example_code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit.Chem import Draw\n",
    "from rdkit.Chem.Draw import IPythonConsole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "mol = Chem.MolFromSmiles('OC(=O)CCc1cc(c2ccccc2)c([nH]1)c3ccccc3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x11c3dfd50>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "aro_atoms = mol.GetAromaticAtoms()\n",
    "aro_idx = [a.GetIdx() for a in aro_atoms]\n",
    "atoms = mol.GetAtoms()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O 0 is not aromatic\n",
      "C 1 is not aromatic\n",
      "O 2 is not aromatic\n",
      "C 3 is not aromatic\n",
      "C 4 is not aromatic\n",
      "C 5 is aromatic\n",
      "C 6 is aromatic\n",
      "C 7 is aromatic\n",
      "C 8 is aromatic\n",
      "C 9 is aromatic\n",
      "C 10 is aromatic\n",
      "C 11 is aromatic\n",
      "C 12 is aromatic\n",
      "C 13 is aromatic\n",
      "C 14 is aromatic\n",
      "N 15 is aromatic\n",
      "C 16 is aromatic\n",
      "C 17 is aromatic\n",
      "C 18 is aromatic\n",
      "C 19 is aromatic\n",
      "C 20 is aromatic\n",
      "C 21 is aromatic\n"
     ]
    }
   ],
   "source": [
    "for atom in atoms:\n",
    "    symbol = atom.GetSymbol()\n",
    "    idx = atom.GetIdx()\n",
    "    if idx in aro_idx:\n",
    "        print(f'{symbol} {idx} is aromatic')\n",
    "    else:\n",
    "        print(f'{symbol} {idx} is not aromatic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = Chem.MolFromSmiles('OC(=O)CCc1cc(c2ccccc2)n(c1)c3ccccc3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x11c5e4c10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}