github6118.ipynb

github6118.ipynb

{
  "cells": [
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2023-02-25T06:54:01.086170Z",
          "end_time": "2023-02-25T06:54:01.093866Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "from rdkit import Chem\nfrom rdkit.Chem import rdFMCS\nfrom rdkit.Chem.Draw import IPythonConsole\nfrom rdkit.Chem import Draw\nimport rdkit\nprint(rdkit.__version__)",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": "2022.09.4\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2023-02-25T06:54:55.124575Z",
          "end_time": "2023-02-25T06:54:55.140467Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "ms = [Chem.MolFromSmiles(smi) for smi in ('c1cccc2c1CCCC2','c1cccc2c1cccc2')]\nDraw.MolsToGridImage(ms)",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "image/png": "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\n",
            "text/plain": "<IPython.core.display.Image object>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Defaults:"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2023-02-25T06:55:30.199111Z",
          "end_time": "2023-02-25T06:55:30.208536Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "rdFMCS.FindMCS(ms).smartsString",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 5,
          "data": {
            "text/plain": "'[#6]1:[#6]:[#6]:[#6]:[#6]2:[#6]:1-,:[#6]-,:[#6]-,:[#6]-,:[#6]-,:2'"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Pay attention to atom aromaticity:"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2023-02-25T07:02:29.426230Z",
          "end_time": "2023-02-25T07:02:29.429928Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "class CompareAtomNumAndAromaticity(rdFMCS.MCSAtomCompare):\n    def __call__(self, p, mol1, atom1, mol2, atom2):\n        a1 = mol1.GetAtomWithIdx(atom1)\n        a2 = mol2.GetAtomWithIdx(atom2)\n        if a1.GetAtomicNum() != a2.GetAtomicNum():\n            return False\n        if a1.GetIsAromatic() != a2.GetIsAromatic():\n            return False\n        if (p.MatchChiralTag and not self.CheckAtomChirality(p, mol1, atom1, mol2, atom2)):\n            return False\n        if (p.MatchFormalCharge and not self.CheckAtomCharge(p, mol1, atom1, mol2, atom2)):\n            return False\n        if (p.RingMatchesRingOnly):\n            return self.CheckAtomRingMatch(p, mol1, atom1, mol2, atom2)\n        return True\n    ",
      "execution_count": 11,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2023-02-25T07:05:42.148711Z",
          "end_time": "2023-02-25T07:05:42.152163Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "ps = rdFMCS.MCSParameters()\nps.SetAtomTyper(CompareAtomNumAndAromaticity())\nmcs = rdFMCS.FindMCS(ms,ps)\nprint(mcs.smartsString)",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": "[#6]1:[#6]:[#6]:[#6]:[#6]:[#6]:1\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "If we want the aromaticity flags in the output, we need to match back to the molecule:"
    },
    {
      "metadata": {
        "ExecuteTime": {
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      "source": "match = ms[0].GetSubstructMatch(mcs.queryMol)\nChem.MolFragmentToSmiles(ms[0],match,allBondsExplicit=True)",
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        {
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            "text/plain": "'c1:c:c:c:c:c:1'"
          },
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