prep_ligand_for_gmx_cphmd.ipynb

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        "<a href=\"https://colab.research.google.com/github/pbuslaev/cphmd_ligand_param/blob/main/prep_ligand_for_gmx_cphmd.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "### This notebook has to be run on Google colab"
      ]
    },
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      "source": [
        "#Preparing ligands for GROMACS constnat pH simulations.\n",
        "\n",
        "This notebook will help you to prepare input files for [phbuilder](https://gitlab.com/gromacs-constantph/phbuilder) for an ionizable ligand. The workflow below is interactive and allows the user to make important decisions about how the ligand is treated in constant pH simulations. In brief, the workflow has several important steps:\n",
        "- Generate protonation states and ask which states to use\n",
        "- Determine the symmetrical states and ask whether to use them or not\n",
        "- Define the microscopic transitions and ask for p$K_{\\text{a}}$ values for each transition\n",
        "- Assign parameters for each $\\lambda$-coordinate to be used\n",
        "- Assign charges and prepare input `lambdagrouptypes.dat` file for phbuilder\n",
        "\n",
        "We will describe each step in more details later on.\n",
        "\n",
        "To execute the whole workflow, run each cell one after antother and provide the input, when needed. The workflow is quite interactive and should be straightforward to follow. If you encounter any kind of problem or unexpected/wrong behaviour, please raise an issue on the [phbuilder gitlab page](https://gitlab.com/gromacs-constantph/phbuilder). Please, provide all possible details (SMILES used, error raised, input selected, expected outcome, obtained outcome, error message, if one raised, etc) when discribing your issue. This will help us to find a solution much faster.\n",
        "\n",
        "We hope you enjoy using our preparation workflow."
      ],
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      "source": [
        "#@title Conda installation\n",
        "%%capture\n",
        "!pip install -q condacolab\n",
        "import condacolab\n",
        "condacolab.install()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Intall packages\n",
        "%%capture\n",
        "!pip install dimorphite_dl --upgrade\n",
        "!mamba install -c conda-forge rdkit sympy openff-toolkit"
      ],
      "metadata": {
        "id": "HApR6x6ptwjO",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Import packages\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import AllChem\n",
        "from rdkit.Chem import Draw\n",
        "from rdkit.Chem.Draw import rdMolDraw2D\n",
        "from rdkit.Chem.Draw import IPythonConsole\n",
        "IPythonConsole.molSize = 300,300\n",
        "from IPython.display import SVG\n",
        "from dimorphite_dl import DimorphiteDL\n",
        "\n",
        "from openff.toolkit import Molecule, Topology, ForceField\n",
        "from openff.interchange import Interchange\n",
        "\n",
        "from IPython.display import HTML, display\n",
        "\n",
        "def set_css():\n",
        "  display(HTML('''\n",
        "  <style>\n",
        "    pre {\n",
        "        white-space: pre-wrap;\n",
        "    }\n",
        "  </style>\n",
        "  '''))\n",
        "  get_ipython().events.register('pre_run_cell', set_css)"
      ],
      "metadata": {
        "id": "9F1Rak-meOlC",
        "cellView": "form"
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      "execution_count": null,
      "outputs": []
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      "cell_type": "code",
      "source": [
        "#@title Input molecule\n",
        "#@markdown Please provide molecule SMILES. We will generate its protonation\n",
        "#@markdown states. Also, specify pH range for which to create states.\n",
        "# As a two state example we will use SM-26 from SAMP7 challenge\n",
        "# (https://github.com/samplchallenges/SAMPL7/tree/master/physical_property)\n",
        "# SMILES: O=S(CCC1=CC=CC=C1)(NC(C)=O)=O\n",
        "# test 1: c1cc(N)c(N)cc1\n",
        "# test 2: c1cc(CO)cc(CO)c1\n",
        "# pKa = 4.91\n",
        "# (https://github.com/samplchallenges/SAMPL7/blob/master/physical_property/experimental_data/Experimental_Properties_of_SAMPL7_Compounds.pdf)\n",
        "smiles = \"C(CO)(CO)(CO)[C@H](N)N\" #@param {type: \"string\"}\n",
        "min_ph = -10 #@param {type: \"number\"}\n",
        "max_ph = 24 #@param {type: \"number\"}\n",
        "dimorphite_dl = DimorphiteDL(\n",
        "    min_ph=min_ph,\n",
        "    max_ph=max_ph,\n",
        "    max_variants=256,\n",
        "    label_states=False,\n",
        "    pka_precision=0.1\n",
        ")\n",
        "mols = [Chem.MolFromSmiles(mol) for mol in dimorphite_dl.protonate(smiles)]\n",
        "mols = sorted(mols, key = lambda x: Chem.GetFormalCharge(x), reverse=True)\n",
        "# Now mols[0] is the highest protonation state\n",
        "for i, m in enumerate(mols):\n",
        "    print(f\"This is Molecule {i}\")\n",
        "    d2d = rdMolDraw2D.MolDraw2DSVG(250, 200)\n",
        "    d2d.DrawMolecule(m)\n",
        "    d2d.FinishDrawing()\n",
        "    display(SVG(d2d.GetDrawingText()))"
      ],
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        "cellView": "form"
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          "name": "stdout",
          "text": [
            "This is Molecule 0\n"
          ]
        },
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            "This is Molecule 1\n"
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "This is Molecule 11\n"
          ]
        },
        {
          "output_type": "display_data",
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Select molecules\n",
        "#@markdown Which molecule states do you want to use?\n",
        "#@markdown The molecule ids are shown in the previous cell.\n",
        "mol1 = True #@param {type:\"boolean\"}\n",
        "mol2 = True #@param {type:\"boolean\"}\n",
        "mol3 = True #@param {type:\"boolean\"}\n",
        "mol4 = True #@param {type:\"boolean\"}\n",
        "mol5 = True #@param {type:\"boolean\"}\n",
        "mol6 = False #@param {type:\"boolean\"}\n",
        "mol7 = False #@param {type:\"boolean\"}\n",
        "mol8 = False #@param {type:\"boolean\"}\n",
        "mol9 = False #@param {type:\"boolean\"}\n",
        "mol10 = False #@param {type:\"boolean\"}\n",
        "\n",
        "mols_to_use = [\n",
        "    mol1, mol2, mol3, mol4, mol5, mol6, mol7, mol8, mol9, mol10, False, False\n",
        "][:len(mols)]\n",
        "\n",
        "mols_for_use = [mols[i] for i in range(len(mols)) if mols_to_use[i]]"
      ],
      "metadata": {
        "id": "6cC1ul8MS8ZO",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Selected molecules\n",
        "#@markdown The foloweing molecules will be used in the furhter analysis.\n",
        "for i, m in enumerate(mols_for_use):\n",
        "    print(f\"This is Molecule {i}\")\n",
        "    d2d = rdMolDraw2D.MolDraw2DSVG(250, 200)\n",
        "    d2d.DrawMolecule(m)\n",
        "    d2d.FinishDrawing()\n",
        "    display(SVG(d2d.GetDrawingText()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "VfSF4T0PV3XY",
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "This is Molecule 4\n"
          ]
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    {
      "cell_type": "code",
      "source": [
        "#@title Get titratable site\n",
        "# Highest protonation state is always in state[0]\n",
        "from copy import deepcopy\n",
        "\n",
        "titratable_sites = []\n",
        "# Dictionary of molecular states\n",
        "mol_states = {}\n",
        "# pmol is a protonated molecule - always in the highest available protonation\n",
        "# state\n",
        "pmol = mols[0]\n",
        "from rdkit.Chem import rdFMCS\n",
        "res = rdFMCS.FindMCS([pmol, pmol])\n",
        "similar_patt = Chem.MolFromSmarts(res.smartsString)\n",
        "# This is a constant mol[0] substructure match\n",
        "subst_matches_pmol = pmol.GetSubstructMatches(similar_patt)[0]\n",
        "mol_states[0] = [\n",
        "    {\n",
        "        \"heavy_atom_mapping\": {x: x for x in subst_matches_pmol},  # mapping to pmol heavy atoms\n",
        "        \"h_formal_charges\": {\n",
        "            x: [1] * (\n",
        "                pmol.GetAtomWithIdx(x).GetNumImplicitHs() +\n",
        "                pmol.GetAtomWithIdx(x).GetNumExplicitHs()\n",
        "            ) for x in range(pmol.GetNumAtoms())\n",
        "        },  # mapping to hydrogen formal charges in the pmol indexing\n",
        "        \"use\": True,  # Flag for using this state\n",
        "        \"mol\": deepcopy(pmol),  # molecule\n",
        "    }\n",
        "]\n",
        "for i, m in enumerate(mols[1:]):\n",
        "    subst_matches = m.GetSubstructMatches(similar_patt)[0]\n",
        "    mol_states[i + 1] = [\n",
        "        {\n",
        "            \"heavy_atom_mapping\": {\n",
        "                a: a0 for a0, a in zip(subst_matches_pmol, subst_matches)\n",
        "            },  # mapping to pmol heavy atoms\n",
        "            \"h_formal_charges\": {\n",
        "                x: [1] * (\n",
        "                    pmol.GetAtomWithIdx(x).GetNumImplicitHs() +\n",
        "                    pmol.GetAtomWithIdx(x).GetNumExplicitHs()\n",
        "                ) for x in range(pmol.GetNumAtoms())\n",
        "            },  # mapping to hydrogen formal charges in the pmol indexing\n",
        "            \"use\": True,  # Flag for using this state\n",
        "            \"mol\": deepcopy(m),  # molecule\n",
        "        }\n",
        "    ]\n",
        "    for a0, a in zip(subst_matches_pmol, subst_matches):\n",
        "        if (pmol.GetAtomWithIdx(a0).GetFormalCharge() !=\n",
        "            m.GetAtomWithIdx(a).GetFormalCharge()\n",
        "        ):\n",
        "            titratable_sites.append(a0)\n",
        "        _n_pmol_h = len(mol_states[i + 1][0][\"h_formal_charges\"][a0])\n",
        "        if (\n",
        "            m.GetAtomWithIdx(a).GetNumImplicitHs() +\n",
        "            m.GetAtomWithIdx(a).GetNumExplicitHs() !=\n",
        "            _n_pmol_h\n",
        "        ):\n",
        "            diff = (\n",
        "                _n_pmol_h -\n",
        "                m.GetAtomWithIdx(a).GetNumImplicitHs() -\n",
        "                m.GetAtomWithIdx(a).GetNumExplicitHs()\n",
        "            )\n",
        "            assert diff > 0, \"Not possible, since pmol is highest protonation state\"\n",
        "            mol_states[i + 1][0][\"h_formal_charges\"][a0] = [1] * (\n",
        "                m.GetAtomWithIdx(a).GetNumImplicitHs() +\n",
        "                m.GetAtomWithIdx(a).GetNumExplicitHs()\n",
        "            ) + [0] * diff\n",
        "\n",
        "for i in mol_states:\n",
        "    if not mols_to_use[i]:\n",
        "        mol_states[i][0][\"use\"] = False\n",
        "\n",
        "titratable_sites = list(set(titratable_sites))"
      ],
      "metadata": {
        "id": "Sl3r5d_MdQcN",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Generate symmetrical states\n",
        "from rdkit.Chem import rdFMCS\n",
        "# We search for symmetrical sites based on the highest protonation states\n",
        "# NOTE: If the user selects not to include the highest protonation state\n",
        "# this behaviour can cause problems.\n",
        "# The indexing of symmetrical sites is for pmol indexing\n",
        "res = rdFMCS.FindMCS([pmol, pmol])\n",
        "similar_patt = Chem.MolFromSmarts(res.smartsString)\n",
        "\n",
        "# We look for all possible substructure matches\n",
        "sym_subst_matches = pmol.GetSubstructMatches(similar_patt, uniquify=False)\n",
        "subst_matches = sym_subst_matches\n",
        "#print(subst_matches)\n",
        "# We create a dictionary of symmetrical sites and substructure machings\n",
        "# for each atom\n",
        "symmetrical_sites = {\n",
        "    x.GetIdx():[{\"idx\": x.GetIdx(), \"mapping\": subst_matches[0]}]\n",
        "    for x in pmol.GetAtoms()\n",
        "}\n",
        "# We save all possible mappings. Then, when generating symmetrical mol_states\n",
        "# we will only save states, if charges are not present in the charge list\n",
        "if len(subst_matches) > 1:\n",
        "    for sm in subst_matches[1:]:\n",
        "        for ts in titratable_sites:\n",
        "            symmetrical_sites[ts].append(\n",
        "                {\n",
        "                    \"idx\": sm[subst_matches_pmol.index(ts)],\n",
        "                    \"mapping\": sm,\n",
        "                }\n",
        "            )\n",
        "\n",
        "def _get_formal_charges(mol: Chem.rdchem.Mol) -> dict[int, int]:\n",
        "    \"\"\"\n",
        "    Get dictionary of formal charges for a molecule.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    mol: rdkit.Chem.rdchem.Mol\n",
        "        Rdkit Molecule.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Dictionary with atom index as key, and atom charge as value.\n",
        "    Indexing in the molecule indexing.\n",
        "    \"\"\"\n",
        "    return {x.GetIdx(): x.GetFormalCharge() for x in mol.GetAtoms()}\n",
        "\n",
        "def _reshufle_charges_to_pmol_indexing(\n",
        "    charge_dict: dict[int, int], mapping: dict[int, int]\n",
        ") -> dict[int, int]:\n",
        "    \"\"\"\n",
        "    Reassignes indices to pmol indexing\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    charge_dict: dict[int, int]\n",
        "        Dictionary of charges in arbitrary indexing system.\n",
        "    mapping: dict[int, int]\n",
        "        Mapping of indexing to pmole indexing.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Dictionary with mapped to pmol atom index as key, and atom charge as value.\n",
        "    \"\"\"\n",
        "    return {mapping[x]: charge_dict[x] for x in charge_dict}\n",
        "\n",
        "for idx, mol in enumerate(mols):\n",
        "    _tmp = mol_states[idx][0]\n",
        "    # Generate dictionary of formal charges\n",
        "    charges = _get_formal_charges(mol)\n",
        "    # Reorder charges to pmol indexing\n",
        "    charges = _reshufle_charges_to_pmol_indexing(\n",
        "        charges, _tmp[\"heavy_atom_mapping\"]\n",
        "    )\n",
        "    _charge_registry = [charges]\n",
        "    _mapping_registry = [_tmp[\"heavy_atom_mapping\"]]\n",
        "    for _match in sym_subst_matches:\n",
        "        _order_dict = {i: _match[i] for i in range(len(_match))}\n",
        "        _try_charges = _reshufle_charges_to_pmol_indexing(charges, _order_dict)\n",
        "        if any(\n",
        "            all(x[i] == _try_charges[i] for i in x) for x in _charge_registry\n",
        "        ):\n",
        "            continue\n",
        "        else:\n",
        "            _charge_registry.append(_try_charges)\n",
        "            # Inintial Mapping Reordering Final Mapping\n",
        "            # 1 - 2            1 - 3      1 - 1\n",
        "            # 2 - 1            2 - 1      1 - 3\n",
        "            # 3 - 3            3 - 2      3 - 2\n",
        "            _new_mapping = {\n",
        "                x: _order_dict[\n",
        "                    _tmp[\"heavy_atom_mapping\"][x]\n",
        "                ] for x in _tmp[\"heavy_atom_mapping\"]\n",
        "            }\n",
        "\n",
        "            def _reverse_mapping(mapping: dict[int, int]) -> dict[int, int]:\n",
        "                \"\"\"\n",
        "                Get mapping from pmol indexing to current indexing.\n",
        "\n",
        "                Parameters\n",
        "                ----------\n",
        "                mapping: dict[int, int]\n",
        "                    Direct mapping.\n",
        "\n",
        "                Returns\n",
        "                -------\n",
        "                Reverse mapping.\n",
        "                \"\"\"\n",
        "                return {mapping[x]: x for x in mapping}\n",
        "\n",
        "            _mol = deepcopy(mol_states[idx][0][\"mol\"])\n",
        "            for _original_idx in range(mol_states[idx][0][\"mol\"].GetNumAtoms()):\n",
        "                _pmol_idx = mol_states[idx][0][\"heavy_atom_mapping\"][\n",
        "                    _original_idx\n",
        "                ]\n",
        "                _mol_idx = _reverse_mapping(_new_mapping)[_pmol_idx]\n",
        "                _mol.GetAtomWithIdx(_original_idx).SetFormalCharge(\n",
        "                    mol_states[idx][0][\"mol\"].GetAtomWithIdx(\n",
        "                        _mol_idx\n",
        "                    ).GetFormalCharge()\n",
        "                )\n",
        "                _mol.GetAtomWithIdx(_original_idx).SetNumExplicitHs(\n",
        "                    mol_states[idx][0][\"mol\"].GetAtomWithIdx(\n",
        "                        _mol_idx\n",
        "                    ).GetNumImplicitHs()\n",
        "                    + mol_states[idx][0][\"mol\"].GetAtomWithIdx(\n",
        "                        _mol_idx\n",
        "                    ).GetNumExplicitHs()\n",
        "                )\n",
        "                _mol.GetAtomWithIdx(_original_idx).SetNoImplicit(True)\n",
        "\n",
        "            mol_states[idx].append(\n",
        "                {\n",
        "                    \"heavy_atom_mapping\": _new_mapping,\n",
        "                    \"h_formal_charges\": {\n",
        "                        _order_dict[x]: _tmp[\"h_formal_charges\"][x]\n",
        "                        for x in _order_dict\n",
        "                    },\n",
        "                    \"use\": False,  # Flag for using this state\n",
        "                    \"mol\": _mol,\n",
        "                }\n",
        "            )\n",
        "    #print(_charge_registry, _mapping_registry)\n",
        "    #print(\"----------\")"
      ],
      "metadata": {
        "id": "y00bjqKqSgXA",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Symmetrical states treatment\n",
        "symm_states_dict = {}\n",
        "color = (0.0, 1.0, 0.0, 0.2)\n",
        "for idx, mol in enumerate(mols):\n",
        "    if len(mol_states[idx]) == 1:\n",
        "        # Only one state was found\n",
        "        continue\n",
        "    if not mol_states[idx][0][\"use\"]:\n",
        "        # Even base molecule should not be used. All symmetrical copies should\n",
        "        # not be used as well.\n",
        "        continue\n",
        "    symm_states_dict[idx] = False\n",
        "    print(f\"For molecule {idx} symmetrical states were detected:\")\n",
        "    d2d = rdMolDraw2D.MolDraw2DSVG(250, 200)\n",
        "    d2d.DrawMolecule(mol_states[idx][0][\"mol\"])\n",
        "    d2d.FinishDrawing()\n",
        "    display(SVG(d2d.GetDrawingText()))\n",
        "    print(\"These are found symmetrical states:\")\n",
        "    _mols = [x[\"mol\"] for x in mol_states[idx]]\n",
        "    highlight_atoms = [[] for _ in range(len(_mols))]\n",
        "    highlight_colors = [{} for _ in range(len(_mols))]\n",
        "    for i in range(_mols[0].GetNumAtoms()):\n",
        "        if len(\n",
        "            set(\n",
        "                [\n",
        "                    x.GetAtomWithIdx(i).GetFormalCharge() for x in _mols\n",
        "                ]\n",
        "            )\n",
        "        ) != 1:\n",
        "            for j in range(len(_mols)):\n",
        "                highlight_atoms[j].append(i)\n",
        "                highlight_colors[j][i] = color\n",
        "    highlight_colors = tuple(x for x in highlight_colors)\n",
        "    d2d = rdMolDraw2D.MolDraw2DSVG(\n",
        "        250 * len(mol_states[idx]) + 50 , 250, 250, 200\n",
        "    )\n",
        "    d2d.DrawMolecules(_mols, highlightAtoms=highlight_atoms, highlightAtomColors=highlight_colors)\n",
        "    d2d.FinishDrawing()\n",
        "    display(SVG(d2d.GetDrawingText()))\n",
        "    # Symmetrical atoms with different charges\n",
        "if not symm_states_dict:\n",
        "    print(\n",
        "        \"No symmetrical states were found \"\n",
        "        + \" You can skip the next step.\"\n",
        "    )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "yHPHi5FtLBNj",
        "outputId": "c395d3fd-a0cc-4733-e37a-bb55d73fc346",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "For molecule 1 symmetrical states were detected:\n"
          ]
        },
        {
          "output_type": "display_data",
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "For molecule 2 symmetrical states were detected:\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            "These are found symmetrical states:\n"
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            "For molecule 3 symmetrical states were detected:\n"
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            "For molecule 4 symmetrical states were detected:\n"
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            "These are found symmetrical states:\n"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Select treatment of symmetrical states\n",
        "#@markdown Please, select whether to inclue symmetrical states for a molecule\n",
        "#@markdown or not. If for a particular molecule there are no symmetrical\n",
        "#@markdown states available, selecting True won't influence the behaviour\n",
        "use_symmetrical_states_molecule_0 = False #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_1 = True #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_2 = True #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_3 = True #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_4 = False #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_5 = False #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_6 = False #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_7 = False #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_8 = False #@param {type:\"boolean\"}\n",
        "use_symmetrical_states_molecule_9 = False #@param {type:\"boolean\"}\n",
        "\n",
        "ss = [\n",
        "    use_symmetrical_states_molecule_0,\n",
        "    use_symmetrical_states_molecule_1,\n",
        "    use_symmetrical_states_molecule_2,\n",
        "    use_symmetrical_states_molecule_3,\n",
        "    use_symmetrical_states_molecule_4,\n",
        "    use_symmetrical_states_molecule_5,\n",
        "    use_symmetrical_states_molecule_6,\n",
        "    use_symmetrical_states_molecule_7,\n",
        "    use_symmetrical_states_molecule_8,\n",
        "    use_symmetrical_states_molecule_9,\n",
        "]\n",
        "\n",
        "if symm_states_dict:\n",
        "    for idx in symm_states_dict:\n",
        "        if ss[idx]:\n",
        "            for _state in mol_states[idx]:\n",
        "                _state[\"use\"] = True"
      ],
      "metadata": {
        "cellView": "form",
        "id": "Pty6-7M2TFgj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Sites with multiple hydrogens\n",
        "sites_with_multiple_hs = []\n",
        "for ts in titratable_sites:\n",
        "    if (\n",
        "        pmol.GetAtomWithIdx(ts).GetNumExplicitHs()\n",
        "        + pmol.GetAtomWithIdx(ts).GetNumImplicitHs()\n",
        "        > 1\n",
        "    ):\n",
        "        sites_with_multiple_hs.append(ts)\n",
        "\n",
        "import textwrap\n",
        "if sites_with_multiple_hs:\n",
        "    print(\n",
        "        textwrap.fill(\n",
        "            (\n",
        "                f\"We detected {len(sites_with_multiple_hs)} sites to which \"\n",
        "                + \"multiple hydrogens are attached. Please, take a careful \"\n",
        "                + \"look and let us know whether we should consider those sites \"\n",
        "                + \"as multisite with each hydrogen titrating separately, or as \"\n",
        "                + \"single site, where only one hydrogen is titrated. Note, \"\n",
        "                + \"that we highlight the titratable sites for the molecule in \"\n",
        "                + \"the highest protonation state.\"\n",
        "            ),\n",
        "            120\n",
        "        )\n",
        "    )\n",
        "    colors = [(1.0, 0.0, 0.0, 0.2)]\n",
        "    for i, a in enumerate(sites_with_multiple_hs):\n",
        "        (pmol.GetAtomWithIdx(a)).SetProp('atomNote', str(i+1))\n",
        "    d2d = rdMolDraw2D.MolDraw2DSVG(250, 200)\n",
        "    at_highlights = {x: [colors[0]] for x in sites_with_multiple_hs}\n",
        "    at_rads = {x: 0.5 for x in sites_with_multiple_hs}\n",
        "    d2d.DrawMoleculeWithHighlights(pmol,\"\", at_highlights,{}, at_rads, {})\n",
        "    d2d.FinishDrawing()\n",
        "    display(SVG(d2d.GetDrawingText()))\n",
        "    for a in sites_with_multiple_hs:\n",
        "        (pmol.GetAtomWithIdx(a)).SetProp('atomNote', '')\n",
        "else:\n",
        "    mHs = None\n",
        "    print(\n",
        "        \"No sites to which multiple hydrogens are attached were detected. \"\n",
        "        + \" You can skip the next step.\"\n",
        "    )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 277
        },
        "id": "Yg2K0Mew3-KU",
        "outputId": "da22ccdf-517b-4ffb-ec6d-2dfef46602de"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "We detected 2 sites to which multiple hydrogens are attached. Please, take a careful look and let us know whether we\n",
            "should consider those sites as multisite with each hydrogen titrating separately, or as single site, where only one\n",
            "hydrogen is titrated. Note, that we highlight the titratable sites for the molecule in the highest protonation state.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Select treatment of multi-hydrogen sites\n",
        "#@markdown Do you want to treat titratable sites with multiple hydrogens\n",
        "#@markdown attached as single multisite or no? Default is no. If you want\n",
        "#@markdown to treat those with multisite representation tick the corresponding\n",
        "#@markdown variable. The id of titratable sites are shown in the previous cell.\n",
        "multiHs_titratable_site_1 = True #@param {type:\"boolean\"}\n",
        "multiHs_titratable_site_2 = True #@param {type:\"boolean\"}\n",
        "multiHs_titratable_site_3 = False #@param {type:\"boolean\"}\n",
        "multiHs_titratable_site_4 = False #@param {type:\"boolean\"}\n",
        "multiHs_titratable_site_5 = False #@param {type:\"boolean\"}\n",
        "\n",
        "from copy import deepcopy\n",
        "from itertools import permutations, product\n",
        "\n",
        "mHs = [\n",
        "    multiHs_titratable_site_1,\n",
        "    multiHs_titratable_site_2,\n",
        "    multiHs_titratable_site_3,\n",
        "    multiHs_titratable_site_4,\n",
        "    multiHs_titratable_site_5,\n",
        "][:len(sites_with_multiple_hs)]\n",
        "mhs_dict = {\n",
        "    sites_with_multiple_hs[i]: mHs[i]\n",
        "    for i in range(len(sites_with_multiple_hs))\n",
        "}\n",
        "pstate = mol_states[0][0]\n",
        "for _state_id in mol_states:\n",
        "    _tmp_new_states = []\n",
        "    for _j, _state in enumerate(mol_states[_state_id]):\n",
        "        sites_to_change = [\n",
        "            _site for _site in sites_with_multiple_hs\n",
        "            if (\n",
        "                sum(_state[\"h_formal_charges\"][_site]) !=\n",
        "                sum(pstate[\"h_formal_charges\"][_site])\n",
        "                and mhs_dict[_site] and _state[\"use\"]\n",
        "            )\n",
        "        ]\n",
        "        if not sites_to_change:\n",
        "            continue\n",
        "        original_combination = [\n",
        "            tuple(_state[\"h_formal_charges\"][_site])\n",
        "            for _site in sites_to_change\n",
        "        ]\n",
        "        new_combinations = []\n",
        "        for _combs in (\n",
        "            set(\n",
        "                product(\n",
        "                    *[set(permutations(x)) for x in original_combination]\n",
        "                )\n",
        "            ) - set(product(*[[x] for x in original_combination]))\n",
        "        ):\n",
        "            new_combinations.append(\n",
        "                [_combs[_idx] for _idx in range(len(sites_to_change))]\n",
        "            )\n",
        "        for _comb in new_combinations:\n",
        "            _tmp = deepcopy(_state)\n",
        "            for _site_comb, _site in zip(_comb, sites_to_change):\n",
        "                _tmp[\"h_formal_charges\"][_site] = list(_site_comb)\n",
        "            _tmp_new_states.append(_tmp)\n",
        "    if _tmp_new_states:\n",
        "        mol_states[_state_id].extend(_tmp_new_states)"
      ],
      "metadata": {
        "id": "6hA84tEeetpF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(mol_states[4])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b5DgTV4eVR3s",
        "outputId": "9747800a-0c34-46e2-ce68-4d753174c034"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Show state transitions\n",
        "state_transitions = []\n",
        "from rdkit.Chem import rdFMCS\n",
        "res = rdFMCS.FindMCS([pmol, pmol])\n",
        "similar_patt = Chem.MolFromSmarts(res.smartsString)\n",
        "subst_matches_pmol = pmol.GetSubstructMatches(similar_patt)[0]\n",
        "for i in mol_states:\n",
        "    if not mol_states[i][0][\"use\"]:\n",
        "        continue\n",
        "    m1 = mol_states[i][0][\"mol\"]\n",
        "    for j in mol_states:\n",
        "        if j <= i:\n",
        "            continue\n",
        "        if not mol_states[j][0][\"use\"]:\n",
        "            continue\n",
        "        m2 = mol_states[j][0][\"mol\"]\n",
        "        subst_matches1 = m1.GetSubstructMatches(similar_patt)[0]\n",
        "        subst_matches2 = m2.GetSubstructMatches(similar_patt)[0]\n",
        "        n_diffs = 0\n",
        "        for idx in titratable_sites:\n",
        "            if (\n",
        "                m1.GetAtomWithIdx(\n",
        "                    subst_matches1[subst_matches_pmol.index(idx)]\n",
        "                ).GetFormalCharge() !=\n",
        "                m2.GetAtomWithIdx(\n",
        "                    subst_matches2[subst_matches_pmol.index(idx)]\n",
        "                ).GetFormalCharge()\n",
        "            ):\n",
        "                n_diffs += 1\n",
        "        if n_diffs != 1:\n",
        "            continue\n",
        "        state_transitions.append((i, j))\n",
        "\n",
        "def view_difference(mol1, mol2):\n",
        "    mcs = rdFMCS.FindMCS([mol1,mol2])\n",
        "    mcs_mol = Chem.MolFromSmarts(mcs.smartsString)\n",
        "    match1 = mol1.GetSubstructMatch(mcs_mol)\n",
        "    match2 = mol2.GetSubstructMatch(mcs_mol)\n",
        "    target_atm1 = []\n",
        "    target_atm2 = []\n",
        "    for a1, a2 in zip(match1, match2):\n",
        "        if (\n",
        "            mol1.GetAtomWithIdx(a1).GetFormalCharge() !=\n",
        "            mol2.GetAtomWithIdx(a2).GetFormalCharge()\n",
        "        ):\n",
        "            target_atm1.append(a1)\n",
        "            target_atm2.append(a2)\n",
        "    d2d = Draw.MolsToGridImage(\n",
        "        [mol1, mol2],\n",
        "        highlightAtomLists=[target_atm1, target_atm2],\n",
        "        useSVG = True,\n",
        "    )\n",
        "    display(d2d)\n",
        "\n",
        "print(\"We found the following transitions between protonation states:\")\n",
        "for i, st_t in enumerate(state_transitions):\n",
        "    print(f\"Transition {i}\")\n",
        "    view_difference(\n",
        "        mol_states[st_t[0]][0][\"mol\"], mol_states[st_t[1]][0][\"mol\"]\n",
        "    )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ZBKOWkcz2HnX",
        "outputId": "143486d3-a267-4223-a850-e59f6b9a358c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "We found the following transitions between protonation states:\n",
            "Transition 0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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          "text": [
            "Transition 1\n"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Provide pKa values for transitions between protonated states\n",
        "#@markdown Please, provide pKa values for protonated states.\n",
        "pka_0 = 2 #@param {type:\"number\"}\n",
        "pka_1 = 3 #@param {type:\"number\"}\n",
        "pka_2 = 4 #@param {type:\"number\"}\n",
        "pka_3 = 5 #@param {type:\"number\"}\n",
        "pka_4 = 6.0 #@param {type:\"number\"}\n",
        "pka_5 = 0.0 #@param {type:\"number\"}\n",
        "pka_6 = 0.0 #@param {type:\"number\"}\n",
        "pka_7 = 0.0 #@param {type:\"number\"}\n",
        "pka_8 = 0.0 #@param {type:\"number\"}\n",
        "pka_9 = 0.0 #@param {type:\"number\"}\n",
        "\n",
        "pkas = [\n",
        "    pka_0, pka_1, pka_2, pka_3, pka_4,\n",
        "    pka_5, pka_6, pka_7, pka_8, pka_9,\n",
        "][:len(state_transitions)]"
      ],
      "metadata": {
        "id": "Qg4YAxSh-Ibw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Generate pKa matrix equation\n",
        "import numpy as np\n",
        "from sympy import Matrix, MatrixSymbol, symbols\n",
        "\n",
        "use_single_state = False\n",
        "\n",
        "def _get_nstates_to_use(_states: dict) -> list[int]:\n",
        "    \"\"\"\n",
        "    Get number of states to use for each protonation state.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    _states: dict\n",
        "        Dictionary of molecular states.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Number of states for each protonation state.\n",
        "    \"\"\"\n",
        "    return [\n",
        "        len(\n",
        "            [\n",
        "                _state for _state in _states[_idx] if _state[\"use\"]\n",
        "            ]\n",
        "        ) for _idx in _states\n",
        "    ]\n",
        "\n",
        "n_states_to_use = _get_nstates_to_use(mol_states)\n",
        "n_mols_to_use = len([x for x in n_states_to_use if x > 0])\n",
        "mapping_to_mols_to_use = {}\n",
        "_current_idx = 0\n",
        "for _state_idx in mol_states:\n",
        "    if mol_states[_state_idx][0][\"use\"]:\n",
        "        mapping_to_mols_to_use[_current_idx] = _state_idx\n",
        "        _current_idx += 1\n",
        "assert all(x in mapping_to_mols_to_use for x in range(n_mols_to_use))\n",
        "\n",
        "if (\n",
        "    len(mol_states.keys()) == 2\n",
        "    and all(x == 20 for x in n_states_to_use)\n",
        "):\n",
        "    use_single_state = True\n",
        "    print(f\"Single state should be used. pKa = {pkas[0]}\")\n",
        "else:\n",
        "    ph = symbols(\"pH\")\n",
        "    A = np.zeros(\n",
        "        (\n",
        "            len(state_transitions) + 1,\n",
        "            n_mols_to_use,\n",
        "        ),\n",
        "        dtype = 'int'\n",
        "    )\n",
        "    b = MatrixSymbol('b', len(state_transitions) + 1, 1).as_explicit()\n",
        "    bsubs = {b[0,0]: ph}\n",
        "    for i, (tr, pka) in enumerate(zip(state_transitions, pkas)):\n",
        "        state1 = tr[0]\n",
        "        state2 = tr[1]\n",
        "        n = n_states_to_use[state1]\n",
        "        m = n_states_to_use[state2]\n",
        "        if (\n",
        "            Chem.GetFormalCharge(mol_states[state1][0][\"mol\"])\n",
        "            > Chem.GetFormalCharge(mol_states[state2][0][\"mol\"])\n",
        "        ):\n",
        "            A[i+1, state1] =-1\n",
        "            A[i+1, state2] = 1\n",
        "            bsubs[b[i + 1, 0]] = pka - np.log10(n/m) - ph\n",
        "        else:\n",
        "            A[i+1, state1] = 1\n",
        "            A[i+1, state2] = -1\n",
        "            bsubs[b[i + 1, 0]] = pka - np.log10(m/n) - ph\n",
        "    A[0, 0] = 1\n",
        "    m = Matrix(A)\n",
        "    _, inds = m.T.rref()\n",
        "    removed_inds = [\n",
        "        x for x in range(len(state_transitions) + 1) if x not in inds\n",
        "    ]\n",
        "    Ar = A[list(inds)]\n",
        "    Ad = A[list(removed_inds)]\n",
        "    mr = Matrix(Ar)\n",
        "    md = Matrix(Ad)\n",
        "    p = MatrixSymbol('p', len(mols), 1).as_explicit()\n",
        "    b = b.subs(bsubs)\n",
        "    br = MatrixSymbol('br', len(inds), 1).as_explicit()\n",
        "    brsubs = {}\n",
        "    for i, idx in enumerate(inds):\n",
        "        brsubs[br[i, 0]] = b[idx, 0]\n",
        "\n",
        "    br = br.subs(brsubs)\n",
        "    br\n",
        "\n",
        "    sol = mr.solve(br)\n",
        "    print(\n",
        "        \"Recommended pKa values for protonations states, considering all previous \"\n",
        "        + \"input are:\"\n",
        "    )\n",
        "    for i in range(n_mols_to_use):\n",
        "        print(f\"State {mapping_to_mols_to_use[i]}: pKa = {sol[i,0]}\")\n",
        "        for _state in mol_states[mapping_to_mols_to_use[i]]:\n",
        "            if _state[\"use\"]:\n",
        "                _state[\"pka\"] = sol[i,0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FPCRNZxE_EIz",
        "outputId": "8487f253-e761-44bb-c0d4-4113cbb95dcf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Recommended pKa values for protonations states, considering all previous input are:\n",
            "State 0: pKa = pH\n",
            "State 1: pKa = 2.47712125471966\n",
            "State 2: pKa = 3.77815125038364\n",
            "State 3: pKa = 6.47712125471966 - pH\n",
            "State 4: pKa = 7.47712125471966 - pH\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Topology and structure general behavior\n",
        "#@markdown Do you want us to generate topology and molecule structure with\n",
        "#@markdown Open Force Field? If no, you would need to provide topologies in\n",
        "#@markdown **.itp** format in the following steps.\n",
        "is_generation_needed = True #@param {type:\"boolean\"}\n",
        "ff_to_use = \"openff-2.2.0.offxml\" #@param {type:\"string\"}\n",
        "molecule_name = \"MOL\" #@param {type:\"string\"}\n",
        "_mols = []\n",
        "_states_to_use = []\n",
        "\n",
        "def _reverse_map(mapping: dict[int, int]) -> dict[int, int]:\n",
        "    \"\"\"\n",
        "    Reverse mapping to common indexing base.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    mapping: dict[int, int]\n",
        "        Mapping from current indexing to common indexing.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Backmapping from common indexing to current.\n",
        "    \"\"\"\n",
        "    return {mapping[i]: i for i in mapping}\n",
        "\n",
        "def _reorder_charges(\n",
        "    charges: list[int],\n",
        "    mapping1: dict[int, int],\n",
        "    mapping2: dict[int, int],\n",
        ") -> list[int]:\n",
        "    \"\"\"\n",
        "    Reorder charges given in current indexing other indexing system.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    charges: list[int]\n",
        "        Charges in the current indexing.\n",
        "    mapping1: dict[int, int]\n",
        "        First mapping to common indexing.\n",
        "    mapping2: dict[int, int]\n",
        "        Second mapping to common indexing.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Charges in the second indexing.\n",
        "    \"\"\"\n",
        "    results = [0] * len(charges)\n",
        "    back_map_2 = _reverse_map(mapping2)\n",
        "    for i in range(len(charges)):\n",
        "        results[i] = charges[back_map_2[mapping1[i]]]\n",
        "    return results\n",
        "\n",
        "def _generate_hydrogen_charges(\n",
        "    hydrogen_map: dict[int, dict[str, int | float]],\n",
        "    h_formal_charge: dict[int, list[int]],\n",
        "    mapping1: dict[int, int],\n",
        "    mapping2: dict[int, int],\n",
        ") -> list[int]:\n",
        "    \"\"\"\n",
        "    Generate correct hydrogen charges for common indexing.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    hydrogen_map: dict[int, dict[str, int | float]]\n",
        "        Map of hydrogens to heavy atoms in current indexing.\n",
        "    h_formal_charge: dict[int, list[int]]\n",
        "        Dictionary of formal charges in common indexing.\n",
        "    mapping1: dict[int, int]\n",
        "        First mapping to common indexing.\n",
        "    mapping2: dict[int, int]\n",
        "        Second mapping to common indexing.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Hydrogen charges in the second indexing.\n",
        "    \"\"\"\n",
        "    sorted_h_formal_charge = dict(sorted(h_formal_charge.items()))\n",
        "    back_map_1 = _reverse_map(mapping1)\n",
        "    back_map_2 = _reverse_map(mapping2)\n",
        "    # we iterate atom by atom in common indexing\n",
        "    # we need to first take first heavy atom in common basis\n",
        "    # and write charges for this one\n",
        "    h_charges = []\n",
        "    for i in sorted_h_formal_charge:\n",
        "        if not len(sorted_h_formal_charge):\n",
        "            continue\n",
        "        if back_map_2[i] in hydrogen_map:\n",
        "            _h_charges = hydrogen_map[back_map_2[i]][\"charges\"]\n",
        "        else:\n",
        "            _h_charges = []\n",
        "        if len(_h_charges) > 0:\n",
        "            assert all(x == _h_charges[0] for x in _h_charges), \"Charges not eq\"\n",
        "        _charge = _h_charges[0] if len(_h_charges) else 0\n",
        "        if len(_h_charges) != len(sorted_h_formal_charge[i]):\n",
        "            _h_charges = [0] * len(sorted_h_formal_charge[i])\n",
        "            for idx, f_charge in enumerate(sorted_h_formal_charge[i]):\n",
        "                _h_charges[idx] = _charge if f_charge != 0 else 0\n",
        "        h_charges.extend(_h_charges)\n",
        "    return h_charges\n",
        "\n",
        "def write_header(\n",
        "    _use_single_state: bool,\n",
        "    interchange: Interchange,\n",
        "    state: dict,\n",
        "    output_file: str,\n",
        "):\n",
        "    \"\"\"\n",
        "    Write header for phbuilder entry.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    _use_single_state: bool\n",
        "        Flag for using single state.\n",
        "    interchange: Interchange\n",
        "        Interchange for topology access.\n",
        "    state: dict\n",
        "        Dictionary of state data (to access charges).\n",
        "    output_file: str\n",
        "        Output file.\n",
        "    \"\"\"\n",
        "    with open(output_file, \"w\") as f:\n",
        "        f.write(f\"[ {interchange.topology.molecule(0).name} ]\\n\")\n",
        "        f.write(f\"{'incl':<10}= {interchange.topology.molecule(0).name}\\n\")\n",
        "        if not all(x.name for x in interchange.topology.atoms):\n",
        "            for _i, x in enumerate(interchange.topology.atoms):\n",
        "                x.name = interchange.topology.molecule(0).name + f\"_{_i}\"\n",
        "        atom_names = \" \".join(\n",
        "            [x.name for x in interchange.topology.atoms]\n",
        "        )\n",
        "        f.write(f\"{'atoms':<10}= {atom_names}\\n\")\n",
        "        if _use_single_state:\n",
        "            atom_charges = \" \".join(\n",
        "                [str(x) for x in state[\"charges\"]]\n",
        "            )\n",
        "            f.write(f\"{'qqA':<10}= {atom_charges}\\n\")\n",
        "        else:\n",
        "            f.write(\n",
        "                f\"{'qqA':<10}= {' '.join(['0.0' for _ in atom_names])}\\n\"\n",
        "            )\n",
        "\n",
        "def write_state(\n",
        "    _use_single_state: bool,\n",
        "    state: dict,\n",
        "    output_file: str,\n",
        "    state_id: int,\n",
        "):\n",
        "    \"\"\"\n",
        "    Write state data for phbuilder entry.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    _use_single_state: bool\n",
        "        Flag for using single state.\n",
        "    state: dict\n",
        "        Dictionary of state data (to access charges).\n",
        "    output_file: str\n",
        "        Output file.\n",
        "    state_id: int\n",
        "        State index.\n",
        "    \"\"\"\n",
        "    with open(output_file, \"a\") as f:\n",
        "        atom_charges = \" \".join(\n",
        "            [str(x) for x in state[\"charges\"]]\n",
        "        )\n",
        "        if _use_single_state:\n",
        "            f.write(f\"{'pKa_1':<10}= {pkas[0]}\\n\")\n",
        "        else:\n",
        "            f.write(f\"{f'pKa_{state_id}':<10}= {state['pka']}\\n\")\n",
        "\n",
        "        f.write(f\"{f'qqB_{state_id}':<10}= {atom_charges}\\n\")\n",
        "        f.write(f\"{f'dvdl_{state_id}':<10}= 0.0\\n\")\n",
        "\n",
        "if is_generation_needed:\n",
        "    ff = ForceField(ff_to_use)\n",
        "    _j = 1\n",
        "    for _state_idx in mol_states:\n",
        "        # We skip mol state if first state is not used\n",
        "        if not mol_states[_state_idx][0][\"use\"]:\n",
        "            continue\n",
        "        _states_to_use.append(_state_idx)\n",
        "        _m = Molecule.from_rdkit(\n",
        "            mol_states[_state_idx][0][\"mol\"],\n",
        "            allow_undefined_stereo=True)\n",
        "        _m.generate_conformers()\n",
        "        interchange = ff.create_interchange(_m.to_topology())\n",
        "        _state_heavy_atom_charges = [\n",
        "            a.partial_charge.magnitude for a in interchange.topology.atoms\n",
        "            if a.atomic_number != 1\n",
        "        ]\n",
        "\n",
        "        _hydrogen_map = {\n",
        "            a.molecule_atom_index: {\n",
        "                \"hidx\": [\n",
        "                    atom.molecule_atom_index for atom in a.bonded_atoms\n",
        "                    if atom.atomic_number == 1\n",
        "                ],\n",
        "                \"charges\": [\n",
        "                    atom.partial_charge.magnitude for atom in a.bonded_atoms\n",
        "                    if atom.atomic_number == 1\n",
        "                ],\n",
        "            } for a in interchange.topology.atoms if a.atomic_number != 1\n",
        "        }\n",
        "\n",
        "        for state in mol_states[_state_idx]:\n",
        "            _state_charges = _reorder_charges(\n",
        "                _state_heavy_atom_charges,\n",
        "                mol_states[_state_idx][0][\"heavy_atom_mapping\"],\n",
        "                state[\"heavy_atom_mapping\"],\n",
        "            )\n",
        "            _state_h_charges = _generate_hydrogen_charges(\n",
        "                _hydrogen_map,\n",
        "                state[\"h_formal_charges\"],\n",
        "                mol_states[_state_idx][0][\"heavy_atom_mapping\"],\n",
        "                state[\"heavy_atom_mapping\"],\n",
        "            )\n",
        "            state[\"charges\"] = _state_charges + _state_h_charges\n",
        "\n",
        "\n",
        "        _mols.append(_m.to_rdkit())\n",
        "        _rdmol = _m.to_rdkit()\n",
        "\n",
        "        # Write parameters\n",
        "        if _state_idx == 0:\n",
        "            interchange.to_gromacs(f\"molecule_{_state_idx}\")\n",
        "            write_header(\n",
        "                use_single_state, interchange, mol_states[0][0], \"phbuiler.in\"\n",
        "            )\n",
        "            if not use_single_state:\n",
        "                write_state(False, mol_states[0][0], \"phbuiler.in\", _j)\n",
        "                _j += 1\n",
        "        else:\n",
        "            interchange.to_top(f\"molecule_{_state_idx}.top\")\n",
        "            for state in mol_states[_state_idx]:\n",
        "                if state[\"use\"]:\n",
        "                    write_state(\n",
        "                        use_single_state, state, \"phbuiler.in\", _j\n",
        "                    )\n",
        "                    _j += 1\n"
      ],
      "metadata": {
        "id": "JsdLCCMpX4LS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sum([len([x for x in mol_states[i] if x[\"use\"]]) for i in mol_states])"
      ],
      "metadata": {
        "id": "r7x3VgStJkYf",
        "outputId": "25b619d3-7894-41cc-fbcd-44e31a6530a8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for s in mol_states[1]:\n",
        "    print(s[\"h_formal_charges\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nb6wjPSEYBfR",
        "outputId": "3a32a8c9-c48f-4fcd-aa5e-0d635e8a3041"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{0: [1, 1, 1], 1: [1], 2: [1, 1, 1], 3: [], 4: [1, 1], 5: [0], 6: [1, 1], 7: [1], 8: [1, 1], 9: [1]}\n",
            "{0: [1, 1, 1], 1: [1], 2: [1, 1, 1], 3: [], 6: [1, 1], 7: [0], 4: [1, 1], 5: [1], 8: [1, 1], 9: [1]}\n",
            "{0: [1, 1, 1], 1: [1], 2: [1, 1, 1], 3: [], 8: [1, 1], 9: [0], 4: [1, 1], 5: [1], 6: [1, 1], 7: [1]}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def _reorder_charges(\n",
        "    charges: list[int],\n",
        "    mapping1: dict[int, int],\n",
        "    mapping2: dict[int, int],\n",
        ") -> list[int]:\n",
        "    \"\"\"\n",
        "    Reorder charges given in current indexing other indexing system.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    charges: list[int]\n",
        "        Charges in the current indexing.\n",
        "    mapping1: dict[int, int]\n",
        "        First mapping to common indexing.\n",
        "    mapping2: dict[int, int]\n",
        "        Second mapping to common indexing.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Charges in the second indexing.\n",
        "    \"\"\"\n",
        "    results = [0] * len(charges)\n",
        "    back_map_2 = _reverse_map(mapping2)\n",
        "    print(back_map_2)\n",
        "    for i in range(len(charges)):\n",
        "        results[i] = charges[back_map_2[mapping1[i]]]\n",
        "    return results\n",
        "\n",
        "_ch = mol_states[1][0][\"charges\"]\n",
        "print(_ch)\n",
        "print(_reorder_charges(_ch, mol_states[1][0][\"heavy_atom_mapping\"],mol_states[1][0][\"heavy_atom_mapping\"]))\n",
        "print(_reorder_charges(_ch, mol_states[1][0][\"heavy_atom_mapping\"],mol_states[1][1][\"heavy_atom_mapping\"]))\n",
        "print(_reorder_charges(_ch, mol_states[1][0][\"heavy_atom_mapping\"],mol_states[1][2][\"heavy_atom_mapping\"]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z6fExgDLygRB",
        "outputId": "aae77e57-937c-464f-d388-18f1eebf91f1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[-1.0165600799999999, 0.16973991999999996, -1.0165600799999999, -0.11196008000000002, 0.43213991999999996, -0.54846008, 0.14193991999999997, -0.59976008, 0.14193991999999997, -0.59976008]\n",
            "{0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9}\n",
            "[-1.0165600799999999, 0.16973991999999996, -1.0165600799999999, -0.11196008000000002, 0.43213991999999996, -0.54846008, 0.14193991999999997, -0.59976008, 0.14193991999999997, -0.59976008]\n",
            "{0: 0, 1: 1, 2: 2, 3: 3, 6: 4, 7: 5, 4: 6, 5: 7, 8: 8, 9: 9}\n",
            "[-1.0165600799999999, 0.16973991999999996, -1.0165600799999999, -0.11196008000000002, 0.14193991999999997, -0.59976008, 0.43213991999999996, -0.54846008, 0.14193991999999997, -0.59976008]\n",
            "{0: 0, 1: 1, 2: 2, 3: 3, 8: 4, 9: 5, 4: 6, 5: 7, 6: 8, 7: 9}\n",
            "[-1.0165600799999999, 0.16973991999999996, -1.0165600799999999, -0.11196008000000002, 0.14193991999999997, -0.59976008, 0.14193991999999997, -0.59976008, 0.43213991999999996, -0.54846008]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for atom_idx, atom in enumerate(mol_states[2][0][\"mol\"].GetAtoms()):\n",
        "    print(atom_idx, atom.GetChiralTag(), atom.HasProp(\"_ChiralityPossible\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f5uymtzuhDY_",
        "outputId": "cce7e272-1e7d-431e-baaf-77a03177b541"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 CHI_UNSPECIFIED 0\n",
            "1 CHI_UNSPECIFIED 0\n",
            "2 CHI_UNSPECIFIED 0\n",
            "3 CHI_UNSPECIFIED 0\n",
            "4 CHI_UNSPECIFIED 0\n",
            "5 CHI_UNSPECIFIED 0\n",
            "6 CHI_UNSPECIFIED 0\n",
            "7 CHI_UNSPECIFIED 0\n",
            "8 CHI_UNSPECIFIED 0\n",
            "9 CHI_UNSPECIFIED 0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mol_states[1][0][\"mol\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "72x3Q3YdVCU5",
        "outputId": "be1f29f7-7669-4b50-b3b8-49ba93c58e22"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<rdkit.Chem.rdchem.Mol at 0x7e2ad9a1aa40>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 206
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# We need to transform top to itp and also for the future\n",
        "# needs we need the functionality for parsing atoms and\n",
        "# bonds sections. This will allow us to generate molecular\n",
        "# graphs, which in turn, will allow us to compare molecules\n",
        "# and prepare data for constant pH.\n",
        "\"\"\"\n",
        "We need to support two types of behaviour:\n",
        "1. Easy case\n",
        "    We generate molecule our selves with OpenFF.\n",
        "    In this case we actually know what is the order atoms in\n",
        "    all protonation states and we can easily do matching.\n",
        "    We also know what to do with all possible states -\n",
        "    symmetrical and with multiple hydrogens. From created\n",
        "    interchanges and topology files we can get all the\n",
        "    partial charges and then using rdkit and we can generate\n",
        "    correct charge lists.\n",
        "    We start by implementing this.\n",
        "2. More complex case\n",
        "    The topologies are provided by the user. In this case\n",
        "    we:\n",
        "        (i) expect that the user will provide us not only\n",
        "            with the topologies, but also with structures\n",
        "            for all states\n",
        "        (ii) don't expect that the order of atoms is the\n",
        "            same as in RdKit.\n",
        "    We will reconstruct the order based on rdkit functionality\n",
        "    https://greglandrum.github.io/rdkit-blog/posts/2022-12-18-introducing-rdDetermineBonds.html\n",
        "\n",
        "    NOTE: in principal, the first case can also be treated\n",
        "    as the second. But we will add it later.\n",
        "In general, we need to read top/itp files (for now we always\n",
        "expect [ atoms ] section to be present) and assign charges\n",
        "in the order of mols[0]. For each state we additionally\n",
        "treap symmetrical states and multi-H states. Then we change\n",
        "the order according to the order in the first file.\n",
        "\"\"\"\n",
        "class GMX_topology:\n",
        "    \"\"\"\n",
        "    Reads gromacs topology file and parses some of the sections.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    gmx_top: str\n",
        "        GROMACS topology file\n",
        "\n",
        "    Attributes\n",
        "    ----------\n",
        "    blocks: Dict[str, str]\n",
        "        Dictionary of blocks available in the topology file\n",
        "    atoms: list\n",
        "\n",
        "    Methods\n",
        "    -------\n",
        "    parse_atoms()\n",
        "        Parse atom section if present. Generates at\n",
        "    parse_atomtypes()\n",
        "        Parse atomtypes section if present.\n",
        "    parse_bonds()\n",
        "        Parse bonds.\n",
        "\n",
        "\n",
        "    \"\"\"\n",
        "    def __init__(self, gmx_top):\n",
        "        self.blocks = {}\n",
        "        with open(gmx_top, \"r\") as top:\n",
        "            section = None\n",
        "            tmp = []\n",
        "            for line in top:\n",
        "                if line.strip().startswith(\"[\"):\n",
        "                    if section:\n",
        "                        if section in self.blocks:\n",
        "                            self.blocks[section] += [tmp]\n",
        "                        else:\n",
        "                            self.blocks[section] = [tmp]\n",
        "                    else:\n",
        "                        self.blocks[\"header\"] = [tmp]\n",
        "                    section = line.strip()[1:-1].strip()\n",
        "                    tmp = []\n",
        "                else:\n",
        "                    tmp += [line]\n",
        "            if section in self.blocks:\n",
        "                self.blocks[section] += [tmp]\n",
        "            else:\n",
        "                self.blocks[section] = [tmp]\n",
        "\n",
        "    def parse_atoms(self):\n",
        "        \"\"\"\n",
        "        Parse atoms block. As a result, creates atoms attribute, where for each\n",
        "        atom in the provided topology atomtype and index are stored\n",
        "        \"\"\"\n",
        "        if \"atoms\" not in self.blocks:\n",
        "            self.atoms = []\n",
        "        else:\n",
        "            self.atoms = []\n",
        "            for section in self.blocks[\"atoms\"]:\n",
        "                for line in section:\n",
        "                    # Skip non-informative lines\n",
        "                    if line.strip().startswith(\";\"):\n",
        "                        continue\n",
        "                    if line.strip().startswith(\"#\"):\n",
        "                        continue\n",
        "                    if not line.strip():\n",
        "                        continue\n",
        "                    self.atoms.append(\n",
        "                        (\n",
        "                            int(line.split()[0]) - 1,\n",
        "                            line.split()[1],\n",
        "                        )\n",
        "                    )\n",
        "\n",
        "    def parse_dihedrals(self):\n",
        "        \"\"\"\n",
        "        Parse dihedral section of the topology. Only dihdrals of type 1 and 9\n",
        "        with explicitly provided parameters are taken into account.\n",
        "        \"\"\"\n",
        "        if \"dihedrals\" not in self.blocks:\n",
        "            self.dihedrals = []\n",
        "        else:\n",
        "            self.dihedrals = []\n",
        "            for section in self.blocks[\"dihedrals\"]:\n",
        "                for line in section:\n",
        "                    # Skip non-informative lines\n",
        "                    if line.strip().startswith(\";\"):\n",
        "                        continue\n",
        "                    if line.strip().startswith(\"#\"):\n",
        "                        continue\n",
        "                    if not line.strip():\n",
        "                        continue\n",
        "                    if int(line.split()[4]) not in [1, 9]:\n",
        "                        continue\n",
        "                    if len(line.split()) < 8:\n",
        "                        continue\n",
        "                    self.dihedrals.append(\n",
        "                        (\n",
        "                            int(line.split()[0])-1,\n",
        "                            int(line.split()[1])-1,\n",
        "                            int(line.split()[2])-1,\n",
        "                            int(line.split()[3])-1,\n",
        "                            line\n",
        "                        )\n",
        "                    )\n",
        "\n",
        "    def parse_dihedraltypes(self):\n",
        "        \"\"\"\n",
        "        Parse dihedraltypes section in the topology if present. Creates\n",
        "        dihedraltypes attribute, where types and of 4 atoms are provided\n",
        "        and also the corresponding dihedral string (to ease the search in\n",
        "        topology file). All imporpers and Fourier dihedrals are for now\n",
        "        excluded. Thus, only type 1 and 9 are supported.\n",
        "        https://manual.gromacs.org/current/reference-manual/topologies/topology-file-formats.html\n",
        "\n",
        "        NOTE: We also should somehow iterate through difened torsions if they\n",
        "        are present.\n",
        "        \"\"\"\n",
        "        if \"dihedraltypes\" not in self.blocks:\n",
        "            self.dihedraltypes = []\n",
        "        else:\n",
        "            self.dihedraltypes = []\n",
        "            for section in self.blocks[\"dihedraltypes\"]:\n",
        "                for line in section:\n",
        "                    # Skip non-informative lines\n",
        "                    if line.strip().startswith(\";\"):\n",
        "                        continue\n",
        "                    if line.strip().startswith(\"#\"):\n",
        "                        continue\n",
        "                    if not line.strip():\n",
        "                        continue\n",
        "                    if int(line.split()[4]) not in [1, 9]:\n",
        "                        continue\n",
        "                    self.dihedraltypes.append(\n",
        "                        (\n",
        "                            line.split()[0],\n",
        "                            line.split()[1],\n",
        "                            line.split()[2],\n",
        "                            line.split()[3],\n",
        "                            line[:(line.rfind(line.split()[3]) + len(line.split()[3]))].strip()\n",
        "                        )\n",
        "                    )"
      ],
      "metadata": {
        "id": "h-x0GMr6xMgS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Provide topologies data\n",
        "#@markdown If parameterisation is needed, all included molecules will be\n",
        "#@markdown parameterized with open force field. If not, for all\n",
        "is_parameterisation_needed = True #@param {type:\"boolean\"}\n",
        "included_mols = [m for m,i in zip(mols, incl) if i]\n",
        "included_svgs = [s for s,i in zip(svgs, incl) if i]\n",
        "for i, s in enumerate(included_svgs):\n",
        "    print(f\"This is Molecule {i}\")\n",
        "    display(SVG(svgs[i]))\n",
        "\n",
        "parameters_for_molecule_0 = \"\" #@param {type:\"string\"}\n",
        "parameters_for_molecule_1 = \"\" #@param {type:\"string\"}\n",
        "parameters_for_molecule_2 = \"\" #@param {type:\"string\"}\n",
        "parameters_for_molecule_3 = \"\" #@param {type:\"string\"}\n",
        "parameters_for_molecule_4 = \"\" #@param {type:\"string\"}"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 464
        },
        "id": "dugAhjr3ex7W",
        "outputId": "cd8a07b4-a286-4dc3-bcf1-da5ee3de28a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "This is Molecule 0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.SVG object>"
            ],
            "image/svg+xml": "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:rdkit=\"http://www.rdkit.org/xml\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" version=\"1.1\" baseProfile=\"full\" xml:space=\"preserve\" width=\"250px\" height=\"200px\" viewBox=\"0 0 250 200\">\n<!-- END OF HEADER -->\n<rect style=\"opacity:1.0;fill:#FFFFFF;stroke:none\" width=\"250.0\" height=\"200.0\" x=\"0.0\" y=\"0.0\"> </rect>\n<path class=\"bond-0 atom-0 atom-1\" d=\"M 166.3,106.4 L 142.2,99.2\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-0 atom-0 atom-1\" d=\"M 142.2,99.2 L 118.2,92.1\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 123.0,93.5 L 117.2,69.0\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 117.2,69.0 L 111.3,44.4\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 114.5,95.6 L 108.6,71.0\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 108.6,71.0 L 102.7,46.5\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-2 atom-1 atom-3\" d=\"M 118.2,92.1 L 101.6,107.8\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-2 atom-1 atom-3\" d=\"M 101.6,107.8 L 85.0,123.5\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-3 atom-0 atom-4\" d=\"M 182.8,111.3 L 202.7,117.2\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-3 atom-0 atom-4\" d=\"M 202.7,117.2 L 222.5,123.1\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-4 atom-0 atom-5\" d=\"M 171.5,119.1 L 166.2,137.1\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-4 atom-0 atom-5\" d=\"M 166.2,137.1 L 160.9,155.0\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-5 atom-0 atom-6\" d=\"M 177.6,98.6 L 183.0,80.6\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-5 atom-0 atom-6\" d=\"M 183.0,80.6 L 188.3,62.7\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-6 atom-3 atom-7\" d=\"M 65.8,129.7 L 46.7,124.0\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-6 atom-3 atom-7\" d=\"M 46.7,124.0 L 27.5,118.3\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path d=\"M 119.4,92.4 L 118.2,92.1 L 117.3,92.9\" style=\"fill:none;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;\"/>\n<path class=\"atom-0\" d=\"M 170.9 100.5 L 176.3 109.3 Q 176.9 110.2, 177.8 111.8 Q 178.6 113.4, 178.7 113.5 L 178.7 100.5 L 180.9 100.5 L 180.9 117.2 L 178.6 117.2 L 172.7 107.5 Q 172.1 106.4, 171.3 105.1 Q 170.6 103.8, 170.4 103.4 L 170.4 117.2 L 168.2 117.2 L 168.2 100.5 L 170.9 100.5 \" fill=\"#0000FF\"/>\n<path class=\"atom-0\" d=\"M 184.0 103.5 L 187.0 103.5 L 187.0 100.4 L 188.3 100.4 L 188.3 103.5 L 191.3 103.5 L 191.3 104.6 L 188.3 104.6 L 188.3 107.7 L 187.0 107.7 L 187.0 104.6 L 184.0 104.6 L 184.0 103.5 \" fill=\"#0000FF\"/>\n<path class=\"atom-2\" d=\"M 96.8 34.9 Q 96.8 30.9, 98.8 28.6 Q 100.8 26.4, 104.5 26.4 Q 108.2 26.4, 110.2 28.6 Q 112.1 30.9, 112.1 34.9 Q 112.1 38.9, 110.1 41.2 Q 108.1 43.5, 104.5 43.5 Q 100.8 43.5, 98.8 41.2 Q 96.8 39.0, 96.8 34.9 M 104.5 41.6 Q 107.0 41.6, 108.4 39.9 Q 109.8 38.2, 109.8 34.9 Q 109.8 31.6, 108.4 30.0 Q 107.0 28.3, 104.5 28.3 Q 101.9 28.3, 100.5 29.9 Q 99.2 31.6, 99.2 34.9 Q 99.2 38.3, 100.5 39.9 Q 101.9 41.6, 104.5 41.6 \" fill=\"#FF0000\"/>\n<path class=\"atom-3\" d=\"M 67.8 132.6 Q 67.8 128.6, 69.8 126.4 Q 71.7 124.1, 75.4 124.1 Q 79.1 124.1, 81.1 126.4 Q 83.1 128.6, 83.1 132.6 Q 83.1 136.6, 81.1 138.9 Q 79.1 141.2, 75.4 141.2 Q 71.8 141.2, 69.8 138.9 Q 67.8 136.7, 67.8 132.6 M 75.4 139.3 Q 78.0 139.3, 79.3 137.6 Q 80.7 135.9, 80.7 132.6 Q 80.7 129.3, 79.3 127.7 Q 78.0 126.0, 75.4 126.0 Q 72.9 126.0, 71.5 127.6 Q 70.1 129.3, 70.1 132.6 Q 70.1 136.0, 71.5 137.6 Q 72.9 139.3, 75.4 139.3 \" fill=\"#FF0000\"/>\n<path class=\"atom-4\" d=\"M 224.5 117.3 L 226.7 117.3 L 226.7 124.4 L 235.2 124.4 L 235.2 117.3 L 237.5 117.3 L 237.5 134.0 L 235.2 134.0 L 235.2 126.3 L 226.7 126.3 L 226.7 134.0 L 224.5 134.0 L 224.5 117.3 \" fill=\"#000000\"/>\n<path class=\"atom-5\" d=\"M 151.3 156.9 L 153.5 156.9 L 153.5 164.0 L 162.1 164.0 L 162.1 156.9 L 164.3 156.9 L 164.3 173.6 L 162.1 173.6 L 162.1 165.9 L 153.5 165.9 L 153.5 173.6 L 151.3 173.6 L 151.3 156.9 \" fill=\"#000000\"/>\n<path class=\"atom-6\" d=\"M 184.8 44.1 L 187.1 44.1 L 187.1 51.2 L 195.6 51.2 L 195.6 44.1 L 197.9 44.1 L 197.9 60.8 L 195.6 60.8 L 195.6 53.1 L 187.1 53.1 L 187.1 60.8 L 184.8 60.8 L 184.8 44.1 \" fill=\"#000000\"/>\n<path class=\"atom-7\" d=\"M 12.5 107.4 L 14.8 107.4 L 14.8 114.5 L 23.3 114.5 L 23.3 107.4 L 25.5 107.4 L 25.5 124.1 L 23.3 124.1 L 23.3 116.4 L 14.8 116.4 L 14.8 124.1 L 12.5 124.1 L 12.5 107.4 \" fill=\"#000000\"/>\n</svg>"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "This is Molecule 1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.SVG object>"
            ],
            "image/svg+xml": "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:rdkit=\"http://www.rdkit.org/xml\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" version=\"1.1\" baseProfile=\"full\" xml:space=\"preserve\" width=\"250px\" height=\"200px\" viewBox=\"0 0 250 200\">\n<!-- END OF HEADER -->\n<rect style=\"opacity:1.0;fill:#FFFFFF;stroke:none\" width=\"250.0\" height=\"200.0\" x=\"0.0\" y=\"0.0\"> </rect>\n<path class=\"bond-0 atom-0 atom-1\" d=\"M 134.4,100.0 L 100.5,100.0\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-0 atom-0 atom-1\" d=\"M 100.5,100.0 L 66.6,100.0\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 73.5,100.0 L 57.0,71.5\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 57.0,71.5 L 40.6,43.0\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 63.2,105.9 L 46.8,77.4\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-1 atom-1 atom-2\" d=\"M 46.8,77.4 L 30.3,48.9\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-2 atom-1 atom-3\" d=\"M 66.6,100.0 L 50.9,127.2\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-2 atom-1 atom-3\" d=\"M 50.9,127.2 L 35.2,154.4\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-3 atom-0 atom-4\" d=\"M 170.5,100.0 L 191.7,100.0\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-3 atom-0 atom-4\" d=\"M 191.7,100.0 L 213.0,100.0\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-4 atom-0 atom-5\" d=\"M 145.5,113.8 L 145.5,139.4\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-4 atom-0 atom-5\" d=\"M 145.5,139.4 L 145.5,165.1\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-5 atom-0 atom-6\" d=\"M 145.5,86.2 L 145.5,60.6\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path class=\"bond-5 atom-0 atom-6\" d=\"M 145.5,60.6 L 145.5,34.9\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n<path d=\"M 68.3,100.0 L 66.6,100.0 L 65.8,101.4\" style=\"fill:none;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;\"/>\n<path class=\"atom-0\" d=\"M 140.5 88.8 L 147.8 100.7 Q 148.6 101.8, 149.7 103.9 Q 150.9 106.1, 151.0 106.2 L 151.0 88.8 L 153.9 88.8 L 153.9 111.2 L 150.9 111.2 L 143.0 98.2 Q 142.1 96.7, 141.1 95.0 Q 140.2 93.3, 139.9 92.7 L 139.9 111.2 L 137.0 111.2 L 137.0 88.8 L 140.5 88.8 \" fill=\"#0000FF\"/>\n<path class=\"atom-0\" d=\"M 158.1 92.9 L 162.1 92.9 L 162.1 88.7 L 163.8 88.7 L 163.8 92.9 L 167.9 92.9 L 167.9 94.4 L 163.8 94.4 L 163.8 98.5 L 162.1 98.5 L 162.1 94.4 L 158.1 94.4 L 158.1 92.9 \" fill=\"#0000FF\"/>\n<path class=\"atom-2\" d=\"M 17.0 31.8 Q 17.0 26.4, 19.6 23.4 Q 22.3 20.4, 27.2 20.4 Q 32.2 20.4, 34.8 23.4 Q 37.5 26.4, 37.5 31.8 Q 37.5 37.2, 34.8 40.3 Q 32.1 43.4, 27.2 43.4 Q 22.3 43.4, 19.6 40.3 Q 17.0 37.2, 17.0 31.8 M 27.2 40.8 Q 30.6 40.8, 32.4 38.6 Q 34.3 36.3, 34.3 31.8 Q 34.3 27.4, 32.4 25.2 Q 30.6 23.0, 27.2 23.0 Q 23.8 23.0, 21.9 25.2 Q 20.1 27.4, 20.1 31.8 Q 20.1 36.3, 21.9 38.6 Q 23.8 40.8, 27.2 40.8 \" fill=\"#FF0000\"/>\n<path class=\"atom-3\" d=\"M 17.0 168.3 Q 17.0 163.0, 19.6 160.0 Q 22.3 157.0, 27.2 157.0 Q 32.2 157.0, 34.8 160.0 Q 37.5 163.0, 37.5 168.3 Q 37.5 173.8, 34.8 176.9 Q 32.1 179.9, 27.2 179.9 Q 22.3 179.9, 19.6 176.9 Q 17.0 173.8, 17.0 168.3 M 27.2 177.4 Q 30.6 177.4, 32.4 175.1 Q 34.3 172.8, 34.3 168.3 Q 34.3 164.0, 32.4 161.7 Q 30.6 159.5, 27.2 159.5 Q 23.8 159.5, 21.9 161.7 Q 20.1 163.9, 20.1 168.3 Q 20.1 172.8, 21.9 175.1 Q 23.8 177.4, 27.2 177.4 \" fill=\"#FF0000\"/>\n<path class=\"atom-3\" d=\"M 40.6 160.6 L 48.3 160.6 L 48.3 162.3 L 40.6 162.3 L 40.6 160.6 \" fill=\"#FF0000\"/>\n<path class=\"atom-4\" d=\"M 215.6 88.8 L 218.6 88.8 L 218.6 98.3 L 230.0 98.3 L 230.0 88.8 L 233.0 88.8 L 233.0 111.2 L 230.0 111.2 L 230.0 100.9 L 218.6 100.9 L 218.6 111.2 L 215.6 111.2 L 215.6 88.8 \" fill=\"#000000\"/>\n<path class=\"atom-5\" d=\"M 136.7 167.7 L 139.8 167.7 L 139.8 177.2 L 151.2 177.2 L 151.2 167.7 L 154.2 167.7 L 154.2 190.0 L 151.2 190.0 L 151.2 179.7 L 139.8 179.7 L 139.8 190.0 L 136.7 190.0 L 136.7 167.7 \" fill=\"#000000\"/>\n<path class=\"atom-6\" d=\"M 136.7 10.0 L 139.8 10.0 L 139.8 19.5 L 151.2 19.5 L 151.2 10.0 L 154.2 10.0 L 154.2 32.3 L 151.2 32.3 L 151.2 22.0 L 139.8 22.0 L 139.8 32.3 L 136.7 32.3 L 136.7 10.0 \" fill=\"#000000\"/>\n</svg>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from openff.interchange import Interchange"
      ],
      "metadata": {
        "id": "5-2RAwueN0DQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "inter = Interchange.from_smirnoff(force_field=ff, topology=top)"
      ],
      "metadata": {
        "id": "jarT_qXWN76B"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "inter.to_top(\"test.top\")"
      ],
      "metadata": {
        "id": "3lfNtlY_Oq6T"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "61TBk7goN61o"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "4PyU1Va5MXJK"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}