{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Virtual Screening"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Objectives"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Perform virtual screening against PubChem using ligand-based approach\n",
"- Apply filters to prioritize virtual screening hit list.\n",
"- Learn how to use pandas' data frame."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this notebook, we perform virtual screening against PubChem using a set of known ligands for muscle glycogen phosphorylase. Compound filters will be applied to identify drug-like compounds and unique structures in terms of canonical SMILES will be selected to remove redundant structures. For some top-ranked compounds in the list, their binding mode will be predicted using molecular docking (which will be covered in a separate assignment)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Read known ligands from a file."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As a starting point, let's download a set of known ligands against muscle glycogen phosphorylase. These data are obtained from the DUD-E (Directory of Useful Decoys, Enhanced) data sets (http://dude.docking.org/), which contain known actives and inactives for 102 protein targets. The DUD-E sets are widely used in benchmarking studies that compare the performance of different virtual screening approaches (https://doi.org/10.1021/jm300687e)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Go to the DUD-E target page (http://dude.docking.org/targets) and find muscle glycogen phosphorylase (Target Name: PYGM, PDB ID: 1c8k) from the target list. Clicking the target name \"PYGM\" directs you to the page that lists various files (http://dude.docking.org/targets/pygm). Download file \"**actives_final.ism**\", which contains the SMILES strings of known actives. Rename the file name as \"**pygm_1c8k_actives.ism**\". \\[Open the file in WordPad or other text viewer/editor to check the format of this file\\]."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now read the data from the file using the pandas library (https://pandas.pydata.org/). Please go through some tutorials available at https://pandas.pydata.org/pandas-docs/version/0.15/tutorials.html"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" smiles | \n",
" dat | \n",
" id | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" c1ccc2cc(c(cc2c1)NC(=O)c3cc(ccn3)N(=O)=O)Oc4cc... | \n",
" 220668 | \n",
" CHEMBL134802 | \n",
"
\n",
" \n",
" 1 | \n",
" CC1=C(C(C(=C(N1Cc2ccc(cc2)Cl)C(=O)O)C(=O)O)c3c... | \n",
" 189331 | \n",
" CHEMBL115651 | \n",
"
\n",
" \n",
" 2 | \n",
" CCN1C(=C(C(C(=C1C(=O)O)C(=O)O)c2ccccc2Cl)C(=O)... | \n",
" 188996 | \n",
" CHEMBL113736 | \n",
"
\n",
" \n",
" 3 | \n",
" c1cc(c(c(c1)F)NC(=O)c2cc(ccn2)N(=O)=O)Oc3ccc(c... | \n",
" 219845 | \n",
" CHEMBL133911 | \n",
"
\n",
" \n",
" 4 | \n",
" CC1=C(C(C(=C(N1Cc2cccc(c2)N(=O)=O)C(=O)O)C(=O)... | \n",
" 189034 | \n",
" CHEMBL423509 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" smiles dat id\n",
"0 c1ccc2cc(c(cc2c1)NC(=O)c3cc(ccn3)N(=O)=O)Oc4cc... 220668 CHEMBL134802\n",
"1 CC1=C(C(C(=C(N1Cc2ccc(cc2)Cl)C(=O)O)C(=O)O)c3c... 189331 CHEMBL115651\n",
"2 CCN1C(=C(C(C(=C1C(=O)O)C(=O)O)c2ccccc2Cl)C(=O)... 188996 CHEMBL113736\n",
"3 c1cc(c(c(c1)F)NC(=O)c2cc(ccn2)N(=O)=O)Oc3ccc(c... 219845 CHEMBL133911\n",
"4 CC1=C(C(C(=C(N1Cc2cccc(c2)N(=O)=O)C(=O)O)C(=O)... 189034 CHEMBL423509"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"colnames = ['smiles','dat', 'id']\n",
"df_act = pd.read_csv(\"pygm_1c8k_actives.ism\", sep=\" \", names=colnames)\n",
"df_act.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"77\n"
]
}
],
"source": [
"print(len(df_act)) # Show how many structures are in the \"data frame\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Similarity Search against PubChem"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, let's perform similarity search against PubChem using each known active compound as a query. There are a few things to mention in this step:\n",
"\n",
"- The isomeric SMILES string is available for each query compound. This string will be used to specify the input structure, so HTTP POST should be used. (Please review lecture02-structure-inputs.ipynb)\n",
"\n",
"- During PubChem's similarity search, molecular similarity is evaluated using the **PubChem fingerprints** and **Tanimoto** coefficient. By default, similarity search will return compounds with Tanimoter scores of **0.9 or higher**. While we will use the default threshold in this practice, it is noteworthy that it is adjustable. If you use a higher threshold (e.g., 0.99), you will get a fewer hits, which are too similar to the query compounds. If you use a lower threshold (e.g., 0.88), you will get more hits, but they will include more false positives.\n",
"\n",
"- PubChem's similarity search does **not** return the similarity scores between the query and hit compounds. Only the hit compound list is returned, which makes it difficult to rank the hit compounds for compound selection. To address this issue, for each hit compound, we compute **the number of query compounds that returned that compound as a hit.** \\[Because we are using multiple query compounds for similarity search, it is possible for different query compounds to return the same compound as a hit. That is, the hit compound may be similar to multiple query compounds. The underlying assumption is that hit compounds returned multiple times from different queries are more likely to be active than those returned only once from a single query.\\]\n",
"\n",
"- Add \"time.sleep()\" to avoid overloading PubChem servers and getting blocked."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"smiles_act = df_act.smiles.to_list()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import time\n",
"import requests\n",
"\n",
"prolog = \"https://pubchem.ncbi.nlm.nih.gov/rest/pug\"\n",
"\n",
"cids_hit = dict()\n",
"\n",
"for idx, mysmiles in enumerate(smiles_act) :\n",
" \n",
" mydata = { 'smiles' : mysmiles }\n",
" \n",
" url = prolog + \"/compound/fastsimilarity_2d/smiles/cids/txt\"\n",
" res = requests.post(url, data=mydata)\n",
"\n",
" if ( res.status_code == 200 ) :\n",
" cids = res.text.split()\n",
" cids = [ int(x) for x in cids ] # Convert CIDs from string to integer.\n",
" else :\n",
" print(\"Error at\", idx, \":\", df_act.loc[idx,'id'], mysmiles )\n",
" print(res.status_code)\n",
" print(res.content)\n",
" \n",
" for mycid in cids:\n",
" cids_hit[mycid] = cids_hit.get(mycid, 0) + 1\n",
" \n",
" time.sleep(0.2)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23981"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cids_hit) # Show the number of compounds returned from any query."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the above code cells, the returned hits are stored in a dictionary, along with the number of times they are returned. Let's print the top 10 compounds that are returned the most number of times from the search."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 (16, 44354348)\n",
"1 (15, 44354370)\n",
"2 (15, 44354349)\n",
"3 (15, 44354322)\n",
"4 (13, 44357907)\n",
"5 (12, 44357938)\n",
"6 (12, 44357937)\n",
"7 (12, 44354455)\n",
"8 (12, 44354454)\n",
"9 (12, 44354362)\n"
]
}
],
"source": [
"sorted_by_freq = [ (v, k) for k, v in cids_hit.items() ]\n",
"sorted_by_freq.sort(reverse=True)\n",
"\n",
"for v, k in enumerate(sorted_by_freq) :\n",
"\n",
" if v == 10 : \n",
" break\n",
" \n",
" print(v, k) # Print (frequency, CID)\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Exclude the query compounds from the hits"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the previous step, we repeated similarity searches using multiple query molecules. This may result in a query molecule being returned as a hit from similarity search using another query molecule. Therefore, we want to check if the hit compound list has any query compounds and if any, we want to remove them. Below, we search PubChem for compounds identical to the query molecules and remove them from the hit compound list.\n",
"Note that the identity_type parameter in the PUG-REST request is set to \"**same_connectivity**\", which will return compounds with the same connectivity with the query molecule (ignoring stereochemistry and isotope information). The default for this parameter is \"same_stereo_isotope\", which returns compounds with the same stereochemistry AND isotope information."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"cids_query = dict()\n",
"\n",
"for idx, mysmiles in enumerate(smiles_act) :\n",
" \n",
" mydata = { 'smiles' : mysmiles }\n",
" url = prolog + \"/compound/fastidentity/smiles/cids/txt?identity_type=same_connectivity\"\n",
" res = requests.post(url, data=mydata)\n",
"\n",
" if ( res.status_code == 200 ) :\n",
" cids = res.text.split()\n",
" cids = [ int(x) for x in cids]\n",
" else :\n",
" print(\"Error at\", idx, \":\", df_act.loc[idx,'id'], mysmiles )\n",
" print(res.status_code)\n",
" print(res.content)\n",
" \n",
" for mycid in cids:\n",
" cids_query[mycid] = cids_query.get(mycid, 0) + 1\n",
" \n",
" time.sleep(0.2)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"133"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cids_query.keys()) # Show the number of CIDs that represent the query compounds."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now remove the query compounds from the hit list (if they are found in the list)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"for mycid in cids_query.keys() :\n",
" \n",
" cids_hit.pop(mycid, None)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23848"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cids_hit)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Print the top 10 compounds in the current hit list and compare them with the old ones."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 (12, 11779854)\n",
"1 (11, 118078858)\n",
"2 (11, 93077065)\n",
"3 (11, 93077064)\n",
"4 (11, 53013349)\n",
"5 (11, 51808718)\n",
"6 (11, 45369696)\n",
"7 (11, 17600716)\n",
"8 (10, 131851009)\n",
"9 (10, 129567524)\n"
]
}
],
"source": [
"sorted_by_freq = [ (v, k) for k, v in cids_hit.items() ]\n",
"sorted_by_freq.sort(reverse=True)\n",
"\n",
"for v, k in enumerate(sorted_by_freq) :\n",
" \n",
" if v == 10 : \n",
" break\n",
" \n",
" print(v, k) # Print (frequency, CID)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Filtering out non-drug-like compounds"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this step, non-drug-like compounds are filtered out from the list. To do that, four molecular properties are downloaded from PubChem and stored in CSV."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"# Number of chunks: 239\n",
"0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 "
]
}
],
"source": [
"chunk_size = 100\n",
"\n",
"if ( len(cids_hit) % chunk_size == 0 ) :\n",
" num_chunks = len(cids_hit) // chunk_size \n",
"else :\n",
" num_chunks = len(cids_hit) // chunk_size + 1\n",
"\n",
"cids_list = list(cids_hit.keys())\n",
" \n",
"print(\"# Number of chunks:\", num_chunks )\n",
"\n",
"csv = \"\" #sets a variable called csv to save the comma separated output\n",
"\n",
"for i in range(num_chunks) :\n",
" \n",
" print(i, end=\" \")\n",
" \n",
" idx1 = chunk_size * i\n",
" idx2 = chunk_size * (i + 1)\n",
"\n",
" cids_str = \",\".join([ str(x) for x in cids_list[idx1:idx2] ]) # build pug input for chunks of data\n",
" url = prolog + \"/compound/cid/\" + cids_str + \"/property/HBondDonorCount,HBondAcceptorCount,MolecularWeight,XLogP,CanonicalSMILES,IsomericSMILES/csv\"\n",
" \n",
" res = requests.get(url)\n",
" \n",
" if ( i == 0 ) : # if this is the first request, store result in empty csv variable\n",
" csv = res.text \n",
" else : # if this is a subsequent request, add the request to the csv variable adding a new line between chunks\n",
" csv = csv + \"\\n\".join(res.text.split()[1:]) + \"\\n\" \n",
" \n",
" time.sleep(0.2)\n",
"\n",
"#print(csv)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Downloaded data (in CSV) are loaded into a pandas data frame."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(23848, 7)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from io import StringIO\n",
"\n",
"csv_file = StringIO(csv)\n",
"\n",
"df_raw = pd.read_csv(csv_file, sep=\",\")\n",
"\n",
"df_raw.shape # Show the shape (dimesnion) of the data frame"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" HBondDonorCount | \n",
" HBondAcceptorCount | \n",
" MolecularWeight | \n",
" XLogP | \n",
" CanonicalSMILES | \n",
" IsomericSMILES | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 1731763 | \n",
" 0 | \n",
" 5 | \n",
" 454.0 | \n",
" 5.5 | \n",
" CCOC(=O)C1=C(N(C(=C(C1C2=CC=C(C=C2)Cl)C(=O)OCC... | \n",
" CCOC(=O)C1=C(N(C(=C(C1C2=CC=C(C=C2)Cl)C(=O)OCC... | \n",
"
\n",
" \n",
" 1 | \n",
" 21795259 | \n",
" 0 | \n",
" 5 | \n",
" 454.0 | \n",
" 5.5 | \n",
" CCOC(=O)C1=C(N(C(=C(C1C2=CC=CC=C2Cl)C(=O)OCC)C... | \n",
" CCOC(=O)C1=C(N(C(=C(C1C2=CC=CC=C2Cl)C(=O)OCC)C... | \n",
"
\n",
" \n",
" 2 | \n",
" 9910160 | \n",
" 3 | \n",
" 4 | \n",
" 422.9 | \n",
" 4.4 | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
"
\n",
" \n",
" 3 | \n",
" 70157737 | \n",
" 2 | \n",
" 4 | \n",
" 436.9 | \n",
" 4.6 | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
"
\n",
" \n",
" 4 | \n",
" 70074958 | \n",
" 2 | \n",
" 6 | \n",
" 448.9 | \n",
" 3.9 | \n",
" CC1=C(C(C(=C(N1)C)C(=O)OC)C2=CC=CC=C2Cl)C(=O)N... | \n",
" CC1=C([C@@H](C(=C(N1)C)C(=O)OC)C2=CC=CC=C2Cl)C... | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID HBondDonorCount HBondAcceptorCount MolecularWeight XLogP \\\n",
"0 1731763 0 5 454.0 5.5 \n",
"1 21795259 0 5 454.0 5.5 \n",
"2 9910160 3 4 422.9 4.4 \n",
"3 70157737 2 4 436.9 4.6 \n",
"4 70074958 2 6 448.9 3.9 \n",
"\n",
" CanonicalSMILES \\\n",
"0 CCOC(=O)C1=C(N(C(=C(C1C2=CC=C(C=C2)Cl)C(=O)OCC... \n",
"1 CCOC(=O)C1=C(N(C(=C(C1C2=CC=CC=C2Cl)C(=O)OCC)C... \n",
"2 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"3 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"4 CC1=C(C(C(=C(N1)C)C(=O)OC)C2=CC=CC=C2Cl)C(=O)N... \n",
"\n",
" IsomericSMILES \n",
"0 CCOC(=O)C1=C(N(C(=C(C1C2=CC=C(C=C2)Cl)C(=O)OCC... \n",
"1 CCOC(=O)C1=C(N(C(=C(C1C2=CC=CC=C2Cl)C(=O)OCC)C... \n",
"2 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"3 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"4 CC1=C([C@@H](C(=C(N1)C)C(=O)OC)C2=CC=CC=C2Cl)C... "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_raw.head(5) # Show the first 5 rows of the data frame"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that some compounds do not have computed XLogP values (because XLogP algorithm cannot handle inorganic compounds, salts, and mixtures) and we want to remove them."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"CID 0\n",
"HBondDonorCount 0\n",
"HBondAcceptorCount 0\n",
"MolecularWeight 0\n",
"XLogP 477\n",
"CanonicalSMILES 0\n",
"IsomericSMILES 0\n",
"dtype: int64"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_raw.isna().sum() # Check if there are any NULL values."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23848"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df_raw) # Check the number of rows (which is equals to the number of CIDs)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For convenience, add the information contained in the **cids_hit** dictionary to this data frame"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" HitFreq | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 1731763 | \n",
" 2 | \n",
"
\n",
" \n",
" 1 | \n",
" 21795259 | \n",
" 4 | \n",
"
\n",
" \n",
" 2 | \n",
" 9910160 | \n",
" 3 | \n",
"
\n",
" \n",
" 3 | \n",
" 70157737 | \n",
" 3 | \n",
"
\n",
" \n",
" 4 | \n",
" 70074958 | \n",
" 3 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID HitFreq\n",
"0 1731763 2\n",
"1 21795259 4\n",
"2 9910160 3\n",
"3 70157737 3\n",
"4 70074958 3"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# First load the cids_hit dictionary into a data frame.\n",
"df_freq = pd.DataFrame( cids_hit.items(), columns=['CID','HitFreq'])\n",
"df_freq.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" HitFreq | \n",
"
\n",
" \n",
" \n",
" \n",
" 1022 | \n",
" 11779854 | \n",
" 12 | \n",
"
\n",
" \n",
" 372 | \n",
" 118078858 | \n",
" 11 | \n",
"
\n",
" \n",
" 2631 | \n",
" 93077065 | \n",
" 11 | \n",
"
\n",
" \n",
" 2630 | \n",
" 93077064 | \n",
" 11 | \n",
"
\n",
" \n",
" 1983 | \n",
" 53013349 | \n",
" 11 | \n",
"
\n",
" \n",
" 1941 | \n",
" 51808718 | \n",
" 11 | \n",
"
\n",
" \n",
" 1707 | \n",
" 45369696 | \n",
" 11 | \n",
"
\n",
" \n",
" 1467 | \n",
" 17600716 | \n",
" 11 | \n",
"
\n",
" \n",
" 3072 | \n",
" 131851009 | \n",
" 10 | \n",
"
\n",
" \n",
" 3067 | \n",
" 129567524 | \n",
" 10 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID HitFreq\n",
"1022 11779854 12\n",
"372 118078858 11\n",
"2631 93077065 11\n",
"2630 93077064 11\n",
"1983 53013349 11\n",
"1941 51808718 11\n",
"1707 45369696 11\n",
"1467 17600716 11\n",
"3072 131851009 10\n",
"3067 129567524 10"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Double-check if the data are loaded correctly\n",
"# Compare the data with those from Cell [12]\n",
"df_freq.sort_values(by=['HitFreq', 'CID'], ascending=False).head(10)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(23848, 8)"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Create a new data frame called \"df\" by joining the df and df_freq data frames\n",
"df = df_raw.join(df_freq.set_index('CID'), on='CID')\n",
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" HBondDonorCount | \n",
" HBondAcceptorCount | \n",
" MolecularWeight | \n",
" XLogP | \n",
" CanonicalSMILES | \n",
" IsomericSMILES | \n",
" HitFreq | \n",
"
\n",
" \n",
" \n",
" \n",
" 1022 | \n",
" 11779854 | \n",
" 3 | \n",
" 2 | \n",
" 305.3 | \n",
" 2.6 | \n",
" C1C(C(=O)NC2=CC=CC=C21)NC(=O)C3=CC4=CC=CC=C4N3 | \n",
" C1C(C(=O)NC2=CC=CC=C21)NC(=O)C3=CC4=CC=CC=C4N3 | \n",
" 12 | \n",
"
\n",
" \n",
" 372 | \n",
" 118078858 | \n",
" 1 | \n",
" 2 | \n",
" 333.4 | \n",
" 3.0 | \n",
" CC1CN(C2=CC=CC=C2N1C(=O)C)C(=O)C3=CC4=CC=CC=C4N3 | \n",
" C[C@H]1CN(C2=CC=CC=C2N1C(=O)C)C(=O)C3=CC4=CC=C... | \n",
" 11 | \n",
"
\n",
" \n",
" 2631 | \n",
" 93077065 | \n",
" 2 | \n",
" 2 | \n",
" 409.5 | \n",
" 4.8 | \n",
" C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... | \n",
" C1CC2=CC=CC=C2N(C1)C(=O)[C@@H](C3=CC=CC=C3)NC(... | \n",
" 11 | \n",
"
\n",
" \n",
" 2630 | \n",
" 93077064 | \n",
" 2 | \n",
" 2 | \n",
" 409.5 | \n",
" 4.8 | \n",
" C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... | \n",
" C1CC2=CC=CC=C2N(C1)C(=O)[C@H](C3=CC=CC=C3)NC(=... | \n",
" 11 | \n",
"
\n",
" \n",
" 1983 | \n",
" 53013349 | \n",
" 2 | \n",
" 2 | \n",
" 409.5 | \n",
" 4.8 | \n",
" C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... | \n",
" C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... | \n",
" 11 | \n",
"
\n",
" \n",
" 1941 | \n",
" 51808718 | \n",
" 2 | \n",
" 3 | \n",
" 390.5 | \n",
" 2.9 | \n",
" CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... | \n",
" C[C@H](C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC... | \n",
" 11 | \n",
"
\n",
" \n",
" 1707 | \n",
" 45369696 | \n",
" 2 | \n",
" 3 | \n",
" 390.5 | \n",
" 2.9 | \n",
" CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... | \n",
" CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... | \n",
" 11 | \n",
"
\n",
" \n",
" 1467 | \n",
" 17600716 | \n",
" 2 | \n",
" 3 | \n",
" 390.5 | \n",
" 2.9 | \n",
" CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... | \n",
" C[C@@H](C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=C... | \n",
" 11 | \n",
"
\n",
" \n",
" 3072 | \n",
" 131851009 | \n",
" 1 | \n",
" 2 | \n",
" 347.4 | \n",
" 3.1 | \n",
" CN1CCN(C(C1=O)CC2=CC=CC=C2)C(=O)C3=CC4=CC=CC=C4N3 | \n",
" CN1CCN([C@H](C1=O)CC2=CC=CC=C2)C(=O)C3=CC4=CC=... | \n",
" 10 | \n",
"
\n",
" \n",
" 3067 | \n",
" 129567524 | \n",
" 1 | \n",
" 2 | \n",
" 347.4 | \n",
" 2.6 | \n",
" CC(=O)N1CCN(CC1C2=CC=CC=C2)C(=O)C3=CC4=CC=CC=C4N3 | \n",
" CC(=O)N1CCN(C[C@@H]1C2=CC=CC=C2)C(=O)C3=CC4=CC... | \n",
" 10 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID HBondDonorCount HBondAcceptorCount MolecularWeight XLogP \\\n",
"1022 11779854 3 2 305.3 2.6 \n",
"372 118078858 1 2 333.4 3.0 \n",
"2631 93077065 2 2 409.5 4.8 \n",
"2630 93077064 2 2 409.5 4.8 \n",
"1983 53013349 2 2 409.5 4.8 \n",
"1941 51808718 2 3 390.5 2.9 \n",
"1707 45369696 2 3 390.5 2.9 \n",
"1467 17600716 2 3 390.5 2.9 \n",
"3072 131851009 1 2 347.4 3.1 \n",
"3067 129567524 1 2 347.4 2.6 \n",
"\n",
" CanonicalSMILES \\\n",
"1022 C1C(C(=O)NC2=CC=CC=C21)NC(=O)C3=CC4=CC=CC=C4N3 \n",
"372 CC1CN(C2=CC=CC=C2N1C(=O)C)C(=O)C3=CC4=CC=CC=C4N3 \n",
"2631 C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... \n",
"2630 C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... \n",
"1983 C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... \n",
"1941 CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... \n",
"1707 CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... \n",
"1467 CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... \n",
"3072 CN1CCN(C(C1=O)CC2=CC=CC=C2)C(=O)C3=CC4=CC=CC=C4N3 \n",
"3067 CC(=O)N1CCN(CC1C2=CC=CC=C2)C(=O)C3=CC4=CC=CC=C4N3 \n",
"\n",
" IsomericSMILES HitFreq \n",
"1022 C1C(C(=O)NC2=CC=CC=C21)NC(=O)C3=CC4=CC=CC=C4N3 12 \n",
"372 C[C@H]1CN(C2=CC=CC=C2N1C(=O)C)C(=O)C3=CC4=CC=C... 11 \n",
"2631 C1CC2=CC=CC=C2N(C1)C(=O)[C@@H](C3=CC=CC=C3)NC(... 11 \n",
"2630 C1CC2=CC=CC=C2N(C1)C(=O)[C@H](C3=CC=CC=C3)NC(=... 11 \n",
"1983 C1CC2=CC=CC=C2N(C1)C(=O)C(C3=CC=CC=C3)NC(=O)C4... 11 \n",
"1941 C[C@H](C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC... 11 \n",
"1707 CC(C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=CC4=CC... 11 \n",
"1467 C[C@@H](C(=O)N1CCN(CC1)CC2=CC=CC=C2)NC(=O)C3=C... 11 \n",
"3072 CN1CCN([C@H](C1=O)CC2=CC=CC=C2)C(=O)C3=CC4=CC=... 10 \n",
"3067 CC(=O)N1CCN(C[C@@H]1C2=CC=CC=C2)C(=O)C3=CC4=CC... 10 "
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.sort_values(by=['HitFreq', 'CID'], ascending=False).head(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now identify and remove those compounds that satisfy all criteria of Lipinski's rule of five."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23803"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df[ df['HBondDonorCount'] <= 5 ])"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23830"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df[ df['HBondAcceptorCount'] <= 10 ])"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23238"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df[ df['MolecularWeight'] <= 500 ])"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"21105"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df[ df['XLogP'] < 5 ])"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"df = df[ ( df['HBondDonorCount'] <= 5) &\n",
" ( df['HBondAcceptorCount'] <= 10 ) &\n",
" ( df['MolecularWeight'] <= 500 ) &\n",
" ( df['XLogP'] < 5 ) ]"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"20827"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. Draw the structures of the top 10 compounds"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's check the structure of the top 10 compounds in the hit list."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"cids_top = df.sort_values(by=['HitFreq', 'CID'], ascending=False).head(10).CID.to_list()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"RDKit WARNING: [10:47:56] Enabling RDKit 2019.09.1 jupyter extensions\n",
"C:\\Users\\rebelford\\AppData\\Local\\Continuum\\anaconda3\\envs\\olcc2019\\lib\\site-packages\\ipykernel_launcher.py:8: FutureWarning: `item` has been deprecated and will be removed in a future version\n",
" \n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from rdkit import Chem\n",
"from rdkit.Chem import Draw\n",
"\n",
"mols = []\n",
"\n",
"for mycid in cids_top :\n",
" \n",
" mysmiles = df[ df.CID==mycid ].IsomericSMILES.item()\n",
" \n",
" mol = Chem.MolFromSmiles( mysmiles )\n",
" Chem.FindPotentialStereoBonds(mol) # Identify potential stereo bonds!\n",
" mols.append(mol)\n",
"\n",
"mylegends = [ \"CID \" + str(x) for x in cids_top ]\n",
"img = Draw.MolsToGridImage(mols, molsPerRow=2, subImgSize=(400,400), legends=mylegends)\n",
"display(img)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"An important observation from these images is that the hit list contains multiple compounds with the same connectivity. For example, CIDs 93077065 and 93077064 are stereoisomers of each other and CID 53013349 has the same connectivity as the two CIDs, but with its stereocenter being unspecified. When performing a screening with limited resources in the early stage of drug discovery, you may want to test as diverse molecules as possible, avoiding testing too similar structures."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To do so, let's look into PubChem's canonical SMILES strings, which do not encode the stereochemisry and isotope information. Chemicals with the same connectivity but with different stereochemistry/isotopes should have the same canonical SMILES. In the next section, we select unique compounds in terms of canonical SMILES to reduce the number of compounds to screen."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6. Extract unique compounds in terms of canonical SMILES"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The next few cells show how to get unique values within a column (in this case, unique canonical SMILES)."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"20827"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"16543"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df.CanonicalSMILES.unique())"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"canonical_smiles = df.CanonicalSMILES.unique()"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" HBondDonorCount | \n",
" HBondAcceptorCount | \n",
" MolecularWeight | \n",
" XLogP | \n",
" CanonicalSMILES | \n",
" IsomericSMILES | \n",
" HitFreq | \n",
"
\n",
" \n",
" \n",
" \n",
" 2 | \n",
" 9910160 | \n",
" 3 | \n",
" 4 | \n",
" 422.9 | \n",
" 4.4 | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" 3 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID HBondDonorCount HBondAcceptorCount MolecularWeight XLogP \\\n",
"2 9910160 3 4 422.9 4.4 \n",
"\n",
" CanonicalSMILES \\\n",
"2 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"\n",
" IsomericSMILES HitFreq \n",
"2 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... 3 "
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[ df.CanonicalSMILES == canonical_smiles[0] ]"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" HBondDonorCount | \n",
" HBondAcceptorCount | \n",
" MolecularWeight | \n",
" XLogP | \n",
" CanonicalSMILES | \n",
" IsomericSMILES | \n",
" HitFreq | \n",
"
\n",
" \n",
" \n",
" \n",
" 3 | \n",
" 70157737 | \n",
" 2 | \n",
" 4 | \n",
" 436.9 | \n",
" 4.6 | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" 3 | \n",
"
\n",
" \n",
" 6 | \n",
" 18318317 | \n",
" 2 | \n",
" 4 | \n",
" 436.9 | \n",
" 4.6 | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... | \n",
" 3 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID HBondDonorCount HBondAcceptorCount MolecularWeight XLogP \\\n",
"3 70157737 2 4 436.9 4.6 \n",
"6 18318317 2 4 436.9 4.6 \n",
"\n",
" CanonicalSMILES \\\n",
"3 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"6 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... \n",
"\n",
" IsomericSMILES HitFreq \n",
"3 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... 3 \n",
"6 CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)... 3 "
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[ df.CanonicalSMILES == canonical_smiles[1] ]"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)N(C)CC=CC3=CC=CC=C3',\n",
" 'CC1=C(C(C(=C(N1)C)C(=O)O)C2=CC(=CC=C2)Cl)C(=O)N(C)C/C=C/C3=CC=CC=C3']"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[ df.CanonicalSMILES == canonical_smiles[1] ].IsomericSMILES.to_list()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's generate a list of unique compounds in terms of canonical SMILES. If multiple compounds have the same canonical SMILES, the one that appears very first will be included in the unique compound list."
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"idx_to_include = []\n",
"\n",
"for mysmiles in canonical_smiles :\n",
"\n",
" myidx = df[ df.CanonicalSMILES == mysmiles ].index.to_list()[0]\n",
" \n",
" idx_to_include.append( myidx )"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"16543"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(idx_to_include)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Create a new column 'Include' \n",
"# All values initialized to 0 (not include)\n",
"df['Include'] = 0\n",
"df['Include'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"16543"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Now the \"Include\" column's value is modified if the record is in the idx_to_include list.\n",
"df.loc[idx_to_include,'Include'] = 1\n",
"df['Include'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" CID | \n",
" Include | \n",
"
\n",
" \n",
" \n",
" \n",
" 2 | \n",
" 9910160 | \n",
" 1 | \n",
"
\n",
" \n",
" 3 | \n",
" 70157737 | \n",
" 1 | \n",
"
\n",
" \n",
" 4 | \n",
" 70074958 | \n",
" 1 | \n",
"
\n",
" \n",
" 5 | \n",
" 70073800 | \n",
" 0 | \n",
"
\n",
" \n",
" 6 | \n",
" 18318317 | \n",
" 0 | \n",
"
\n",
" \n",
" 7 | \n",
" 18318313 | \n",
" 1 | \n",
"
\n",
" \n",
" 9 | \n",
" 18318274 | \n",
" 1 | \n",
"
\n",
" \n",
" 10 | \n",
" 18318270 | \n",
" 1 | \n",
"
\n",
" \n",
" 11 | \n",
" 15838576 | \n",
" 0 | \n",
"
\n",
" \n",
" 12 | \n",
" 15838575 | \n",
" 1 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" CID Include\n",
"2 9910160 1\n",
"3 70157737 1\n",
"4 70074958 1\n",
"5 70073800 0\n",
"6 18318317 0\n",
"7 18318313 1\n",
"9 18318274 1\n",
"10 18318270 1\n",
"11 15838576 0\n",
"12 15838575 1"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[['CID','Include']].head(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now draw the top 10 unique compounds (in terms of canonical SMILES). Note the, the structure figures are drawn using isomeric SMILES, but canonical SMILES strings could be used."
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"cids_top = df[ df['Include'] == 1].sort_values(by=['HitFreq', 'CID'], ascending=False).head(10).CID.to_list()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\rebelford\\AppData\\Local\\Continuum\\anaconda3\\envs\\olcc2019\\lib\\site-packages\\ipykernel_launcher.py:5: FutureWarning: `item` has been deprecated and will be removed in a future version\n",
" \"\"\"\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mols = []\n",
"\n",
"for mycid in cids_top :\n",
" \n",
" mysmiles = df[ df.CID==mycid ].IsomericSMILES.item()\n",
" \n",
" mol = Chem.MolFromSmiles( mysmiles )\n",
" Chem.FindPotentialStereoBonds(mol) # Identify potential stereo bonds!\n",
" mols.append(mol)\n",
"\n",
"mylegends = [ \"CID \" + str(x) for x in cids_top ]\n",
"img = Draw.MolsToGridImage(mols, molsPerRow=2, subImgSize=(400,400), legends=mylegends)\n",
"display(img)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7. Saving molecules in files"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now save the molecules in the cids_top list in files, which will be used in molecular docking experiments. For simplicity, we will use only the **top 3** compounds in the list."
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\rebelford\\AppData\\Local\\Continuum\\anaconda3\\envs\\olcc2019\\lib\\site-packages\\ipykernel_launcher.py:8: FutureWarning: `item` has been deprecated and will be removed in a future version\n",
" \n"
]
}
],
"source": [
"from rdkit.Chem import AllChem\n",
"\n",
"for idx, mycid in enumerate( cids_top ) :\n",
"\n",
" if idx == 3 :\n",
" break\n",
" \n",
" mysmiles = df[ df['CID'] == mycid ].IsomericSMILES.item()\n",
"\n",
" mymol = Chem.MolFromSmiles(mysmiles)\n",
" mymol = Chem.AddHs(mymol)\n",
" AllChem.EmbedMolecule(mymol)\n",
" AllChem.MMFFOptimizeMolecule(mymol)\n",
"\n",
" filename = \"pygm_lig\" + str(idx) + \"_\" + str(mycid) + \".mol\"\n",
" Chem.MolToMolFile(mymol, filename)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To save all data in the **df** data frame (in CSV) "
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"df.to_csv('pygm_df.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Exersises"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**1.** From the DUD-E target list (http://dude.docking.org/targets), find cyclooxigenase-2 (Target Name: PGH2, PDB ID: 3ln1). Download the \"**actives_final.ism**\" file and save it as \"**pgh2_3ln1_actives.ism**\". Load the data into a data frame called **df_act**. After loading the data, show the following information:\n",
"- the number of rows of the data frame.\n",
"- the first five rows of the data frame."
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" smiles | \n",
" dat | \n",
" id | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" c1ccc2cc(c(cc2c1)NC(=O)c3cc(ccn3)N(=O)=O)Oc4cc... | \n",
" 220668 | \n",
" CHEMBL134802 | \n",
"
\n",
" \n",
" 1 | \n",
" CC1=C(C(C(=C(N1Cc2ccc(cc2)Cl)C(=O)O)C(=O)O)c3c... | \n",
" 189331 | \n",
" CHEMBL115651 | \n",
"
\n",
" \n",
" 2 | \n",
" CCN1C(=C(C(C(=C1C(=O)O)C(=O)O)c2ccccc2Cl)C(=O)... | \n",
" 188996 | \n",
" CHEMBL113736 | \n",
"
\n",
" \n",
" 3 | \n",
" c1cc(c(c(c1)F)NC(=O)c2cc(ccn2)N(=O)=O)Oc3ccc(c... | \n",
" 219845 | \n",
" CHEMBL133911 | \n",
"
\n",
" \n",
" 4 | \n",
" CC1=C(C(C(=C(N1Cc2cccc(c2)N(=O)=O)C(=O)O)C(=O)... | \n",
" 189034 | \n",
" CHEMBL423509 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" smiles dat id\n",
"0 c1ccc2cc(c(cc2c1)NC(=O)c3cc(ccn3)N(=O)=O)Oc4cc... 220668 CHEMBL134802\n",
"1 CC1=C(C(C(=C(N1Cc2ccc(cc2)Cl)C(=O)O)C(=O)O)c3c... 189331 CHEMBL115651\n",
"2 CCN1C(=C(C(C(=C1C(=O)O)C(=O)O)c2ccccc2Cl)C(=O)... 188996 CHEMBL113736\n",
"3 c1cc(c(c(c1)F)NC(=O)c2cc(ccn2)N(=O)=O)Oc3ccc(c... 219845 CHEMBL133911\n",
"4 CC1=C(C(C(=C(N1Cc2cccc(c2)N(=O)=O)C(=O)O)C(=O)... 189034 CHEMBL423509"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_act.head(5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**2.** Perform similarity search using each of the isomeric SMILES contained in the loaded data frame. \n",
"- As we did for PYGM ligands in this notebook, track the number of times a particular hit is returned from multiple queries, using a dictionary named **cids_hit** (CIDs as keys and the frequencies as values). This information will be used to rank the hit compounds.\n",
"- Make sure that the CIDs are recognized as integers when they are used as keys in the dictionary.\n",
"- Print the total number of hits returned from this step (which is the same as the number of CIDs in **cids_hit**.\n",
"- Add **time.sleep()** to avoid overloading PubChem servers."
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
"prolog = \"https://pubchem.ncbi.nlm.nih.gov/rest/pug\"\n",
"\n",
"cids_hit = dict()\n",
"\n",
"for idx, mysmiles in enumerate(df_act.smiles.to_list()) :\n",
" \n",
" mydata = { 'smiles' : mysmiles }\n",
" \n",
" url = prolog + \"/compound/fastsimilarity_2d/smiles/cids/txt\"\n",
" res = requests.post(url, data=mydata)\n",
"\n",
" if ( res.status_code == 200 ) :\n",
" cids = res.text.split()\n",
" cids = [ int(x) for x in cids ]\n",
" else :\n",
" print(\"Error at\", idx, \":\", df_act.loc[idx,'id'], mysmiles )\n",
" print(res.status_code)\n",
" print(res.content)\n",
" \n",
" for mycid in cids:\n",
" cids_hit[mycid] = cids_hit.get(mycid, 0) + 1\n",
" \n",
" time.sleep(0.2)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23981"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cids_hit)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**3.** The hit list from the above step may contain the query compounds themselves. Get the CIDs of the query compounds through idenitity search and remove them from the hit list.\n",
"- Set the optional parameter \"**identity_type**\" to \"**same_connectivity**\".\n",
"- Add **time.sleep()** to avoid overloading PubChem servers.\n",
"- Print the number of CIDs corresponding to the query compounds.\n",
"- Print the number of the remaining hit compounds, after removing the query compounds from the hit list."
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"for mycid in cids_query.keys() :\n",
" \n",
" cids_hit.pop(mycid, None)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"133"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cids_query)"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23848"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cids_hit)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**4.** Download the hydrogen donor and acceptor counts, molecular weights, XlogP, and canonical and isomeric SMILES for each compound in **cids_hit**. Load the downloaded data into a new data frame called **df_raw**. Print the size (or dimension) of the data frame using **.shape**."
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(23848, 7)"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from io import StringIO\n",
"\n",
"csv_file = StringIO(csv)\n",
"df_raw = pd.read_csv(csv_file, sep=\",\")\n",
"df_raw.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**5.** Create a new data frame called **df**, which combines the data stored in **cids_hit** and **df_raw**. \n",
"- First load the frequency data into a new data frame called **df_freq** and then join **df_raw** and **df_freq** into **df**\n",
"- Print the shape (dimension) of **df**"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**6.** Remove from **df** the compounds that violate any criterion of Congreve's rule of 3 and show the number of remaining compounds (the number of rows of **df**)."
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**7.** Get the unique canonical SMILES strings from the **df**. Add to the **df** a column named '**Include**', which contains a flag set to 1 for the lowest CID associated with each unique CID and set to 0 for other CIDs. Show the number of compounds for which this flag is set to 1. "
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
"idx_to_include = []\n",
"\n",
"for mysmiles in canonical_smiles :\n",
"\n",
" myidx = df[ df.CanonicalSMILES == mysmiles ].index.to_list()[0]\n",
" \n",
" idx_to_include.append( myidx )"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"16543"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Include'] = 0\n",
"df.loc[idx_to_include,'Include'] = 1\n",
"\n",
"df['Include'].sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**8.** Among those with the \"Include\" flag set to 1, identify the top 10 compounds that were returned from the largest number of query compounds. \n",
"- Sort the data frame by the number of times returned (in descending order) and then by CID (in ascending order)\n",
"- For each of the 10 compounds, print its CID, isomeric SMILES, and the number of times it was returned.\n",
"- For each of the 10 compounds, draw its structure (using isomeric SMILES)."
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"# Write your code in this cell\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\rebelford\\AppData\\Local\\Continuum\\anaconda3\\envs\\olcc2019\\lib\\site-packages\\ipykernel_launcher.py:7: FutureWarning: `item` has been deprecated and will be removed in a future version\n",
" import sys\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cids_top = df[ df['Include'] == 1].sort_values(by=['HitFreq', 'CID'], ascending=[False,True]).head(10).CID.to_list()\n",
"\n",
"mols = []\n",
"\n",
"for mycid in cids_top :\n",
" \n",
" mysmiles = df[ df.CID==mycid ].IsomericSMILES.item()\n",
" \n",
" mol = Chem.MolFromSmiles( mysmiles )\n",
" Chem.FindPotentialStereoBonds(mol) # Identify potential stereo bonds!\n",
" mols.append(mol)\n",
"\n",
"mylegends = [ \"CID \" + str(x) for x in cids_top ]\n",
"img = Draw.MolsToGridImage(mols, molsPerRow=2, subImgSize=(400,400), legends=mylegends)\n",
"display(img)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"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": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 4
}