZlZhTg5MzMzM6sQJ2dmZmZmFeLkzMzMzKxCnJyZmZmZVYgfpdHnBmv2jLdVpxxYdghmZmZdVfiZM0mzJF0q6QZJ10t6f5Myw5IelLQ8nT5RdJxmZmZmZSjjzNkYsCAirkmHLLla0iURcUNDuR9HxGtLiM/MzMysNIWfOYuItRFxTTr/MHAjsE3RcZiZmZlVUakdAiQNAnsAVzTZ/BJJ10n6rqRdCw3MzMzMrCSldQiQNB34FvCBiHioYfM1wPYRMSppLnABsFOL/cwH5gMMDAwwMjKS6/gLZo8BMLDJE/NVlrde40ZHR3O9pg51zxoZGcldtypo9/2ty/exXXX6zMzMylZKciZpI5LE7OyIOK9xezZZi4iLJH1e0syIuKdJ2YXAQoChoaEYHh7OFcO8tJfigtljnLqi+p1WVx0+3Fb5kZER8rwX8+rWW/Pw4dx1q4J239+6fB/btXjOtNp8ZmZmZSujt6aAM4EbI+LTLco8Ny2HpL1I4ry3uCjNzMzMylHGT/SXAm8DVkhanq77KLAdQEScARwCHC1pDPgdcGhERAmxmpmZmRWq8OQsIi4DNEGZ04HTi4nIzMzMrDo8fJOZmZlZhfTencdmZmbWVN2G7OtXPnNmZmZmViFOzszMzMwqxMmZmZmZWYU4OTMzMzOrECdnZmZmZhXi3po10W4PmwWzx2o3NFMeg8ct7dm6mZmZgZMzMzPrA3l/4PrHX7XU8dEfi+dMm/I+fFnTzMzMrEKcnJmZmZlViJMzMzMzswopJTmTNEfSLyXdIum4JtufLuncdPsVkgaLj9LMrBgTtYlm1l8KT84kbQB8DngNsAtwmKRdGoodCdwfETsCpwGfLDZKM7Ni5GwTzayPlHHmbC/gloi4LSL+CHwdOLihzMHAWen8/wL7SVKBMZqZFSVPm2hmfaSM5Gwb4I7M8up0XdMyETEGPAg8u5DozMyKladNNLM+UvvnnEmaD8xPF0cl/bKd1/89zATu6XhgJevVeoHrVkev/GRb9dq+m7HU1VTbuqLU/Tvs+MtV9/ihM+1dGcnZGmBWZnnbdF2zMqslbQhsCtzbbGcRsRBYONlgJF0VEUOTfX1V9Wq9wHWro16tV4fkaROn3NYVpe6fteMvV93jh87UoYzLmj8HdpL0PEkbA4cCSxrKLAGOSOcPAX4UEVFgjGZmRcnTJppZHyn8zFlEjEk6BrgY2ABYFBHXSzoRuCoilgBnAl+VdAtwH0ljZWbWc1q1iSWHZWYlKuWes4i4CLioYd0nMvO/B95UUDiVv0wwSb1aL3Dd6qhX69URzdrEGqv7Z+34y1X3+KEDdZCvFpqZmZlVh4dvMjMzM6uQvkjOcgwX9Y+SbpD0C0k/lFSbrvx5h32R9LeSQlJtesHkqZukN6ef3fWSvlZ0jJOR4/u4naRLJV2bfifnlhFnuyQtkrRO0soW2yXps2m9fyFpz6JjtM7ohTa17m1n3dvHureDXW/vIqKnJ5IbbG8FdgA2Bq4Ddmko80rgmen80cC5Zcfdqbql5WYAy4DLgaGy4+7g57YTcC2webr8nLLj7lC9FgJHp/O7AKvKjjtn3V4O7AmsbLF9LvBdQMA+wBVlx+xpUp9z7dvUureddW8fe6Ed7HZ71w9nziYcGiUiLo2IR9PFy0meM1QHeYd9OYlkfNLfFxncFOWp27uBz0XE/QARsa7gGCcjT70CeFY6vylwZ4HxTVpELCPpXd3KwcBXInE5sJmkrYqJzjqoF9rUureddW8fa98Odru964fkrN2hUY4kyXbrYMK6padSZ0XE0iID64A8n9sLgBdI+omkyyXNKSy6yctTrxOAt0paTdKD7++KCa3rPExRb+iFNrXubWfd28d+aAen1N7VfvimTpL0VmAIeEXZsXSCpKcBnwbmlRxKt2xIcup+mOSX+TJJsyPigVKjmrrDgMURcaqkl5A882+3iHi87MDM2lHXNrVH2s66t4993Q72w5mzXEOjSNof+BhwUET8oaDYpmqius0AdgNGJK0iue69pGo3traQ53NbDSyJiD9FxK+BX5E0RlWWp15HAt8AiIifAc8gGW+u7nL9W7TK64U2te5tZ93bx35oB6fU3vVDcjbh0CiS9gC+SNKIVOm6/ETWW7eIeDAiZkbEYEQMktz7cVBEXFVOuG3JM6TNBSS/CpE0k+Q0/m1FBjkJeer1G2A/AEkvJGmUfltolN2xBHh72otpH+DBiFhbdlDWtl5oU+vedta9feyHdnBK7V3PX9aMfMNF/QcwHfimJIDfRMRBpQWdU8661VLOul0MHCDpBuAx4EMRcW95UU8sZ70WAF+S9A8kN8XOi7T7T5VJOofkP4OZ6X0ixwMbAUTEGST3jcwFbgEeBd5RTqQ2Fb3Qpta97ax7+9gL7WC32zuPEGBmZmZWIf1wWdPMzMysNpycmZmZmVWIkzMzMzOzCnFyZmZmZlYhTs7MzMzMKsTJmeUm6cuSdmmj/JCkz6bz8ySd3ubxsq8flvTX7UXcHkknSPpgN49hZmY2kZ5/zpl1TkS8q83yVwGTemijpA0bXj8MjAI/ncz+zMzM6sJnzuwpJE2TtFTSdZJWSnpLun5kfPgSSaOS/kPS9ZJ+IGmvdPttkg5KywxLurDJ/l8n6QpJ16avHUjXnyDpq5J+QjKO2rCkCyUNAu8B/kHSckkvk/RrSRulr3tWdjldt6mk29Mx8sbrdIekjSS9W9LP0/p9S9Izm8SYretMJUO4IGmDtN4/l/QLSUd17p03MzNzcmbNzQHujIgXRcRuwPealJkG/CgidgUeBk4GXgW8AThxgv1fBuwTEXsAXweOzWzbBdg/Ig4bXxERq4AzgNMiYveI+DEwAhyYFjkUOC8i/pR5zYPAcp4YcPm1wMVpmfMi4sUR8SLgRpIx3PI6kmQYjhcDLwbeLel5bbzezMxsvZycWTMrgFdJ+qSkl6WJTqM/8kTStgL4vzTxWQEMTrD/bYGLJa0APgTsmtm2JCJ+lyPGL/PEcBjvAP67SZlzgbek84emywC7SfpxevzDG44/kQNIxktbDlwBPJvqDCZsZmY9wMmZPUVE/ArYkyTROlnSJ5oU+1NmnLPHgT+kr32cie9l/C/g9IiYDRxFMqDtuEdyxvgTYFDSMLBBRKxsUmwJMEfSFsBfAT9K1y8GjkmP/88Nxx83xhP/PrLbBfxdegZv94h4XkR8P0/MZmZmeTg5s6eQtDXwaET8D8kAxnt2+BCbAmvS+SNyvuZhYEbDuq8AX6P5WTMiYhT4OfCfwIUR8Vi6aQawNr1H7fAWx1tFktABHJJZfzFwdOZ+txdImpazDmZmZhNycmbNzAauTC/dHU9yP1knnQB8U9LVwD05X/Md4A3jHQLSdWcDmwPnrOd15wJv5YlLmgD/RHJJ8ifATS1e9ymSJOxaYGZm/ZeBG4BrJK0Evoh7PZuZWQfpiStTZvUi6RDg4Ih4W9mxmJmZdYp/8VstSfov4DXA3LJjMTMz6ySfOTMzMzOrEN9zZmZmZlYhTs7MzMzMKsTJmZmZmVmFODkzMzMzqxAnZ2ZmZmYV4uTMzMzMrEL+PwWFITwo/0CRAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axes = plt.subplots(figsize=(12, 6), nrows=1, ncols=2)\n",
        "\n",
        "molecule_dataset.plot(\"tanimoto_maccs\", \"dice_maccs\", kind=\"scatter\", ax=axes[0])\n",
        "axes[0].plot([0, 1], [0, 1], \"k--\")\n",
        "axes[0].set_xlabel(\"Tanimoto (MACCS)\")\n",
        "axes[0].set_ylabel(\"Dice (MACCS)\")\n",
        "\n",
        "molecule_dataset.plot(\"tanimoto_morgan\", \"dice_morgan\", kind=\"scatter\", ax=axes[1])\n",
        "axes[1].plot([0, 1], [0, 1], \"k--\")\n",
        "axes[1].set_xlabel(\"Tanimoto (Morgan)\")\n",
        "axes[1].set_ylabel(\"Dice (Morgan)\")\n",
        "\n",
        "fig;"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "id": "FMB6Qty1-pbn",
        "outputId": "a89635a2-5a28-441f-d586-11115a1cc86b"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "molecule_dataset.sort_values([\"tanimoto_morgan\"], ascending=False).head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 767
        },
        "id": "4UzFAWc6-ykA",
        "outputId": "7cc8f596-bcd6-4482-90d4-3a69b7034df5"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   molecule_chembl_id                                             smiles  \\\n",
              "0        CHEMBL336546  O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...   \n",
              "25       CHEMBL131976  NC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F)(...   \n",
              "2        CHEMBL134490  CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...   \n",
              "\n",
              "       pIC50                                              ROMol  \\\n",
              "0   7.301030  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "25  5.301030  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "2   6.552842  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "\n",
              "    tanimoto_maccs  tanimoto_morgan  dice_maccs  dice_morgan  \n",
              "0         1.000000         1.000000    1.000000     1.000000  \n",
              "25        0.894737         0.714286    0.944444     0.833333  \n",
              "2         0.755556         0.666667    0.860759     0.800000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fe6a74dd-df65-4a56-9b84-c43f2038c967\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        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",
              "      <th>ROMol</th>\n",
              "      <th>tanimoto_maccs</th>\n",
              "      <th>tanimoto_morgan</th>\n",
              "      <th>dice_maccs</th>\n",
              "      <th>dice_morgan</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL336546</td>\n",
              "      <td>O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...</td>\n",
              "      <td>7.301030</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" 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\" alt=\"Mol\"/></td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>CHEMBL131976</td>\n",
              "      <td>NC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F)(...</td>\n",
              "      <td>5.301030</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>0.894737</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>0.944444</td>\n",
              "      <td>0.833333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL134490</td>\n",
              "      <td>CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...</td>\n",
              "      <td>6.552842</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>0.755556</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.860759</td>\n",
              "      <td>0.800000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fe6a74dd-df65-4a56-9b84-c43f2038c967')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </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",
              "      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-fe6a74dd-df65-4a56-9b84-c43f2038c967 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-fe6a74dd-df65-4a56-9b84-c43f2038c967');\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": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_n_molecules = 10\n",
        "top_molecules = molecule_dataset.sort_values([\"tanimoto_morgan\"], ascending=False).reset_index()\n",
        "top_molecules = top_molecules[:top_n_molecules]\n",
        "legends = [\n",
        "    f\"#{index+1} {molecule['molecule_chembl_id']}, pIC50={molecule['pIC50']:.2f}\"\n",
        "    for index, molecule in top_molecules.iterrows()\n",
        "]\n",
        "Chem.Draw.MolsToGridImage(\n",
        "    mols=[query] + top_molecules[\"ROMol\"].tolist(),\n",
        "    legends=([\"Gefitinib\"] + legends),\n",
        "    molsPerRow=3,\n",
        "    subImgSize=(450, 150),\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 440
        },
        "id": "BgcxSuAj-6gv",
        "outputId": "f5eb38ff-82a6-4d7f-97cc-a8317c0b0818"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1350x600 at 0x7FDBDF22ABD0>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "molecule_dataset.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 767
        },
        "id": "u0tFvI4Y_Msf",
        "outputId": "becd363a-9657-4fe1-b307-8eb6020bdc49"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  molecule_chembl_id                                             smiles  \\\n",
              "0       CHEMBL336546  O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...   \n",
              "1       CHEMBL131636  CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...   \n",
              "2       CHEMBL134490  CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...   \n",
              "\n",
              "      pIC50                                              ROMol  \\\n",
              "0  7.301030  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "1  6.769551  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "2  6.552842  <img data-content=\"rdkit/molecule\" src=\"data:i...   \n",
              "\n",
              "   tanimoto_maccs  tanimoto_morgan  dice_maccs  dice_morgan  \n",
              "0        1.000000         1.000000    1.000000     1.000000  \n",
              "1        0.680000         0.625000    0.809524     0.769231  \n",
              "2        0.755556         0.666667    0.860759     0.800000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7701b7af-bace-4f0d-8db3-6067c8eb7f9f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        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",
              "      <th>ROMol</th>\n",
              "      <th>tanimoto_maccs</th>\n",
              "      <th>tanimoto_morgan</th>\n",
              "      <th>dice_maccs</th>\n",
              "      <th>dice_morgan</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL336546</td>\n",
              "      <td>O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cnc(Cl)nc1...</td>\n",
              "      <td>7.301030</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL131636</td>\n",
              "      <td>CCCCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C...</td>\n",
              "      <td>6.769551</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>0.680000</td>\n",
              "      <td>0.625000</td>\n",
              "      <td>0.809524</td>\n",
              "      <td>0.769231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL134490</td>\n",
              "      <td>CCOC(=O)c1cc(NC(=O)c2cnc(Cl)nc2C(F)(F)F)cc(C(F...</td>\n",
              "      <td>6.552842</td>\n",
              "      <td style=\"text-align: center;\"><img data-content=\"rdkit/molecule\" src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
              "      <td>0.755556</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.860759</td>\n",
              "      <td>0.800000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7701b7af-bace-4f0d-8db3-6067c8eb7f9f')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </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",
              "      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-7701b7af-bace-4f0d-8db3-6067c8eb7f9f 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-7701b7af-bace-4f0d-8db3-6067c8eb7f9f');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def get_enrichment_data(molecules, similarity_measure, pic50_cutoff):\n",
        "    \"\"\"\n",
        "    Calculates x and y values for enrichment plot:\n",
        "        x - % ranked dataset\n",
        "        y - % true actives identified\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    molecules : pandas.DataFrame\n",
        "        Molecules with similarity values to a query molecule.\n",
        "    similarity_measure : str\n",
        "        Column name which will be used to sort the DataFrame．\n",
        "    pic50_cutoff : float\n",
        "        pIC50 cutoff value used to discriminate active and inactive molecules.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    pandas.DataFrame\n",
        "        Enrichment data: Percentage of ranked dataset by similarity vs. percentage of identified true actives.\n",
        "    \"\"\"\n",
        "\n",
        "    # Get number of molecules in data set\n",
        "    molecules_all = len(molecules)\n",
        "\n",
        "    # Get number of active molecules in data set\n",
        "    actives_all = sum(molecules[\"pIC50\"] >= pic50_cutoff)\n",
        "\n",
        "    # Initialize a list that will hold the counter for actives and molecules while iterating through our dataset\n",
        "    actives_counter_list = []\n",
        "\n",
        "    # Initialize counter for actives\n",
        "    actives_counter = 0\n",
        "\n",
        "    # Note: Data must be ranked for enrichment plots:\n",
        "    # Sort molecules by selected similarity measure\n",
        "    molecules.sort_values([similarity_measure], ascending=False, inplace=True)\n",
        "\n",
        "    # Iterate over the ranked dataset and check each molecule if active (by checking bioactivity)\n",
        "    for value in molecules[\"pIC50\"]:\n",
        "        if value >= pic50_cutoff:\n",
        "            actives_counter += 1\n",
        "        actives_counter_list.append(actives_counter)\n",
        "\n",
        "    # Transform number of molecules into % ranked dataset\n",
        "    molecules_percentage_list = [i / molecules_all for i in range(1, molecules_all + 1)]\n",
        "\n",
        "    # Transform number of actives into % true actives identified\n",
        "    actives_percentage_list = [i / actives_all for i in actives_counter_list]\n",
        "\n",
        "    # Generate DataFrame with x and y values as well as label\n",
        "    enrichment = pd.DataFrame(\n",
        "        {\n",
        "            \"% ranked dataset\": molecules_percentage_list,\n",
        "            \"% true actives identified\": actives_percentage_list,\n",
        "        }\n",
        "    )\n",
        "\n",
        "    return enrichment"
      ],
      "metadata": {
        "id": "GupUIRiM_Pin"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pic50_cutoff = 6.3"
      ],
      "metadata": {
        "id": "KdgWp1l8_T4L"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "similarity_measures = [\"tanimoto_maccs\", \"tanimoto_morgan\"]\n",
        "enrichment_data = {\n",
        "    similarity_measure: get_enrichment_data(molecule_dataset, similarity_measure, pic50_cutoff)\n",
        "    for similarity_measure in similarity_measures\n",
        "}"
      ],
      "metadata": {
        "id": "mEKlMs7q_XG_"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# NBVAL_CHECK_OUTPUT\n",
        "enrichment_data[\"tanimoto_maccs\"].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "58Jqhzk__ZHX",
        "outputId": "b1d39d15-6788-498d-9536-8b6983fd1748"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   % ranked dataset  % true actives identified\n",
              "0          0.020408                        0.2\n",
              "1          0.040816                        0.4\n",
              "2          0.061224                        0.6\n",
              "3          0.081633                        0.6\n",
              "4          0.102041                        0.6"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>% ranked dataset</th>\n",
              "      <th>% true actives identified</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.020408</td>\n",
              "      <td>0.2</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.040816</td>\n",
              "      <td>0.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.061224</td>\n",
              "      <td>0.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.081633</td>\n",
              "      <td>0.6</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.102041</td>\n",
              "      <td>0.6</td>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "                                                     [key], {});\n",
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            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(figsize=(6, 6))\n",
        "\n",
        "fontsize = 20\n",
        "\n",
        "# Plot enrichment data\n",
        "for similarity_measure, enrichment in enrichment_data.items():\n",
        "    ax = enrichment.plot(\n",
        "        ax=ax,\n",
        "        x=\"% ranked dataset\",\n",
        "        y=\"% true actives identified\",\n",
        "        label=similarity_measure,\n",
        "        alpha=0.5,\n",
        "        linewidth=4,\n",
        "    )\n",
        "ax.set_ylabel(\"% True actives identified\", size=fontsize)\n",
        "ax.set_xlabel(\"% Ranked dataset\", size=fontsize)\n",
        "\n",
        "# Plot optimal curve: Ratio of actives in dataset\n",
        "ratio_actives = sum(molecule_dataset[\"pIC50\"] >= pic50_cutoff) / len(molecule_dataset)\n",
        "ax.plot(\n",
        "    [0, ratio_actives, 1],\n",
        "    [0, 1, 1],\n",
        "    label=\"Optimal curve\",\n",
        "    color=\"black\",\n",
        "    linestyle=\"--\",\n",
        ")\n",
        "\n",
        "# Plot random curve\n",
        "ax.plot([0, 1], [0, 1], label=\"Random curve\", color=\"grey\", linestyle=\"--\")\n",
        "\n",
        "plt.tick_params(labelsize=16)\n",
        "plt.legend(\n",
        "    labels=[\"MACCS\", \"Morgan\", \"Optimal\", \"Random\"],\n",
        "    loc=(0.5, 0.08),\n",
        "    fontsize=fontsize,\n",
        "    labelspacing=0.3,\n",
        ")\n",
        "\n",
        "# Save plot -- use bbox_inches to include text boxes\n",
        "plt.savefig(\n",
        "    \"enrichment_plot.png\",\n",
        "    dpi=300,\n",
        "    bbox_inches=\"tight\",\n",
        "    transparent=True,\n",
        ")\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "8is59ZNb_ctY",
        "outputId": "045e17fe-bcad-43c4-9a9d-3632f740b275"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def calculate_enrichment_factor(enrichment, ranked_dataset_percentage_cutoff):\n",
        "    \"\"\"\n",
        "    Get the experimental enrichment factor for a given percentage of the ranked dataset.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    enrichment : pd.DataFrame\n",
        "        Enrichment data: Percentage of ranked dataset by similarity vs. percentage of\n",
        "        identified true actives.\n",
        "    ranked_dataset_percentage_cutoff : float or int\n",
        "        Percentage of ranked dataset to be included in enrichment factor calculation.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    float\n",
        "        Experimental enrichment factor.\n",
        "    \"\"\"\n",
        "\n",
        "    # Keep only molecules that meet the cutoff\n",
        "    enrichment = enrichment[\n",
        "        enrichment[\"% ranked dataset\"] <= ranked_dataset_percentage_cutoff / 100\n",
        "    ]\n",
        "    # Get highest percentage of actives and the corresponding percentage of actives\n",
        "    highest_enrichment = enrichment.iloc[-1]\n",
        "    enrichment_factor = round(100 * float(highest_enrichment[\"% true actives identified\"]), 1)\n",
        "    return enrichment_factor"
      ],
      "metadata": {
        "id": "XUWbwjU7_uBR"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def calculate_enrichment_factor_random(ranked_dataset_percentage_cutoff):\n",
        "    \"\"\"\n",
        "    Get the random enrichment factor for a given percentage of the ranked dataset.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    ranked_dataset_percentage_cutoff : float or int\n",
        "        Percentage of ranked dataset to be included in enrichment factor calculation.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    float\n",
        "        Random enrichment factor.\n",
        "    \"\"\"\n",
        "\n",
        "    enrichment_factor_random = round(float(ranked_dataset_percentage_cutoff), 1)\n",
        "    return enrichment_factor_random"
      ],
      "metadata": {
        "id": "wbjqjFRr_wqT"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def calculate_enrichment_factor_optimal(molecules, ranked_dataset_percentage_cutoff, pic50_cutoff):\n",
        "    \"\"\"\n",
        "    Get the optimal random enrichment factor for a given percentage of the ranked dataset.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    molecules : pandas.DataFrame\n",
        "        the DataFrame with all the molecules and pIC50.\n",
        "    ranked_dataset_percentage_cutoff : float or int\n",
        "        Percentage of ranked dataset to be included in enrichment factor calculation.\n",
        "    activity_cutoff: float\n",
        "        pIC50 cutoff value used to discriminate active and inactive molecules\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    float\n",
        "        Optimal enrichment factor.\n",
        "    \"\"\"\n",
        "\n",
        "    ratio = sum(molecules[\"pIC50\"] >= pic50_cutoff) / len(molecules) * 100\n",
        "    if ranked_dataset_percentage_cutoff <= ratio:\n",
        "        enrichment_factor_optimal = round(100 / ratio * ranked_dataset_percentage_cutoff, 1)\n",
        "    else:\n",
        "        enrichment_factor_optimal = 100.0\n",
        "    return enrichment_factor_optimal"
      ],
      "metadata": {
        "id": "2m4I2IHo_0pj"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ranked_dataset_percentage_cutoff = 5"
      ],
      "metadata": {
        "id": "WbAfjid7_4MA"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for similarity_measure, enrichment in enrichment_data.items():\n",
        "    enrichment_factor = calculate_enrichment_factor(enrichment, ranked_dataset_percentage_cutoff)\n",
        "    print(\n",
        "        f\"Experimental EF for {ranked_dataset_percentage_cutoff}% of ranked dataset ({similarity_measure}): {enrichment_factor}%\"\n",
        "    )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "osJhc5pK_5zv",
        "outputId": "251b5f74-9e9a-4fc4-d439-f1edb44c84d3"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Experimental EF for 5% of ranked dataset (tanimoto_maccs): 40.0%\n",
            "Experimental EF for 5% of ranked dataset (tanimoto_morgan): 20.0%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "enrichment_factor_random = calculate_enrichment_factor_random(ranked_dataset_percentage_cutoff)\n",
        "print(\n",
        "    f\"Random EF for {ranked_dataset_percentage_cutoff}% of ranked dataset: {enrichment_factor_random}%\"\n",
        ")\n",
        "enrichment_factor_optimal = calculate_enrichment_factor_optimal(\n",
        "    molecule_dataset, ranked_dataset_percentage_cutoff, pic50_cutoff\n",
        ")\n",
        "print(\n",
        "    f\"Optimal EF for {ranked_dataset_percentage_cutoff}% of ranked dataset: {enrichment_factor_optimal}%\"\n",
        ")\n",
        "# NBVAL_CHECK_OUTPUT"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dY2atRHUACoz",
        "outputId": "e9ba37b8-7b2c-4c5e-db54-769e182c5ff4"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Random EF for 5% of ranked dataset: 5.0%\n",
            "Optimal EF for 5% of ranked dataset: 49.0%\n"
          ]
        }
      ]
    }
  ]
}