02_rdkit_intro.ipynb

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    "# apply Jupyter notebook style\n",
    "from IPython.core.display import HTML\n",
    "\n",
    "from custom.styles import style_string\n",
    "\n",
    "HTML(style_string)"
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   "cell_type": "markdown",
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    "<div style=\"text-align:center;\">\n",
    "  <img src=\"custom/molssi_main_horizontal.png\" style=\"display: block; margin: 0 auto; max-height:200px;\">\n",
    "</div>\n",
    "\n",
    "\n",
    "# Introduction to RDKit\n",
    "\n",
    "<div class=\"overview admonition\"> \n",
    "<p class=\"admonition-title\">Overview</p>\n",
    "\n",
    "Questions:\n",
    "\n",
    "* What is RDKit?\n",
    "\n",
    "* How can I get molecule information in Python?\n",
    "\n",
    "* What is a molecular descriptor?\n",
    "\n",
    "Objectives:\n",
    "\n",
    "* Use RDKit to create molecules in Python\n",
    "\n",
    "</div>\n",
    "\n",
    "There are Python libraries that are made for working just with chemical data. One commonly used library in Python for data science (or cheminformatics) is called [RDKit](https://en.wikipedia.org/wiki/RDKit). RDKit is an open-source cheminformatics library, primarily developed in C++, and was created by [Dr. Greg Landrum](https://scholar.google.com/citations?user=xr9paY0AAAAJ&hl=en) in 2006. We will be using the Python interface to RDKit, though there are interfaces in other languages.\n",
    "\n",
    "The primary goal of RDKit is to facilitate the manipulation of chemical structures, including reading and writing molecular file formats, calculating molecular properties, and performing substructure searches. In addition, it offers a wide range of cheminformatics algorithms such as molecular fingerprint generation, similarity metrics calculation, and molecular descriptor computation. This notebook introduces RDKit basis, but we will see more of all of these topics in later notebooks.\n",
    "\n",
    "<div class=\"tip admonition\"> \n",
    "<p class=\"admonition-title\">Python Objects</p>\n",
    "\n",
    "Most of this functionality is achieved through the RDKit `mol` object. In Python, we use the word \"object\" to refer to a variable type with associated data and methods. \n",
    "One example of an object we have seen in notebooks is a list - we could also call it a \"list object\". An object has `attributes` (data) and `methods`. \n",
    "You access information about objects with the syntax\n",
    "```python\n",
    "object.data\n",
    "```\n",
    "where data is the attribute name.\n",
    "\n",
    "You acceess object methods with the syntax\n",
    "```python\n",
    "object.method(arguments)\n",
    "```\n",
    "\n",
    "For example, for a list \"`append` is a method that was covered in the introductory lesson.\n",
    "\n",
    "```\n",
    "my_list = []\n",
    "my_list.append(1) # \"append\" is a method\n",
    "```\n",
    "</div>    \n",
    "\n",
    "In this lesson, we will create and manipulate RDKit `mol` objects. RDKit `mol` objects represent molecules and have\n",
    "attributes (data) and methods (actions) associated with molecules.\n",
    "\n",
    "We are going to use a part of RDKit called `Chem`. To use `Chem`, we first have to import it. "
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   "execution_count": 2,
   "id": "afc9bc63",
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   "source": [
    "from rdkit import Chem"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5b835ad",
   "metadata": {},
   "source": [
    "## Creating Molecules with RDKit\n",
    "\n",
    "To get information about molecules in RDKit, we have to first create objects representing molecules. RDKit has molecule object that can be used to retrieve information or calculate properties. To create a molecule object, we have to communicate the molecule identity in a way that computers understand. \n",
    "\n",
    "### Creating molecules using SMILES\n",
    "\n",
    "In the last lesson, we learned about molecular representations using SMILES strings. Now we will use SMILES strings to create molecule objects in RDKIT. \n",
    "\n",
    "We can create a representation of methane using RDKit by using the `MolFromSmiles` function in `rdkit.Chem`."
   ]
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   "id": "40b29a7c",
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   "source": [
    "methane = Chem.MolFromSmiles(\"C\")"
   ]
  },
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   "source": [
    "The `methane` variable is now an RDKit \"molecule object\".\n",
    "\n",
    "In a Jupyter environment, putting a variable that is an RDKit molecule as the only or last thing in a cell,\n",
    "will result in a picture of the molecule as an output."
   ]
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       "<rdkit.Chem.rdchem.Mol at 0x7f8d5567d1c0>"
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   ],
   "source": [
    "methane"
   ]
  },
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   "id": "e98c39d3",
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   "source": [
    "<div class=\"exercise admonition\">\n",
    "<p class=\"admonition-title\">Check Your Understanding</p>\n",
    "<p> Create RDKit molecules for the following molecules. You can look up the SMILES strings on <a href=\"https://pubchem.ncbi.nlm.nih.gov/\">PubChem</a>:\n",
    "<p>\n",
    "    <ul>\n",
    "        <li> Propane\n",
    "        <li> Ethene\n",
    "        <li> Cyclohexane\n",
    "        <li> Benzene\n",
    "    </ul>\n",
    "</p>\n",
    "<p>Create variables for each molecule. The variable names should be the molecule name (all lowercase)</p>\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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   "outputs": [],
   "source": [
    "# Your answers go here\n",
    "propane = Chem.MolFromSmiles(\"CCC\")\n",
    "ethene = Chem.MolFromSmiles(\"C=C\")\n",
    "cyclohexane = Chem.MolFromSmiles(\"C1CCCCC1\")\n",
    "benzene = Chem.MolFromSmiles(\"c1ccccc1\") # a lowercase c indicates an aromatic"
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
   "id": "395bc20c-bef9-4941-a2f8-fca830baae2b",
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    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d5567d4d0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Try visualizing your molecules here - you visualize a molecule as putting its variable name as the last thing in a cell\n",
    "propane"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e22a13a2-305e-458b-9caa-ba636b836e1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcIAAACWCAIAAADCEh9HAAAABmJLR0QA/wD/AP+gvaeTAAACdElEQVR4nO3ZwY2jQABFwfVqMrG4QS5k4CCIyBk4F3MjmN4ceEhotFX3L7ovT0j9GGP8AeCsv3cfAOB3k1GAREYBEhkFSGQUIJFRgERGARIZBUhkFCCRUYBERgESGQVIZBQgkVGAREYBEhkFSGQUIJFRgERGARIZBUhkFCCRUYBERgESGQVIZBQgkVGAREYBEhkFSGQUIJFRgERGARIZBUhkFCCRUYBERgESGQVIZBQgkVGAREYBEhkFSGQUIJFRgOSnjN/v9+fzueooALdY1/X1ep2ep4x+v18ZBX675/NZ5o8xxunxvu/HcZTPA9xumqZ5nk/PU0YB8MQEkMgoQCKjAImMAiQyCpDIKEAiowCJjAIkMgqQyChAIqMAiYwCJDIKkMgoQCKjAImMAiQyCpDIKEAiowCJjAIkMgqQyChAIqMAiYwCJDIKkMgoQCKjAImMAiQyCpDIKEAiowCJjAIkMgqQyChAIqMAiYwCJDIKkMgoQCKjAImMAiQyCpDIKEAiowCJjAIkMgqQyChAIqMAiYwCJDIKkMgoQCKjAImMAiQyCpDIKEAiowCJjAIkMgqQ/JTxvu/HcVx1FIBbTNM0z/P5/Qi2bbvuIgD32LatlDD9jS7Lsq7rVTcBuMWyLGX+GGNcdRSA/5AnJoBERgESGQVIZBQgkVGAREYBEhkFSGQUIJFRgERGARIZBUhkFCCRUYBERgESGQVIZBQgkVGAREYBEhkFSGQUIJFRgERGARIZBUhkFCCRUYBERgESGQVIZBQgkVGAREYBEhkFSGQUIJFRgERGARIZBUhkFCCRUYBERgESGQVIZBQgkVGAREYBkn89HqBN5/RT7wAAAFl6VFh0cmRraXRQS0wgcmRraXQgMjAyMy4wMy4yAAB4nHu/b+09BiDgZYAAJihmBOIGRjaGDCDNzMQEZ3AzMHIwiYBUiitBlcH0OewHalGBcB3sgewlIJYYANg8CHghkD36AAAAmHpUWHRNT0wgcmRraXQgMjAyMy4wMy4yAAB4nONSAIEgF+/MEgU4MHLh4lJQMMCDLC0tFcKMDQwMuHwVQAwFJ1d3Tz8F5xBHJ5iIs3+oX0iwgpGCIVAHEKKqdAzx94WJGCo4K+ga6JmbAs0DKtQzMEBjwBQaARXC1eniUejq54JiA8ROJ38/F4SdIIcZIWtAlgbxYZ4BsrkA5RU5IyVJP2sAAAAyelRYdFNNSUxFUyByZGtpdCAyMDIzLjAzLjIAAHicc7Z1VqjR0DXQMzfVMdCxhtKaNQBBuQU51OhF1AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d5567d2a0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Try visualizing your molecules here - you visualize a molecule as putting its variable name as the last thing in a cell\n",
    "ethene"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2fc9b578-6889-43d9-85c0-0f07111053b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d5567d3f0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Try visualizing your molecules here - you visualize a molecule as putting its variable name as the last thing in a cell\n",
    "cyclohexane"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0942cfe3-0ca2-4145-baaf-c7dff83fed24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d5567d540>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Try visualizing your molecules here - you visualize a molecule as putting its variable name as the last thing in a cell\n",
    "benzene"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95ad0cdb",
   "metadata": {},
   "source": [
    "## RDKit and Molecular Properties\n",
    "\n",
    "RDKit will allow us to access molecular properties of the molecules we've created.\n",
    "For example, we can have RDKit tell us the number of atoms in a molecule using the `GetNumAtoms` methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e045598b-847c-4d21-a336-f4b6cd7bf0b0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of atoms in methane is 1\n"
     ]
    }
   ],
   "source": [
    "num_methane = methane.GetNumAtoms()\n",
    "print(f\"The number of atoms in methane is {num_methane}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc5d6ee6",
   "metadata": {},
   "source": [
    "This isn't exactly what we expect. By default, RDKit only counts \"heavy atoms\". This means that hydrogen isn't included. We can tell RDKit to count hydrogens by adding `onlyExplicit=False` to our `GetNumAtoms` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3e94e9f4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of atoms in methane including hydrogens is 5.\n"
     ]
    }
   ],
   "source": [
    "num_methane_h = methane.GetNumAtoms(onlyExplicit=False)\n",
    "print(f\"The number of atoms in methane including hydrogens is {num_methane_h}.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e78625d",
   "metadata": {},
   "source": [
    "We can also get information about atoms or  bonds from RDKit molecules. We can use the `GetAtoms()` function, then use a loop to look at t`for` loop to look at the atoms. In the `for` loop, we can get information about each atom, like the atomic symbol or mass."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6bf913ea",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C 12.011\n",
      "C 12.011\n",
      "O 15.999\n"
     ]
    }
   ],
   "source": [
    "ethanol = Chem.MolFromSmiles(\"CCO\")\n",
    "\n",
    "for atom in ethanol.GetAtoms():\n",
    "    print(atom.GetSymbol(), atom.GetMass())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e14d40c2",
   "metadata": {},
   "source": [
    "Like the previous example, the molecule does not have hydrogens by default.\n",
    "If you need to work with the hydrogens, you can use a function to add them called `AddHs`.\n",
    "Now, when we look through the atoms, we get the hydrogens as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "107fe76e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d5567dd20>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ethanol_h = Chem.AddHs(ethanol)\n",
    "\n",
    "ethanol_h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a96a43e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C\n",
      "C\n",
      "O\n",
      "H\n",
      "H\n",
      "H\n",
      "H\n",
      "H\n",
      "H\n"
     ]
    }
   ],
   "source": [
    "for atom in ethanol_h.GetAtoms():\n",
    "    print(atom.GetSymbol())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6dc6fb9",
   "metadata": {},
   "source": [
    "You can use the `GetBonds` method to get the bonds in a molecule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "371244ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SINGLE\n",
      "SINGLE\n"
     ]
    }
   ],
   "source": [
    "for bond in ethanol.GetBonds():\n",
    "    print(bond.GetBondType())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e9469fa-d7c2-44e6-b83c-6f06946503ba",
   "metadata": {},
   "source": [
    "<div class=\"exercise admonition\">\n",
    "<p class=\"admonition-title\">Check Your Understanding</p>\n",
    "<p> Print atom and bond info for one or more of the molecules you created in the previous exercise. </p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7027bb2e-b388-4c5f-a055-27d989641d25",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C\n",
      "C\n",
      "C\n",
      "C\n",
      "C\n",
      "C\n"
     ]
    }
   ],
   "source": [
    "# print atom information for benzene\n",
    "\n",
    "for atom in benzene.GetAtoms():\n",
    "    print(atom.GetSymbol())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ec52c9cd-a5fa-44f6-9e68-f5b2086df591",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AROMATIC\n",
      "AROMATIC\n",
      "AROMATIC\n",
      "AROMATIC\n",
      "AROMATIC\n",
      "AROMATIC\n"
     ]
    }
   ],
   "source": [
    "# print bond information for benzene\n",
    "for bond in benzene.GetBonds():\n",
    "    print(bond.GetBondType())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b39599a7",
   "metadata": {},
   "source": [
    "## RDKit and Molecular Descriptors\n",
    "\n",
    "A molecular descriptor is a numerical value or a set of values that represent specific structural or chemical features of a molecule. Molecular descriptors are based on molecular structure and allow statistical analysis and similarity measurements on molecules.\n",
    "\n",
    "RDKit supports the calculation of many molecular descriptors. You can see a [full list of RDKit descriptors](https://www.rdkit.org/docs/GettingStartedInPython.html#list-of-available-descriptors) or [see the module documentation](https://www.rdkit.org/docs/source/rdkit.Chem.Descriptors.html).\n",
    "\n",
    "To get molecular descriptors from RDKit, we import the `Descriptors` module.\n",
    "\n",
    "```python\n",
    "from rdkit.Chem import Descriptors\n",
    "```\n",
    "\n",
    "To get a descriptor, you do\n",
    "\n",
    "```python\n",
    "Descriptors.descriptor_name(molecule_variable)\n",
    "\n",
    "```\n",
    "\n",
    "RDKit supports a number of molecular descriptors, a list of which is given below, along with the RDKit method for the property.\n",
    "\n",
    "\n",
    "Name of Property      | Name of RDKit Descriptor Function\n",
    "----------------------|-----------------------------------|\n",
    "molecular weight      | Descriptors.MolWt\n",
    "number of heavy atoms | Descriptors.HeavyAtomCount\n",
    "number of H-bond donors| Descriptors.NumHDonors\n",
    "number of H-bond donors| Descriptors.NumHAcceptors\n",
    "octanol-water partition coefficient| Descriptors.MolLogP\n",
    "topological polar surface area | Descriptors.TPSA\n",
    "number of rotatable bonds      | Descriptors.NumRotatableBonds\n",
    "number of aromatic rings       | Descriptors.NumAromaticRings\n",
    "number of aliphatic rings      | Descriptors.NumAliphaticRings\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3d8d3ac3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from rdkit.Chem import Descriptors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f3ed7282",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Printing info for methane:\n",
      "The molecular weight is 16.043\n",
      "The number of aromatic rings is 0\n"
     ]
    }
   ],
   "source": [
    "print(\"Printing info for methane:\")\n",
    "print(f\"The molecular weight is {Descriptors.MolWt(methane)}\")\n",
    "print(f\"The number of aromatic rings is {Descriptors.NumAromaticRings(methane)}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02f13392-9307-4398-8f31-c23b6f5faa60",
   "metadata": {},
   "source": [
    "<div class=\"exercise admonition\">\n",
    "<p class=\"admonition-title\">Check Your Understanding</p>\n",
    "    <p> Print molecular descriptors for some of the molecules you've created</p>\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "eb3aa2de-f22c-4408-addb-11a1417022eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The molecular weight is 78.11399999999999\n",
      "The number of aromatic rings is 1\n",
      "The topological polar surface area is 0.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"The molecular weight is {Descriptors.MolWt(benzene)}\")\n",
    "print(f\"The number of aromatic rings is {Descriptors.NumAromaticRings(benzene)}\")\n",
    "print(f\"The topological polar surface area is {Descriptors.TPSA(benzene)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "401eb6c2-179f-4e91-95cf-b9799dc66108",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6868227-ea3c-48dc-8759-1cd8db8830e2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5b9f1e8-469c-42db-b628-03b4c0bb0c1f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4143ac73-a5b6-419d-aa8f-692b33bb83ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8a5be400",
   "metadata": {},
   "source": [
    "## RDKit and Stereochemistry\n",
    "\n",
    "RDKit can be used to find chiral centers and print stereochemistry information about molecules. Consider 2-chlorobutane, created below.\n",
    "We are using a canonical SMILES which does not include stereo center information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f05c1617-9d2f-4f83-b151-2d15aa8168c3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d55707060>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chlorobutane = Chem.MolFromSmiles(\"CCC(C)Cl\")\n",
    "chlorobutane"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60375660-0e25-49ef-aa16-1c89637018f9",
   "metadata": {},
   "source": [
    "However, RDKit can analyze the molecule and tell us about the number of chiral centers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b091f596",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Can tell us how many stereocenters\n",
    "Chem.rdMolDescriptors.CalcNumAtomStereoCenters(chlorobutane)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d9c32b8-0ab1-4348-a5c3-6d81144706f7",
   "metadata": {},
   "source": [
    "We can also retrieve the atom indices of the chiral centers and see their orientation.\n",
    "If the orientation was not specified, RDKit will list it as `?`. \n",
    "We also have to tell RDKit to tell us about unassigned chiral centers using\n",
    "`includeUnassigned=True`.\n",
    "\"Unassigned\" refers to the fact that we have not specified the stereochemistry.\n",
    "\n",
    "We can get the atom index of the stereocenter using `FindMolChiralCenters`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9e2c4e5a-4f1b-4e88-aeaf-6b3585088e2b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(2, '?')]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Can tell us the atom number and the orientation.\n",
    "Chem.FindMolChiralCenters(chlorobutane, includeUnassigned=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea1457c4-0a0c-439f-aa99-a07e8cfea28e",
   "metadata": {},
   "source": [
    "### Visualizing Chiral Centers\n",
    "\n",
    "Although we can visualize molecules by making them the last thing in a cell, RDKit also allows us to make more complicated visualizations using its\n",
    "`Draw` module. To make the same visualization we did earlier we could do the following"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "decd78e2-c887-4240-a0cd-d77e965641fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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      "image/png": 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II0JAGBECwogQEEaEgDAiBIQRISCMCAFhRAgII0JAGBECwogQEEaEgDAiBIQRISCMCAFhRAgII0JAGBECwogQEEaEgDAiBIQRISCMCAFhRAgII0JAGBECwogQEEaEgDAiBIQRISCMCAFhRAgII0JAGBECwogQEEaEgDAiBIQRISCMCAFhRAgII0JAGBECwogQEEaEgDAiBIQRISCMCAFhRAgII0JAGBECwogQEPYvnquAjmboP8QAAAAASUVORK5CYII=",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from rdkit.Chem import Draw\n",
    "\n",
    "Draw.MolToImage(chlorobutane)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5203a6-338b-470c-82aa-3631551a4614",
   "metadata": {},
   "source": [
    "The `MolToImage` function can be used to highlight particular atoms. \n",
    "To highlight the chiral center in this molecule, we might first use\n",
    "`Chem.FindMolChiralCenters` to get the index of the chiral centers,\n",
    "then pass the atom indices of the chiral centers into `MolToImage`, as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bd9b2525-7250-4b11-a5bf-f862968f4b7a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(2, '?')]\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chiral_centers = Chem.FindMolChiralCenters(chlorobutane, includeUnassigned=True)\n",
    "print(chiral_centers)\n",
    "\n",
    "# We use 2 because that is the index of the chiral center.\n",
    "Draw.MolToImage(chlorobutane, highlightAtoms=[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da6a8dff-6d9d-4439-aca7-984e98fc365f",
   "metadata": {},
   "source": [
    "We could have also used Python instead of filling in the number.\n",
    "A `for` loop would make this more transferable between different atoms (hint for the next exercise!)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a19d0e2f-1d38-40e2-a3b2-cb69be0480bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chiral_centers = Chem.FindMolChiralCenters(chlorobutane, includeUnassigned=True)\n",
    "\n",
    "chiral_indices = []\n",
    "\n",
    "for center in chiral_centers:\n",
    "    chiral_indices.append(center[0])\n",
    "\n",
    "Draw.MolToImage(chlorobutane, highlightAtoms=chiral_indices)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9c43cdd-b9ca-49e1-8fd3-520bb4ed4aa2",
   "metadata": {},
   "source": [
    "<div class=\"exercise admonition\">\n",
    "<p class=\"admonition-title\">Exercise</p>\n",
    "    <p> Create a molecule using the SMILES string C1[C@@H](Cl)[C@H](Cl)CCC1. Print the stereochemistry information and\n",
    "        create a visualization highlighting the stereocenters.</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "23991157-3516-448f-8159-9d777beab358",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exercise_molecule = Chem.MolFromSmiles(\"C1[C@@H](Cl)[C@H](Cl)CCC1\")\n",
    "\n",
    "chiral_centers = Chem.FindMolChiralCenters(exercise_molecule, includeUnassigned=True)\n",
    "\n",
    "chiral_indices = []\n",
    "\n",
    "for center in chiral_centers:\n",
    "    chiral_indices.append(center[0])\n",
    "\n",
    "Draw.MolToImage(exercise_molecule, highlightAtoms=chiral_indices)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a398d681-9a75-4b7f-99d2-9dc60b74730b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f3019c1-fb23-40d5-953d-619534e17448",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31444b0f-a345-4b58-b720-6fcd6166f6bb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e976bbd5-a457-46cc-8196-d6da501b2aaf",
   "metadata": {},
   "source": [
    "## RDKit and Molecular Similarity\n",
    "\n",
    "### Substructure Searches\n",
    "\n",
    "RDKit can be used to search molecules for substructures. \n",
    "You can define your own substructures using SMILES. \n",
    "For example, we'll first look for carbons in caffeine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6da72486-c3b4-4bbe-9613-2985090d8b91",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d54ffe810>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "caffeine = Chem.MolFromSmiles('CN1C=NC2=C1C(=O)N(C(=O)N2C)C')\n",
    "carbon = Chem.MolFromSmiles('C')\n",
    "\n",
    "matches = caffeine.GetSubstructMatches(carbon)\n",
    "\n",
    "caffeine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3027482-0ffd-4124-9a07-d7a9fde69f77",
   "metadata": {},
   "source": [
    "In this example, you can see that all of the carbons are highlighted. \n",
    "\n",
    "The code `matches = caffeine.GetSubstructMatches(carbon)` will highlight all of the carbons in the caffeine molecule because it is searching for a specific substructure, which in this case is just a single carbon atom.\n",
    "\n",
    "But, what if we just wanted to highlight the methyl groups? We would have to use a different strategy for substructure matching.\n",
    "\n",
    "#### SMARTS Strings\n",
    "A [SMARTS (SMiles ARbitrary Target Specification)](https://en.wikipedia.org/wiki/SMILES_arbitrary_target_specification) string is a pattern-matching language for specifying substructures in molecules. It is similar to SMILES but has additional features for specifying atom and bond properties. In contrast to SMILES, SMARTS allows for specifying substructures based on patterns of atoms and bonds, rather than just specifying the exact arrangement of atoms and bonds in a molecule.\n",
    "\n",
    "In this case, we want to highlight the methyl group in caffeine, which contains a single carbon atom bonded to three hydrogen atoms. We can use a SMARTS string to define this substructure as `[CH3]`, which represents a carbon atom with three hydrogen atoms bonded to it.\n",
    "\n",
    "Using a SMARTS string is necessary in this case because simply searching for a single carbon atom with the code `carbon = Chem.MolFromSmiles('C')` would highlight all carbons in the molecule, not just the methyl group. By using a SMARTS string, we can specify the exact substructure we want to highlight and avoid highlighting unintended parts of the molecule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "65d9212b-1b66-4c23-8314-2b9b10c7b817",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d54ffeea0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "caffeine = Chem.MolFromSmiles('CN1C=NC2=C1C(=O)N(C(=O)N2C)C')\n",
    "methyl_pattern = Chem.MolFromSmarts('[CH3]')\n",
    "\n",
    "# Get the indices of the matching atoms\n",
    "matches = caffeine.GetSubstructMatches(methyl_pattern)\n",
    "caffeine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4d29c59-6587-4ad1-adba-907ff11c631a",
   "metadata": {},
   "source": [
    "You can see a list of SMARTS strings for different functional groups [at this link](https://www.daylight.com/dayhtml_tutorials/languages/smarts/smarts_examples.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4acb103b-f24b-4276-901b-a6f2e35e180b",
   "metadata": {},
   "source": [
    "<div class=\"exercise admonition\">\n",
    "<p class=\"admonition-title\">Exercise</p>\n",
    "    <p>Create an RDKit molecule object for aspirin (acetylsalicylic acid) using its SMILES string \"CC(=O)OC1=CC=CC=C1C(=O)O\".</p>\n",
    "    <p>Visualize the molecule, highlighting any carboxyl groups (COOH) in the structure. Use a SMARTS string to define the carboxyl group substructure.</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cde5bf62-668a-4141-a6b1-afb7a44e8ed8",
   "metadata": {},
   "outputs": [],
   "source": [
    "aspirin = Chem.MolFromSmiles(\"CC(=O)OC1=CC=CC=C1C(=O)O\")\n",
    "carboxyl_smarts = Chem.MolFromSmarts(\"[CX3]=[OX1]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "8aa2579f-2598-47a8-a277-c4274bd03c30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d54fff840>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches = aspirin.GetSubstructMatches(carboxyl_smarts)\n",
    "aspirin"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc1b8369-d480-4a64-8b57-04eedece3244",
   "metadata": {},
   "source": [
    "## Molecular Fingerprints\n",
    "\n",
    "Molecular fingerprinting is a method that represents the structure of a molecule in a way so that molecules may be compared. There are numerous molecular fingerprint algorithms that you might choose, each with their own strengths and weaknesses. You can see more information on fingerprinting in RDKit in [this presentation](https://www.rdkit.org/UGM/2012/Landrum_RDKit_UGM.Fingerprints.Final.pptx.pdf) or in the [RDKit documentation](https://www.rdkit.org/docs/GettingStartedInPython.html#fingerprinting-and-molecular-similarity).\n",
    "\n",
    "Let's see how we might use RDKit to compare some molecules using fingerprints.\n",
    "We already have aspirin defined. We will also create a molecule for salicylic acid and one for acetaminophen.\n",
    "Aspirin is derived from salicylic acid, so we would expect the structures to be similar.\n",
    "Acetaminophen is another molecule that is used as a pain reliever."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "124b129d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit import DataStructs\n",
    "from rdkit.Chem import Draw\n",
    "\n",
    "salicylic_acid_smiles = \" C1=CC=C(C(=C1)C(=O)O)O\"\n",
    "aspirin_smiles = \"CC(=O)OC1=CC=CC=C1C(=O)O\"\n",
    "acetaminophen_smiles = \"CC(=O)NC1=CC=C(C=C1)O\"\n",
    "\n",
    "aspirin = Chem.MolFromSmiles(aspirin_smiles)\n",
    "salicylic_acid = Chem.MolFromSmiles(salicylic_acid_smiles)\n",
    "acetaminophen = Chem.MolFromSmiles(acetaminophen_smiles)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "7c35dc81-ea82-471c-9d32-2b1480ed4dbc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d54a08b30>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salicylic_acid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "a3b49b61-4b82-4c52-9b6f-a87b96dd48ea",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YMACAm5vbjRs3mv+ooqIiPj5eIpFYWVlp91C5ublFR0c3nzy2wYkTJ9iTlnx9fauqqp4a5ubNm+35CGJgqEYN39ChQwFcvHiRfcjOT0UiEbepXujMmTP29vYAJkyYUFpa+qyn1dXVJSUlhYeHs4fym/fp+fPnX/ZDDxw4wC4MGhISUl9frx3/9ddf2TCenp5lZWVt/ErEQFGNGr6FCxcC+Oabb9iH7PzU3NxcOz/VQzKZzNLSEoBYLK6rq2vNS+rr69k+bX4CvIuLS2RkZEZGhkajac2bbNq0CU+cBJqUlMSGCQoKevDgQRu/EjFcVKOG76uvvgKwePFi7UiL+am+iY+PZ68Revvtt5VK5cu+XKVSZWRkREZG9u7dW9unzs7ObJ++8CT548ePN3+4Y8cOY2PjNochXQHVqOFjL0V3d3fXjoSHhwPYvHkzh6meZcOGDexNOFauXNnKKeSzaPu0T58+2j7t1atXeHh4UlJSaybjMTEx2jDtSUIMG9Wo4WtoaDAzMxMKhdXV1ezIk/NTfaDRaNibcBgZGW3atKkD31mtVp8/fz46Olq7qB17Nijbpw0NDU++RKVSffDBB2wY/fz3hugPqtEugV0hKS0tjX3IrvHh5ubGbarHKBRfffghAHNz83379nXe52RnZ0dHRw8fPlzbpzY2NhKJJD4+vra29mEWxdy5cwGYmZnx5cwwwiGq0S4hMjISwL///W/2YWNjo4WFhUAgqKys5DZYk6oqZsqUBlNTyaRJJ06c0M1nXrp0KTo6esSIEdo+7dat25w5c+Lj46dOncrW68mTJ3UThvAa1WiX8MMPPwAIDg7Wjnh6egI4evQoh6malJQwr73GAIyjI5OVpfvPz8/P37Bhg0gk0t4Y2cjIiE6wJ61HS5N0CS2WPW5oaOD8dkZN8vPh44OsLAwejIwMjBql+wiDBg368MMPMzMzCwoKvvjiCzs7O7VavX79+uYTVUKeg2q0Sxg8eLC9vX1JSUlcXJy1tXX37t3ZpZJOnTrFZazz5+HlhWvXMG4cTp/GK69wGQZwdnZesWIFe5ptYWEht2EIj1CNdgkCgWDcuHEAVqxYUVNTo1Qqs7KyAKSmpgYGBm7fvr28vFzXmdLS4OeHe/cwbRrS0tCrl64DPEOLlfYJeSGq0a6CvVZSo9EMHz48Ly9vy5YtAQEBQqHw0KFDERERvXv39vb2jo2NvX37ti7S7NoFf3/U1GDhQiQno9l1nJx78n7OhLwA1ztniS7ExsayS8xFRkY2v4ynrKzsWQsmXb16tbPSbNjACIUMwERGMvp34w2NRsNePt9iMRRCnoVq1MA95z5CzZWXl+/YsUMsFpubm7N9yu4HSN+0ienAPtVomJUrGYARCJj//KfD3rajzZo1C8DevXu5DkL4gWrUkCmVynfeeQdPu4/Qs7RYMOnuuHEMwLi5MStXMu1cpVipZCIiGIAxNWV27WrXW3Uy9qYgn3zyCddBCD9QjRqs+/fvs7MqKyur5OTkl335gwcPEhISVG+/zdjYMEDTn2HDmL//nWnNAnR1dUxBAfPwuiCGYZjGRsbfn+nWjUlJedkwOpaSkgLAx8eH6yCEHwQMw+h6dyzpfBUVFWKxWC6X29nZyWQyLy+vtr+XWo3TpyGVYu9eaO+FN2AAgoMhFsPXF8bGjz3/4kV8/DEyMqBWQyDAhAn4z3/g4wMAdXXIz4fen49ZUVFhb29vYWFRXV1t3OLbEfIkrnucdLzm9xHKy8vrsPdVqZiMDCYykunb99H81N6eCQ9nkpIYdsGk7GymWzcmIICRy5l795izZ5m5cxlT0/buENA5dhGTLC6uqiK8QzVqaJ51H6GOpFYzp04xUVHMwIGP+pS93VNAAOPhwTRfg06tZkQiZty4TknSaRYsWABgy5YtXAchPEDnjRqUEydOeHt7FxcXT5kyJTMzs2/fvp3yMUIhJk7E55+joADZ2YiOhqsrpk6FQoEjR/DmmzAxeezJb72Fc+dQUtIpYToHnT1KWo/2+xiOxMTE+fPnKxSKkJCQ3bt3a09d6lzu7nB3x+rVUCpRWIjGRgwa1PI5gwcDQH4+nJx0Eakj6MuaA4QPaDZqIDZt2hQWFqZQKJYtW7Zv3z4ddWhzJibQaADg4Zn8j5iZAYBKpetI7TBq1CgzM7M//vijpqaG6yxE31GNGoJ169YtW7aMYZjo6OivvvqKvWCJA46OEAhQVNRy/MYNAOjXT/eJ2szMzGzkyJEajebChQtcZyH6jmqU39Rq9fvvv79q1SojI6MtW7aw541zxtoaY8bgl19ajqemYuBAuLhwkantaPcoaSWqUR5raGiYN2/et99+a2lpmZiYuGTJEq4TAf/zP0hJQWwstOcj79yJXbvw6ad4uCgyX9BST6SV6PR7vqqsrJw9e3ZmZmbPnj1lMplIJOI60UNxcfj732FpiWHDcP06Kirwj3/gf/+XdzV69erVoUOHOjk56WjVK8JbVKO8dPv2bX9//0uXLvXp0yc1NVXv1mkvK8OJEygtRc+e8PWFoyPXgdqCYZhevXqVl5cXFRX149WOXaJjdMIT/+Tk5Pj7+9+8edPNzS01NbV///5cJ3qCvT3eeIPrEO3FrnGVmpp65swZqlHyHLRvlGfOnDkzefLkmzdvenp6pqen62OHGhDaPUpag2qUT2Qy2dSpU8vKyoKCgo4dO2ZnZ8d1IgNHB+tJa9C+Ud7YsWPHkiVLVCrV4sWLv/32W1p5SAfKy8t79eplaWlZVVVF/8HJs9BslB/WrVsXERGhUqlWrlz53Xff0a+0btjZ2bm4uNTV1eXk5HCdhegvqlF9p1ar//rXv65atUooFG7evDkmJobrRF0L7R4lL0Q1qu/i4uK+/vprc3NzqVS6dOlSruN0ObR7lLwQ1ai++8tf/hIUFHT48OGQkBCus3RFVKPkhegQEyHP09DQYG1trVQqq6qq2Nv8EdICzUYJeR4zM7MRI0ZoNJqLFy9ynYXoKapRQl6AtuvJ81GNEvICdLCePB/VKCEvwM5Gjx8/fv78ea6zEH1Eh5gIeQGGYezs7CorKwEMGDAgODhYLBb7+vrSRRCERTVKyIuJRCK5XG5tbV1dXc2OODk5hYSEhIaG+vr6GhkZcRuPcIs26gl5MYFAAMDV1TU7Ozs6Onro0KElJSVff/31tGnTHBwcFi1aJJPJGhoauI5JuEGzUUJeoKqqavz48deuXROLxT///DM7eOXKFalUKpVKtZfbW1paTp06VSKRhIaGduvWjbu8RNeoRgl5nlu3bvn5+eXl5dnb2+/Zs8fPz6/FE65cubJ///6EhITff/+dHbGysrqwZMmwCRMQEAA6Y78LoBol5Jlyc3Nff/31mzdvAhgyZMibb745d+5cV1fXpz65sLDw559/lkqlF8+evd+9u7CiAmZm8PFBYCDmz4eDg26zE92hGiXk6c6ePRsYGFhaWtq7d+/79+/X1dWx4yNGjAgNDQ0LC3vWLbDKiorsExKwfz9OnYJGAwAmJvD1RVgYgoPRu7fOvgLRDapRQp7iyJEjYWFhtbW1YrF4z549QqHwyJEjBw8ePHDgQGlpKfucQYMGicViiUQiEokET73vaXk5Dh2CVIrDh9HYCABCIby8IBYjLAyvvKLDL0Q6EdUoIS3t3Lnz3XffVSqVb7311tatW5ufH6pWq0+fPi2VSvfu3Xvnzh12sH///iEhIc87mbSyEjIZDh5EcjIezmrh5gaJBPPmYfjwTv9KpDNRjRLymNjY2BUrVjAMs3LlyrVr1z59mgmo1er09PSEhIQDBw7cunWLHXRyclq7ePFbU6di8mQ8tU9ranDoEBISkJyMBw+aBr//HgsXgmFw/DjkctTVoX9/BAZiwIBO+YakwzGEEIZhGEaj0XzyyScABALB559/3voXak8mBXBx8mQGYGxtmfBwJimJUSie/pr6eiYpiQkPZ2xsmKIiprKS8fVlzMyYSZMYiYQZMoQxNWViYzvmi5FORjVKCMMwTENDw7x58wCYmpru2bOnbW9y4cKF2n/9ixk+nAGa/lhbMwsWMPv3M3V1T3+NUskwDDNvHuPkxOTlNQ1qNMzatYxAwBw71rYkRJdoo54QoKamJDJy6I8/GllYJCYm+vr6tvcN8/Mhk0EqhVwO9lfMwgJ+fpBIEBQEa+vHnlxcDGdnfPMNlix5NMgwGD0a/fsjKam9YUgnoxolXd6dO5g1C1lZ+f7+tWvXjhw5siPfvLAQP//8WJ9qTyadN6/p5Kd9+yCRIDsb7u6PvXb5cvz4I8rKOjIP6QR0TT3p2vLzMWkSsrLg4uISF9fBHQpg4EB8+CEyM3HjBmJjMWkSVCocPYqPPkK/fli+HEBTUfbt2/K1/fqhoqLpzFOix6hGSRd2/jy8vHD1KsaNw+nTnXsiZ//+iIzEyZO4exfx8QgMhFAIJycAsLAAgIdrRz1SVQVzcwjpl1Tf0YKJpKtKS0NoKGpqMG0aEhJ0d/G7nR0WLcKiRaioaBphry798084Oz/2zLw8uLnpKBVpB/qHjnRJu3bB3x81NVi4EMnJ3CwgYmsLW1sAGDsWgwbh66/R/EDF9etIScHcuRwEIy+JDjGRric2FlFR0GgQGYkvv9SLreYjRxAYiOBgLFoEJydkZeGf/4S9PTIzYW7OdTjyAlSjpCthGKxZgzVrIBAgJgZ/+xvXgZr59Vd89hkyM3H/PpydIZHg00/RowfXsciLUY2SLkOlwvvv47vvYGqK7dvx5ptcByIGgmqUdBlBQUhKQvfu2L8f06dznYYYDj3YK0RIK9XV4fBhVFU9Nnj9OtLTHxtpaMCxY4iPx/79KCp6NB4RAQcHHD5MHUo6Fs1GCX/k5MDdHZmZEIkeDUZHY9s2FBc3PfzlF0REoKwMQ4fi7l2UlyMiAhs3wswMAOrqYGXFQXJi0Gg2SgzIH38gOBgzZ6KyEpcv4949pKTgp58QFdX0BOpQ0gmoRokBWb8ejo745htYWjaNzJiBf/wD//d/eLjEMiEdjmqUGJDjxzFlCkxMHhucNQtKJTIzOcpEDB9dDEr4JjgYpqaPHtbWPjq5sqTkKSvGs1dYlpToJBzpiqhGCd98+uljC8rt3Iljx5r+bmIChaLl89mR5s1LSIeiGiV8M3bsY0fqMzIe/d3FBQUFLZ9//ToADB7c+clIF0X7RokBEYuRmoqHN0BusnMn7Owea15COhTVKDEgUVGwsUFAADIzUV+PggKsWYNvvkFMTNOanoR0AtqoJwbE1hbp6Vi+HFOmQKUCAGdn7NiB8HCukxFDRlcxEV5pbISJCZrfO16thkbT8iSn2loUF6N7d/Trp+OApAuiGiWEkHahfaOEENIuVKOEENIuVKOEENIuVKOEENIuVKOEENIu/w9twwBWGJODmAAAARp6VFh0cmRraXRQS0wgcmRraXQgMjAyMy4wMy4yAAB4nHu/b+09BiDgZYAAJigbhBsY2RgSgDQjMxuDBpBmZuGA0Ewwms0BIs7mkAGimRnxMqBqMcwCK2Bk5GZgZGBk0mBiZFZgZlFgYc1gYmVLYGPPYGLnSODgzGDi5FLg4tZg4uJR4GRJEGEEamJj4eRgZ2MVXwZyJNQDDLx5f4oPPNi6ZD+I075d58AR3wn7QOyEEw4H7q+bbg9iTzi8aP/iNDuwGpFzivvK9rTagdjncz/uyzW8C1azOUbF/t1LPQcQ+00Oi8O/SEEw+0ithEPEY1+wmj2Fi+wl23zB5udOPmUvXHwVbGbZfAeHKk+OAyB2g9oHu4Nc2mC2GACIaUMiA+GQ1wAAAXR6VFh0TU9MIHJka2l0IDIwMjMuMDMuMgAAeJx9k1FuwyAMht9zCl+gyDYGm8e2qaZpaiJt3e6w991fs1N1pBIaxBGQDxt+OxNEe5/fvn/gr/E8TQD4z9Nag6+MiNMVYgCny8vrAufb8fRYOa+fy+0DKMeD0Z/Z4229PlYIznDIyYjZGA6U2Kqhb0m4tb6Xg+RUmyk6iU6SSR6QGdbwie4zIiSygiwDUAL0kEql5XCpkrWMyBLBMVExjDslrsQ4il3voLhLIY+tbKg0ANVBTFXcTQNOmjOyDThzjhPWRmI+8LMSjbi2cdm4avXPhsJlJCN5fvxcXBu2usmIqKgjkjayuEtXz3WqVYuO1CF2IV1wbH6NSBJxEysjMnLj8nh0kS2dyiWP9Lks81Oh3EvntC5zL53o3Osjeu5F4N9AeqrJrfR8+gRqz5q4ac+NuFlPgbi1rrS40V5R2l60U47jRbxTiLaVvFNCYlfZX3h/vZg//iofT78xK6/C2aeMsgAAAL16VFh0U01JTEVTIHJka2l0IDIwMjMuMDMuMgAAeJwljssNAlEIRVtxqQlD+MPLxNUUYBG2YfHep+w4HOBe1/35erze+t6l/+72uR/Oo2ZDh7JNDZ2Hca1pOgRAJxzIWSA5KeukGAjs1lzb6vDOABPWHFEnbJaa+I8FvFCsto00ncIVmC0ybvctGUstTQDcVNvAx5BFeCQs6cQ3GL9IIr2vKCcU27GrOkGQUVY7Ib/aitmfopZEbFRt6fT4fAGjlzXsNvV9FgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d54a08a50>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aspirin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f9c7e8c9-9069-4097-b09e-f7efbd6f2f21",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f8d54a08ba0>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "acetaminophen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e56c6c8-1163-4005-8b4a-d5c48b6509bf",
   "metadata": {},
   "source": [
    "From inspecting these molecules visually, we can see that aspirin and salicylic acid look more similar than aspirin and acetaminophen. \n",
    "We will see this next using a molecular fingerprint.\n",
    "\n",
    "We will use the `Chem.RDKFingerprint`, which is an RDKit specific fingerprint, though there are other options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "864cf1eb-7eca-4b71-a490-53078492a83c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "acetaminophen_fp = Chem.RDKFingerprint(acetaminophen)\n",
    "aspirin_fp = Chem.RDKFingerprint(aspirin)\n",
    "salicylic_acid_fp = Chem.RDKFingerprint(salicylic_acid)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90af75ae-ae6c-4513-842f-3e3ec76cb033",
   "metadata": {},
   "source": [
    "To calculate the similarity between molecular fingerprints, a measure called the Tanimoto similarity is often used. \n",
    "This number ranges from 0 to 1.\n",
    "A higher number means that molecules are more similar. For example, the similarity of a molecule with itself would be 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "927f103e-b65e-464c-b5b4-54b641b92fa2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5621468926553672\n"
     ]
    }
   ],
   "source": [
    "similarity = DataStructs.TanimotoSimilarity(aspirin_fp, salicylic_acid_fp)\n",
    "print(similarity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c2792e17-a2b3-430c-8dd1-b79d283bd5b4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.15486725663716813\n"
     ]
    }
   ],
   "source": [
    "similarity = DataStructs.TanimotoSimilarity(aspirin_fp, acetaminophen_fp)\n",
    "print(similarity)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc73d27a-f9ea-4595-a5db-66704918354e",
   "metadata": {},
   "source": [
    "As expected, our similarity scores indicate that aspirin and salicylic acid are more similar than aspirin and acetaminophen. \n",
    "This starts being more useful when working with larger data sets."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28a48040-bb26-44b1-b119-c51b9de140b4",
   "metadata": {
    "tags": []
   },
   "source": [
    "<div class=\"exercise admonition\">\n",
    "<p class=\"admonition-title\">Final Challenge</p>\n",
    "\n",
    "<p> For the following sets of molecules, generate the RDKit molecule using a SMILES string (you can find this on PubChem).\n",
    "    Identify which molecules contain an amine group and which contain a phenyl group. Finally, use fingerprints to compute\n",
    "    the similarity between a few of the molecules.</p>\n",
    "\n",
    "<ul>\n",
    "<li>Neurotransmitters:</li>\n",
    "    <ul>\n",
    "        <li> Dopamine </li>\n",
    "        <li> Serotonin </li>\n",
    "        <li> Norephinephrine </li>\n",
    "    </ul>\n",
    "<li>Hormones:</li>\n",
    "    <ul>\n",
    "        <li> Cortisol </li>\n",
    "        <li> Testosterone </li>\n",
    "        <li> Estradiol </li>\n",
    "    </ul>\n",
    "<ul>\n",
    "\n",
    "</div>\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c10a9ee8-f382-4f2b-a98f-4aadf16959b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Amine found in dopamine\n",
      "Phenyl found in dopamine\n",
      "Amine found in seratonin\n",
      "Phenyl found in seratonin\n",
      "Amine found in norephinephrine\n",
      "Phenyl found in norephinephrine\n"
     ]
    }
   ],
   "source": [
    "molecule_names = [\"dopamine\", \"seratonin\", \"norephinephrine\", \"cortisol\"]\n",
    "molecule_smiles = [\"C1=CC(=C(C=C1CCN)O)O\", \n",
    "                   \"C1=CC2=C(C=C1O)C(=CN2)CCN\", \n",
    "                   \"C1=CC(=C(C=C1C(CN)O)O)O\",\n",
    "                   \"CC12CCC(=O)C=C1CCC3C2C(CC4(C3CCC4(C(=O)CO)O)C)O\"\n",
    "                  ]\n",
    "amine_pattern = Chem.MolFromSmarts(\"[NX3;H2,H1;!$(NC=O)]\")\n",
    "phenyl_pattern = Chem.MolFromSmarts(\"c1ccccc1\")\n",
    "\n",
    "num_molecules = len(molecule_names)\n",
    "\n",
    "mol_objects = []\n",
    "\n",
    "for i in range(num_molecules):\n",
    "    \n",
    "    mol_object = Chem.MolFromSmiles(molecule_smiles[i])\n",
    "    mol_objects.append(mol_object)\n",
    "    \n",
    "    amine_matches = mol_object.GetSubstructMatches(amine_pattern)\n",
    "    phenyl_matches = mol_object.GetSubstructMatches(phenyl_pattern)\n",
    "    \n",
    "    if len(amine_matches) > 0:\n",
    "        print(f\"Amine found in {molecule_names[i]}\")\n",
    "        \n",
    "    if len(phenyl_matches) > 0:\n",
    "        print(f\"Phenyl found in {molecule_names[i]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ab3e4281-0a43-4b52-9232-1994b2730070",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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