Bridged system stereochemistry issues

bridgedStereo.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:5d10ff0c6bff28663c00377e5d96a01e15f952364da6f7ade239f9655af6b8e4"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sys\n",
      "import rdkit\n",
      "from rdkit import Chem\n",
      "from rdkit.Chem import AllChem\n",
      "from rdkit.Chem.Draw import IPythonConsole"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "m = Chem.MolFromSmiles('CN1C(=O)[C@H]2[C@H](C1=O)[C@@]1(C)CC[C@H]2O1')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "m"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAcIAAACWCAYAAABNcIgQAAAenElEQVR4nO3de3xMd/7H8ddMSITI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\nIYQQbu3/Ae952IOVc6dCAAAAAElFTkSuQmCC\n",
       "prompt_number": 3,
       "text": [
        "<rdkit.Chem.rdchem.Mol at 0x2281a60>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Chem.FindMolChiralCenters(m)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "[(4, 'S'), (5, 'S'), (8, 'R'), (12, 'R')]"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mH = Chem.AddHs(m)\n",
      "list(AllChem.EmbedMultipleConfs(mH, 5))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "[]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for i in [8, 12]:\n",
      "    mFixed = Chem.Mol(m)\n",
      "    mFixed.GetAtomWithIdx(i).InvertChirality()\n",
      "    mFixedH = Chem.AddHs(mFixed)\n",
      "    print (list(AllChem.EmbedMultipleConfs(mFixedH, 5)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[0, 1, 2, 3, 4]\n",
        "[0, 1, 2, 3, 4]\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    }
   ],
   "metadata": {}
  }
 ]
}