greglandrum/Github5634.ipynb

## Github5634.ipynb
{
  "cells": [
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2022-10-26T03:03:08.499660Z",
          "end_time": "2022-10-26T03:03:08.506312Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "from rdkit import Chem\nfrom rdkit.Chem.Draw import IPythonConsole\n\nmolecule = Chem.MolFromMolBlock(\"\"\"0121.cdx\n  ChemDraw04300520492D\n\n 12 13  0  0  0  0  0  0  0  0999 V2000\n   -0.9920    0.7219    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -0.9920   -0.1031    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -0.2775   -0.5156    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n    0.4369   -0.1031    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n    0.4369    0.7219    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -0.2775    1.1344    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -1.7065   -0.5156    0.0000 O   0  0  0  0  0  0  0  0  0  0  0  0\n    1.2216   -0.3581    0.0000 O   0  0  0  0  0  0  0  0  0  0  0  0\n    1.7065    0.3094    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n    1.2216    0.9768    0.0000 O   0  0  0  0  0  0  0  0  0  0  0  0\n   -0.6348   -0.7219    0.0000 O   0  0  0  0  0  0  0  0  0  0  0  0\n    0.0797   -1.1344    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n  1  2  4  0      \n  2  3  4  0      \n  3  4  4  0      \n  4  5  4  0      \n  5  6  4  0      \n  6  1  4  0      \n  2  7  1  0      \n  4  8  1  0      \n  8  9  1  0      \n  9 10  1  0      \n 10  5  1  0      \n  3 11  1  0      \n 11 12  1  0      \nM  STY  1   1 SUP\nM  SLB  1   1   1\nM  SAL   1  2  11  12\nM  SBL   1  1  12\nM  SMT   1 OCH3\nM  SBV   1 12   -2.4599    6.1489\nM  END\"\"\")\nmolecule",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 6,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f1f421b9340>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2022-10-26T03:03:13.982541Z",
          "end_time": "2022-10-26T03:03:13.991381Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "from rdkit.Chem import rdAbbreviations\nabbrmol = rdAbbreviations.CondenseAbbreviationSubstanceGroups(molecule)\nabbrmol",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 7,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f1f421b9400>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2022-10-26T03:04:09.944052Z",
          "end_time": "2022-10-26T03:04:09.951462Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "nmol = Chem.MolFromSmiles('c1ccccc1OC')\nnmol",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 8,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f1f431e2b80>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2022-10-26T03:04:42.497723Z",
          "end_time": "2022-10-26T03:04:42.503900Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "nmol2 = rdAbbreviations.CondenseMolAbbreviations(nmol,rdAbbreviations.GetDefaultAbbreviations())\nnmol2",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 9,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f1f421b9460>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
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          "start_time": "2022-10-26T03:04:58.939890Z",
          "end_time": "2022-10-26T03:04:58.942437Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "print(Chem.MolToMolBlock(nmol2))",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": "\n     RDKit          2D\n\n  7  7  0  0  0  0  0  0  0  0999 V2000\n    1.5000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n    0.7500   -1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -0.7500   -1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -1.5000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n   -0.7500    1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n    0.7500    1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n    1.5000    2.5981    0.0000 R   0  0  0  0  0  0  0  0  0  0  0  0\n  1  2  2  0\n  2  3  1  0\n  3  4  2  0\n  4  5  1  0\n  5  6  2  0\n  6  7  1  0\n  6  1  1  0\nM  END\n\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2022-10-26T03:06:20.684407Z",
          "end_time": "2022-10-26T03:06:20.687549Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "nmol2 = rdAbbreviations.LabelMolAbbreviations(nmol,rdAbbreviations.GetDefaultAbbreviations())\nprint(Chem.MolToV3KMolBlock(nmol2))",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": "\n     RDKit          2D\n\n  0  0  0  0  0  0  0  0  0  0999 V3000\nM  V30 BEGIN CTAB\nM  V30 COUNTS 8 8 1 0 0\nM  V30 BEGIN ATOM\nM  V30 1 C 1.500000 0.000000 0.000000 0\nM  V30 2 C 0.750000 -1.299038 0.000000 0\nM  V30 3 C -0.750000 -1.299038 0.000000 0\nM  V30 4 C -1.500000 0.000000 0.000000 0\nM  V30 5 C -0.750000 1.299038 0.000000 0\nM  V30 6 C 0.750000 1.299038 0.000000 0\nM  V30 7 O 1.500000 2.598076 0.000000 0\nM  V30 8 C 3.000000 2.598076 0.000000 0\nM  V30 END ATOM\nM  V30 BEGIN BOND\nM  V30 1 2 1 2\nM  V30 2 1 2 3\nM  V30 3 2 3 4\nM  V30 4 1 4 5\nM  V30 5 2 5 6\nM  V30 6 1 6 7\nM  V30 7 1 7 8\nM  V30 8 1 6 1\nM  V30 END BOND\nM  V30 BEGIN SGROUP\nM  V30 1 SUP 0 ATOMS=(2 7 8) XBONDS=(1 6) LABEL=OMe SAP=(3 7 6 1)\nM  V30 END SGROUP\nM  V30 END CTAB\nM  END\n\n",
          "name": "stdout"
        }
      ]
    },
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      "source": "",
      "execution_count": null,
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