jose-manuel/maybe_bug_murcko_drawing.ipynb

## maybe_bug_murcko_drawing.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Inconsistency with a molecule smiles and its drawing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import rdkit\n",
    "from rdkit import Chem\n",
    "from rdkit.Chem.MolStandardize.metal import MetalDisconnector\n",
    "from rdkit.Chem.MolStandardize.charge import Uncharger\n",
    "from rdkit.Chem.MolStandardize.normalize import Normalizer\n",
    "from rdkit.Chem.MolStandardize.tautomer import TautomerCanonicalizer\n",
    "from rdkit.Chem import rdmolops\n",
    "from rdkit.Chem.Scaffolds import MurckoScaffold\n",
    "from rdkit.Chem import Draw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Init"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def standardize(mol):\n",
    "    # disconnect metals\n",
    "    mol = metal_disconnector.disconnect(mol)\n",
    "    # remove isotopes\n",
    "    for a in mol.GetAtoms():\n",
    "        a.SetIsotope(0)\n",
    "    # normalize functional groups\n",
    "    mol = normalizer.normalize(mol)\n",
    "    # remove charges\n",
    "    mol = uncharger.uncharge(mol)\n",
    "    # enumerate canonical tautomer\n",
    "    mol = canonicalizer.canonicalize(mol)\n",
    "    # remove stereo\n",
    "    rdmolops.RemoveStereochemistry(mol)\n",
    "    \n",
    "    return mol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "metal_disconnector = MetalDisconnector()\n",
    "normalizer = Normalizer()\n",
    "uncharger = Uncharger()\n",
    "canonicalizer = TautomerCanonicalizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cn1cnc2c(NO)ncnc21\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=300x300 at 0x7F9AFE515400>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = Chem.MolFromSmiles('Cn1cnc2c(NO)ncnc21')\n",
    "print(Chem.MolToSmiles(m))\n",
    "Draw.MolToImage(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Without standardization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c1ncc2nc[nH]c2n1\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=300x300 at 0x7F9AFE52D7B8>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms = MurckoScaffold.GetScaffoldForMol(mol=m)\n",
    "print(Chem.MolToSmiles(ms))\n",
    "Draw.MolToImage(ms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c1ncc2nc[nH]c2n1\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=300x300 at 0x7F9AFE52DB38>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Chem.SanitizeMol(ms)\n",
    "print(Chem.MolToSmiles(ms))\n",
    "Draw.MolToImage(ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## With standardization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cn1cnc2c(=NO)[nH]cnc21\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=300x300 at 0x7F9AFE5155C0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_std = standardize(m)\n",
    "print(Chem.MolToSmiles(m_std))\n",
    "Draw.MolToImage(m_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N=c1[nH]cnc2[nH]cnc12\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=300x300 at 0x7F9AFE515828>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms = MurckoScaffold.GetScaffoldForMol(mol=m_std)\n",
    "print(Chem.MolToSmiles(ms))\n",
    "Draw.MolToImage(ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[N]=c1[nH]cnc2[nH]cnc12\n",
      "UnicodeEncodeError!\n"
     ]
    }
   ],
   "source": [
    "ms_all = Chem.Mol(ms)\n",
    "Chem.SanitizeMol(ms_all)\n",
    "print(Chem.MolToSmiles(ms_all))\n",
    "try:\n",
    "    Draw.MolToImage(ms_all)\n",
    "except UnicodeEncodeError:\n",
    "    print(\"UnicodeEncodeError!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All except FindRadicals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N=c1[nH]cnc2[nH]cnc12\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=300x300 at 0x7F9AFE52DD30>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "options = Chem.SANITIZE_ALL ^ Chem.SANITIZE_FINDRADICALS\n",
    "ms_norad = Chem.Mol(ms)\n",
    "Chem.SanitizeMol(ms_norad, options)\n",
    "print(Chem.MolToSmiles(ms_norad))\n",
    "Draw.MolToImage(ms_norad)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}