examples/diamond_light_source_covid19_candidates_retrosynthesis.ipynb

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   "source": [
    "# IBM RXN for Chemistry on COVID19 candidates\n",
    "\n",
    "An example usage of `rxn4chemistry` using the COVID19 candidates recently released [here](https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html) and hosted on Diamond Light Source [website](https://www.diamond.ac.uk/covid-19.html).\n",
    "In the following we will use `rxn4chemistry` for automated retrosynthesis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "!curl https://www.diamond.ac.uk/dam/jcr:db16b9c7-fff4-4cc1-bb40-d233c566ff31/Mpro%20full%20XChem%20screen%20-%20experiment%20summary%20-%20ver-2020-03-25-annotated.xlsx -o data.xlsx\n",
    "!ls *xlsx  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parse the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "data = pd.read_csv('data.xlsx').dropna(axis=0, how='all')\n",
    "data = data[~pd.isna(data['CompoundSMILES'])]\n",
    "code_to_smiles = {\n",
    "    code: smiles\n",
    "    for code, smiles in zip(data['CompoundCode'], data['CompoundSMILES'])\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Instantiate the wrapper\n",
    "\n",
    "Setup the wrapper using a valida API key. You can get one on the IBM RXN website from [here](https://rxn.res.ibm.com/rxn/user/profile)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rxn4chemistry import RXN4ChemistryWrapper\n",
    "api_key = 'API_KEY'\n",
    "rxn4chemistry_wrapper = RXN4ChemistryWrapper(api_key=api_key)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a project\n",
    "\n",
    "Create a project, you can easily check the identifier associated to it in the response."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = rxn4chemistry_wrapper.create_project('diamond_light_source_covid19_candidates')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can get your project id from the wrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rxn4chemistry_wrapper.project_id"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run  a retrosynthesis using the wrapper\n",
    "\n",
    "Running a retrosynthesis is as easy as picking a molecule and calling a one-liner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "compound = 'Z271004858'\n",
    "smiles = code_to_smiles[compound]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = rxn4chemistry_wrapper.predict_automatic_retrosynthesis(product=smiles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check the status and get the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rerun this until the status is 'SUCCESS', keep in mind the server allows only 5 requests per minute\n",
    "# and a timeout between consecutive requests of 2 seconds\n",
    "results = rxn4chemistry_wrapper.get_predict_automatic_retrosynthesis_results(response['prediction_id'])\n",
    "results['status']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inspect the predicted paths (upon 'SUCCESS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit.Chem import AllChem\n",
    "from IPython.display import display\n",
    "\n",
    "\n",
    "def collect_reactions(tree):\n",
    "    reactions = []\n",
    "    if 'children' in tree and len(tree['children']):\n",
    "        reactions.append(\n",
    "            AllChem.ReactionFromSmarts('{}>>{}'.format(\n",
    "                '.'.join([node['smiles'] for node in tree['children']]),\n",
    "                tree['smiles']\n",
    "            ), useSmiles=True)\n",
    "        )\n",
    "    for node in tree['children']:\n",
    "        reactions.extend(collect_reactions(node))\n",
    "    return reactions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "for index, path in enumerate(results['retrosynthetic_paths']):\n",
    "    print('Showing path {} with confidence {}:'.format(index, path['confidence']))\n",
    "    for reaction in collect_reactions(path):\n",
    "        display(Chem.Draw.ReactionToImage(reaction))"
   ]
  }
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