greglandrum/Adjust atom stereochemistry.ipynb

## Adjust atom stereochemistry.ipynb
{
  "cells": [
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "from rdkit import Chem\nimport sys",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": "RDKit WARNING: [09:18:08] Enabling RDKit 2020.03.1dev1 jupyter extensions\n",
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# there are faster ways to do this, but this is quick and easy. :-)\ndef is_cyclic_permutation(l1,l2):\n    l1 = ' '.join(str(x) for x in l1)\n    l2 = ' '.join(str(x) for x in l2)\n    l1 = l1+' '+l1\n    return l2 in l1\n\ndef switch_atom_stereo_if_necessary(atom):\n    nbrs = [(x.GetOtherAtomIdx(atom.GetIdx()),x.GetIdx()) for x in atom.GetBonds()]\n    bnds = [y for x,y in nbrs]\n    s_nbrs = sorted(nbrs)\n    s_bnds = [y for x,y in s_nbrs]\n    # if it's a cyclic permutation, we're done:\n    if is_cyclic_permutation(bnds,s_bnds):\n        return\n    # it was not a cyclic permutation, change the chiral flag\n    if atom.GetChiralTag()==Chem.ChiralType.CHI_TETRAHEDRAL_CCW:\n        atom.SetChiralTag(Chem.ChiralType.CHI_TETRAHEDRAL_CW)\n    elif atom.GetChiralTag()==Chem.ChiralType.CHI_TETRAHEDRAL_CW:\n        atom.SetChiralTag(Chem.ChiralType.CHI_TETRAHEDRAL_CCW)\n    \ndef update_all_atom_stereo(mol):\n    for atom in mol.GetAtoms():\n        if atom.GetChiralTag() in (Chem.ChiralType.CHI_TETRAHEDRAL_CCW,Chem.ChiralType.CHI_TETRAHEDRAL_CW):\n            switch_atom_stereo_if_necessary(atom)\n",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# create a molecule where the atom and bond orderings around the chiral center\n# are different from each other\nm = Chem.MolFromSmiles('CC123.F2.Cl1.Br3')\nm.Debug()\nm",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": "RDKit INFO: Atoms:\nRDKit INFO: \t0 6 C chg: 0  deg: 1 exp: 1 imp: 3 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t1 6 C chg: 0  deg: 4 exp: 4 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t2 9 F chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t3 17 Cl chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t4 35 Br chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: Bonds:\nRDKit INFO: \t0 0->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t1 3->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t2 2->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t3 4->1 order: 1 conj?: 0 aromatic?: 0\n",
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f04186b1a30>",
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# set a chiral flag based on \"atom order\": when looking down the C-C bond\n# the rotation direction between the F (atom 2) and the Cl (atom 3) should\n# be clockwise:\nm.GetAtomWithIdx(1).SetChiralTag(Chem.ChiralType.CHI_TETRAHEDRAL_CW)\nm.Debug()\nm",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": "RDKit INFO: Atoms:\nRDKit INFO: \t0 6 C chg: 0  deg: 1 exp: 1 imp: 3 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t1 6 C chg: 0  deg: 4 exp: 4 imp: 0 hyb: 4 arom?: 0 chi: 1\nRDKit INFO: \t2 9 F chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t3 17 Cl chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t4 35 Br chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: Bonds:\nRDKit INFO: \t0 0->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t1 3->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t2 2->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t3 4->1 order: 1 conj?: 0 aromatic?: 0\n",
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f04186b1a30>",
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# adjust the stereo using the bond order:\nupdate_all_atom_stereo(m)\nm.Debug()\nm",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": "RDKit INFO: Atoms:\nRDKit INFO: \t0 6 C chg: 0  deg: 1 exp: 1 imp: 3 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t1 6 C chg: 0  deg: 4 exp: 4 imp: 0 hyb: 4 arom?: 0 chi: 2\nRDKit INFO: \t2 9 F chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t3 17 Cl chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: \t4 35 Br chg: 0  deg: 1 exp: 1 imp: 0 hyb: 4 arom?: 0 chi: 0\nRDKit INFO: Bonds:\nRDKit INFO: \t0 0->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t1 3->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t2 2->1 order: 1 conj?: 0 aromatic?: 0\nRDKit INFO: \t3 4->1 order: 1 conj?: 0 aromatic?: 0\n",
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "execution_count": 5,
          "data": {
            "text/plain": "<rdkit.Chem.rdchem.Mol at 0x7f04186b1a30>",
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "gist": {
      "id": "",
      "data": {
        "description": "Notebooks/Adjust atom stereochemistry.ipynb",
        "public": true
      }
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "language_info": {
      "name": "python",
      "version": "3.7.3",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}