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jglaser
/
binding_affinity

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chemistry
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2
jglaser commited on
Commit
5a93178
•
1 Parent(s): 75e835a

convert dtype to float32

Browse files
Files changed (7) hide show
  1. bindingdb.ipynb +428 -12
  2. combine_dbs.ipynb +163 -21
  3. data/all.parquet +2 -2
  4. data/all_nokras.parquet +2 -2
  5. data/cov.parquet +2 -2
  6. moad.ipynb +264 -2
  7. pdbbind.ipynb +190 -10
bindingdb.ipynb CHANGED
@@ -12,7 +12,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 2,
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  "id": "89cbcd82-4ca2-4aba-95b7-e58c0ceed770",
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  "metadata": {},
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  "outputs": [],
@@ -619,17 +619,28 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 16,
 
 
 
 
 
 
 
 
 
 
 
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  "id": "f602fdbe-7083-436c-9eac-9d97fbc8be67",
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "text/plain": [
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- "2512985"
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  ]
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  },
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- "execution_count": 16,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
@@ -640,7 +651,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 18,
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  "id": "27194288-cf3e-4c30-ad55-3b0998fdf939",
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  "metadata": {},
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  "outputs": [
@@ -758,7 +769,7 @@
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  "4 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00099 "
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  ]
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  },
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- "execution_count": 18,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
@@ -769,17 +780,17 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 19,
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  "id": "603fd298-0aa6-4097-b298-c55db013548c",
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "text/plain": [
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- "2512985"
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  ]
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  },
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- "execution_count": 19,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
@@ -790,7 +801,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 20,
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  "id": "d95ad9a9-d4ca-4679-8a33-235fe6e7047f",
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  "metadata": {},
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  "outputs": [
@@ -800,7 +811,7 @@
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  "2510716"
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  ]
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  },
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- "execution_count": 20,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
@@ -809,10 +820,415 @@
809
  "len(df_affinity[~df_affinity['affinity_uM'].isnull()])"
810
  ]
811
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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  "cell_type": "code",
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  "execution_count": null,
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- "id": "372a8c60-e63c-4d6a-a144-3ab5f4d93d22",
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  "metadata": {},
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  "outputs": [],
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  "source": []
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 3,
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  "id": "89cbcd82-4ca2-4aba-95b7-e58c0ceed770",
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  "metadata": {},
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  "outputs": [],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 1,
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+ "id": "f3a9173e-d574-4314-9cea-f8c0a66766c0",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
627
+ "import pandas as pd\n",
628
+ "df_affinity = pd.read_parquet('data/bindingdb.parquet')"
629
+ ]
630
+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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  "id": "f602fdbe-7083-436c-9eac-9d97fbc8be67",
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "text/plain": [
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+ "2510716"
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  ]
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  },
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+ "execution_count": 2,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 3,
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  "id": "27194288-cf3e-4c30-ad55-3b0998fdf939",
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  "metadata": {},
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  "outputs": [
 
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  "4 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00099 "
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  ]
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  },
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+ "execution_count": 3,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 4,
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  "id": "603fd298-0aa6-4097-b298-c55db013548c",
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "text/plain": [
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+ "2510716"
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  ]
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+ "execution_count": 4,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 5,
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  "id": "d95ad9a9-d4ca-4679-8a33-235fe6e7047f",
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  "metadata": {},
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  "outputs": [
 
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  "2510716"
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  ]
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  },
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+ "execution_count": 5,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
 
820
  "len(df_affinity[~df_affinity['affinity_uM'].isnull()])"
821
  ]
822
  },
823
+ {
824
+ "cell_type": "code",
825
+ "execution_count": 6,
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+ "id": "b21c4683-0fe1-4a0a-a55c-c0dc80193f36",
827
+ "metadata": {},
828
+ "outputs": [
829
+ {
830
+ "data": {
831
+ "text/html": [
832
+ "<div>\n",
833
+ "<style scoped>\n",
834
+ " .dataframe tbody tr th:only-of-type {\n",
835
+ " vertical-align: middle;\n",
836
+ " }\n",
837
+ "\n",
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+ " .dataframe tbody tr th {\n",
839
+ " vertical-align: top;\n",
840
+ " }\n",
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+ "\n",
842
+ " .dataframe thead th {\n",
843
+ " text-align: right;\n",
844
+ " }\n",
845
+ "</style>\n",
846
+ "<table border=\"1\" class=\"dataframe\">\n",
847
+ " <thead>\n",
848
+ " <tr style=\"text-align: right;\">\n",
849
+ " <th></th>\n",
850
+ " <th>Ligand SMILES</th>\n",
851
+ " <th>IC50 (nM)</th>\n",
852
+ " <th>KEGG ID of Ligand</th>\n",
853
+ " <th>Ki (nM)</th>\n",
854
+ " <th>Kd (nM)</th>\n",
855
+ " <th>EC50 (nM)</th>\n",
856
+ " <th>seq</th>\n",
857
+ " <th>affinity_uM</th>\n",
858
+ " </tr>\n",
859
+ " </thead>\n",
860
+ " <tbody>\n",
861
+ " <tr>\n",
862
+ " <th>0</th>\n",
863
+ " <td>COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1</td>\n",
864
+ " <td>None</td>\n",
865
+ " <td>None</td>\n",
866
+ " <td>0.24</td>\n",
867
+ " <td>None</td>\n",
868
+ " <td>None</td>\n",
869
+ " <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
870
+ " <td>0.00024</td>\n",
871
+ " </tr>\n",
872
+ " <tr>\n",
873
+ " <th>1</th>\n",
874
+ " <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...</td>\n",
875
+ " <td>None</td>\n",
876
+ " <td>None</td>\n",
877
+ " <td>0.25</td>\n",
878
+ " <td>None</td>\n",
879
+ " <td>None</td>\n",
880
+ " <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
881
+ " <td>0.00025</td>\n",
882
+ " </tr>\n",
883
+ " <tr>\n",
884
+ " <th>2</th>\n",
885
+ " <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...</td>\n",
886
+ " <td>None</td>\n",
887
+ " <td>None</td>\n",
888
+ " <td>0.41</td>\n",
889
+ " <td>None</td>\n",
890
+ " <td>None</td>\n",
891
+ " <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
892
+ " <td>0.00041</td>\n",
893
+ " </tr>\n",
894
+ " <tr>\n",
895
+ " <th>3</th>\n",
896
+ " <td>OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...</td>\n",
897
+ " <td>None</td>\n",
898
+ " <td>None</td>\n",
899
+ " <td>0.8</td>\n",
900
+ " <td>None</td>\n",
901
+ " <td>None</td>\n",
902
+ " <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
903
+ " <td>0.00080</td>\n",
904
+ " </tr>\n",
905
+ " <tr>\n",
906
+ " <th>4</th>\n",
907
+ " <td>OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...</td>\n",
908
+ " <td>None</td>\n",
909
+ " <td>None</td>\n",
910
+ " <td>0.99</td>\n",
911
+ " <td>None</td>\n",
912
+ " <td>None</td>\n",
913
+ " <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
914
+ " <td>0.00099</td>\n",
915
+ " </tr>\n",
916
+ " <tr>\n",
917
+ " <th>...</th>\n",
918
+ " <td>...</td>\n",
919
+ " <td>...</td>\n",
920
+ " <td>...</td>\n",
921
+ " <td>...</td>\n",
922
+ " <td>...</td>\n",
923
+ " <td>...</td>\n",
924
+ " <td>...</td>\n",
925
+ " <td>...</td>\n",
926
+ " </tr>\n",
927
+ " <tr>\n",
928
+ " <th>5112</th>\n",
929
+ " <td>COc1ccc(NC(=O)N2CCC(CC2)C(=O)N[C@@H](CC(C)C)C(...</td>\n",
930
+ " <td>17</td>\n",
931
+ " <td>None</td>\n",
932
+ " <td>None</td>\n",
933
+ " <td>None</td>\n",
934
+ " <td>None</td>\n",
935
+ " <td>MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE...</td>\n",
936
+ " <td>0.01700</td>\n",
937
+ " </tr>\n",
938
+ " <tr>\n",
939
+ " <th>5113</th>\n",
940
+ " <td>CC(C)C[C@H](NC(=O)C1CCN(CC1)C(=O)Nc1cnccn1)C(=...</td>\n",
941
+ " <td>76</td>\n",
942
+ " <td>None</td>\n",
943
+ " <td>None</td>\n",
944
+ " <td>None</td>\n",
945
+ " <td>None</td>\n",
946
+ " <td>MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE...</td>\n",
947
+ " <td>0.07600</td>\n",
948
+ " </tr>\n",
949
+ " <tr>\n",
950
+ " <th>5313</th>\n",
951
+ " <td>C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)OCc1ccccc1)...</td>\n",
952
+ " <td>&gt;100000</td>\n",
953
+ " <td>None</td>\n",
954
+ " <td>None</td>\n",
955
+ " <td>None</td>\n",
956
+ " <td>None</td>\n",
957
+ " <td>MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE...</td>\n",
958
+ " <td>100.00000</td>\n",
959
+ " </tr>\n",
960
+ " <tr>\n",
961
+ " <th>5314</th>\n",
962
+ " <td>FCC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)c1cccc2ccc...</td>\n",
963
+ " <td>&gt;100000</td>\n",
964
+ " <td>None</td>\n",
965
+ " <td>None</td>\n",
966
+ " <td>None</td>\n",
967
+ " <td>None</td>\n",
968
+ " <td>MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE...</td>\n",
969
+ " <td>100.00000</td>\n",
970
+ " </tr>\n",
971
+ " <tr>\n",
972
+ " <th>5361</th>\n",
973
+ " <td>FCC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)c1ccccc1</td>\n",
974
+ " <td>&gt;100000</td>\n",
975
+ " <td>None</td>\n",
976
+ " <td>None</td>\n",
977
+ " <td>None</td>\n",
978
+ " <td>None</td>\n",
979
+ " <td>MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE...</td>\n",
980
+ " <td>100.00000</td>\n",
981
+ " </tr>\n",
982
+ " </tbody>\n",
983
+ "</table>\n",
984
+ "<p>2510716 rows × 8 columns</p>\n",
985
+ "</div>"
986
+ ],
987
+ "text/plain": [
988
+ " Ligand SMILES IC50 (nM) \\\n",
989
+ "0 COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1 None \n",
990
+ "1 O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn... None \n",
991
+ "2 O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=... None \n",
992
+ "3 OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@... None \n",
993
+ "4 OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H... None \n",
994
+ "... ... ... \n",
995
+ "5112 COc1ccc(NC(=O)N2CCC(CC2)C(=O)N[C@@H](CC(C)C)C(... 17 \n",
996
+ "5113 CC(C)C[C@H](NC(=O)C1CCN(CC1)C(=O)Nc1cnccn1)C(=... 76 \n",
997
+ "5313 C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)OCc1ccccc1)... >100000 \n",
998
+ "5314 FCC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)c1cccc2ccc... >100000 \n",
999
+ "5361 FCC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)c1ccccc1 >100000 \n",
1000
+ "\n",
1001
+ " KEGG ID of Ligand Ki (nM) Kd (nM) EC50 (nM) \\\n",
1002
+ "0 None 0.24 None None \n",
1003
+ "1 None 0.25 None None \n",
1004
+ "2 None 0.41 None None \n",
1005
+ "3 None 0.8 None None \n",
1006
+ "4 None 0.99 None None \n",
1007
+ "... ... ... ... ... \n",
1008
+ "5112 None None None None \n",
1009
+ "5113 None None None None \n",
1010
+ "5313 None None None None \n",
1011
+ "5314 None None None None \n",
1012
+ "5361 None None None None \n",
1013
+ "\n",
1014
+ " seq affinity_uM \n",
1015
+ "0 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00024 \n",
1016
+ "1 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00025 \n",
1017
+ "2 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00041 \n",
1018
+ "3 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00080 \n",
1019
+ "4 PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM... 0.00099 \n",
1020
+ "... ... ... \n",
1021
+ "5112 MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE... 0.01700 \n",
1022
+ "5113 MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE... 0.07600 \n",
1023
+ "5313 MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE... 100.00000 \n",
1024
+ "5314 MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE... 100.00000 \n",
1025
+ "5361 MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVE... 100.00000 \n",
1026
+ "\n",
1027
+ "[2510716 rows x 8 columns]"
1028
+ ]
1029
+ },
1030
+ "execution_count": 6,
1031
+ "metadata": {},
1032
+ "output_type": "execute_result"
1033
+ }
1034
+ ],
1035
+ "source": [
1036
+ "df_affinity"
1037
+ ]
1038
+ },
1039
+ {
1040
+ "cell_type": "code",
1041
+ "execution_count": 25,
1042
+ "id": "20690729",
1043
+ "metadata": {},
1044
+ "outputs": [],
1045
+ "source": [
1046
+ "import rdkit.Chem as Chem"
1047
+ ]
1048
+ },
1049
+ {
1050
+ "cell_type": "code",
1051
+ "execution_count": 27,
1052
+ "id": "48114dcc",
1053
+ "metadata": {},
1054
+ "outputs": [],
1055
+ "source": [
1056
+ "df_pdb = df[~df['PDB ID(s) for Ligand-Target Complex'].isnull()][['PDB ID(s) for Ligand-Target Complex','Ligand SMILES']]"
1057
+ ]
1058
+ },
1059
+ {
1060
+ "cell_type": "code",
1061
+ "execution_count": 28,
1062
+ "id": "caa0497c",
1063
+ "metadata": {},
1064
+ "outputs": [],
1065
+ "source": [
1066
+ "def make_canonical(smi):\n",
1067
+ " return Chem.MolToSmiles(Chem.MolFromSmiles(smi))\n",
1068
+ "\n",
1069
+ "df_pdb['can_smiles'] = df_pdb['Ligand SMILES'].apply(make_canonical)"
1070
+ ]
1071
+ },
1072
+ {
1073
+ "cell_type": "code",
1074
+ "execution_count": 29,
1075
+ "id": "e82d64f3",
1076
+ "metadata": {},
1077
+ "outputs": [
1078
+ {
1079
+ "data": {
1080
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1092
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+ "</style>\n",
1095
+ "<table border=\"1\" class=\"dataframe\">\n",
1096
+ " <thead>\n",
1097
+ " <tr style=\"text-align: right;\">\n",
1098
+ " <th></th>\n",
1099
+ " <th>PDB ID(s) for Ligand-Target Complex</th>\n",
1100
+ " <th>Ligand SMILES</th>\n",
1101
+ " <th>can_smiles</th>\n",
1102
+ " </tr>\n",
1103
+ " </thead>\n",
1104
+ " <tbody>\n",
1105
+ " <tr>\n",
1106
+ " <th>0</th>\n",
1107
+ " <td>2IVU</td>\n",
1108
+ " <td>COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1</td>\n",
1109
+ " <td>COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1</td>\n",
1110
+ " </tr>\n",
1111
+ " <tr>\n",
1112
+ " <th>29</th>\n",
1113
+ " <td>1HWR</td>\n",
1114
+ " <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC=C)C(=O)...</td>\n",
1115
+ " <td>C=CCN1C(=O)N(CC=C)[C@H](Cc2ccccc2)[C@H](O)[C@@...</td>\n",
1116
+ " </tr>\n",
1117
+ " <tr>\n",
1118
+ " <th>34</th>\n",
1119
+ " <td>6DGY,6DH1,6DH4,6DH7,3O99</td>\n",
1120
+ " <td>CC[C@H](C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O...</td>\n",
1121
+ " <td>CC[C@H](C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O...</td>\n",
1122
+ " </tr>\n",
1123
+ " <tr>\n",
1124
+ " <th>129</th>\n",
1125
+ " <td>1MES,1MEU,1MET,1BVG,1BVE,3JVW,1QBS</td>\n",
1126
+ " <td>OCc1ccc(CN2[C@H](Cc3ccccc3)[C@H](O)[C@@H](O)[C...</td>\n",
1127
+ " <td>O=C1N(Cc2ccc(CO)cc2)[C@H](Cc2ccccc2)[C@H](O)[C...</td>\n",
1128
+ " </tr>\n",
1129
+ " <tr>\n",
1130
+ " <th>130</th>\n",
1131
+ " <td>1MER,1DMP,1RQ9</td>\n",
1132
+ " <td>Nc1cccc(CN2[C@H](Cc3ccccc3)[C@H](O)[C@@H](O)[C...</td>\n",
1133
+ " <td>Nc1cccc(CN2C(=O)N(Cc3cccc(N)c3)[C@H](Cc3ccccc3...</td>\n",
1134
+ " </tr>\n",
1135
+ " <tr>\n",
1136
+ " <th>...</th>\n",
1137
+ " <td>...</td>\n",
1138
+ " <td>...</td>\n",
1139
+ " <td>...</td>\n",
1140
+ " </tr>\n",
1141
+ " <tr>\n",
1142
+ " <th>2333375</th>\n",
1143
+ " <td>1MUI,2RKG,2RKF,1RV7,2Q5K,2O4S,6DJ1,6DJ2,3OGQ,2...</td>\n",
1144
+ " <td>CC(C)[C@H](N1CCCNC1=O)C(=O)N[C@H](C[C@H](O)[C@...</td>\n",
1145
+ " <td>Cc1cccc(C)c1OCC(=O)N[C@@H](Cc1ccccc1)[C@@H](O)...</td>\n",
1146
+ " </tr>\n",
1147
+ " <tr>\n",
1148
+ " <th>2333376</th>\n",
1149
+ " <td>4NPT,4DQH,4DQE,5E5J,3JW2,6OPU,6OPX,2HS2,2HS1,2...</td>\n",
1150
+ " <td>CC(C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O[C@H]...</td>\n",
1151
+ " <td>CC(C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O[C@H]...</td>\n",
1152
+ " </tr>\n",
1153
+ " <tr>\n",
1154
+ " <th>2333380</th>\n",
1155
+ " <td>6EKZ,1DY4,5FUK,6PS5</td>\n",
1156
+ " <td>CC(C)NCC(O)COc1cccc2ccccc12</td>\n",
1157
+ " <td>CC(C)NCC(O)COc1cccc2ccccc12</td>\n",
1158
+ " </tr>\n",
1159
+ " <tr>\n",
1160
+ " <th>2333384</th>\n",
1161
+ " <td>6EKZ,1DY4,5FUK,6PS5</td>\n",
1162
+ " <td>CC(C)NCC(O)COc1cccc2ccccc12</td>\n",
1163
+ " <td>CC(C)NCC(O)COc1cccc2ccccc12</td>\n",
1164
+ " </tr>\n",
1165
+ " <tr>\n",
1166
+ " <th>2333385</th>\n",
1167
+ " <td>6A60,3DCT</td>\n",
1168
+ " <td>CC(C)c1onc(c1COc1ccc(\\C=C\\c2cccc(c2)C(O)=O)c(C...</td>\n",
1169
+ " <td>CC(C)c1onc(-c2c(Cl)cccc2Cl)c1COc1ccc(/C=C/c2cc...</td>\n",
1170
+ " </tr>\n",
1171
+ " </tbody>\n",
1172
+ "</table>\n",
1173
+ "<p>123385 rows × 3 columns</p>\n",
1174
+ "</div>"
1175
+ ],
1176
+ "text/plain": [
1177
+ " PDB ID(s) for Ligand-Target Complex \\\n",
1178
+ "0 2IVU \n",
1179
+ "29 1HWR \n",
1180
+ "34 6DGY,6DH1,6DH4,6DH7,3O99 \n",
1181
+ "129 1MES,1MEU,1MET,1BVG,1BVE,3JVW,1QBS \n",
1182
+ "130 1MER,1DMP,1RQ9 \n",
1183
+ "... ... \n",
1184
+ "2333375 1MUI,2RKG,2RKF,1RV7,2Q5K,2O4S,6DJ1,6DJ2,3OGQ,2... \n",
1185
+ "2333376 4NPT,4DQH,4DQE,5E5J,3JW2,6OPU,6OPX,2HS2,2HS1,2... \n",
1186
+ "2333380 6EKZ,1DY4,5FUK,6PS5 \n",
1187
+ "2333384 6EKZ,1DY4,5FUK,6PS5 \n",
1188
+ "2333385 6A60,3DCT \n",
1189
+ "\n",
1190
+ " Ligand SMILES \\\n",
1191
+ "0 COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1 \n",
1192
+ "29 O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC=C)C(=O)... \n",
1193
+ "34 CC[C@H](C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O... \n",
1194
+ "129 OCc1ccc(CN2[C@H](Cc3ccccc3)[C@H](O)[C@@H](O)[C... \n",
1195
+ "130 Nc1cccc(CN2[C@H](Cc3ccccc3)[C@H](O)[C@@H](O)[C... \n",
1196
+ "... ... \n",
1197
+ "2333375 CC(C)[C@H](N1CCCNC1=O)C(=O)N[C@H](C[C@H](O)[C@... \n",
1198
+ "2333376 CC(C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O[C@H]... \n",
1199
+ "2333380 CC(C)NCC(O)COc1cccc2ccccc12 \n",
1200
+ "2333384 CC(C)NCC(O)COc1cccc2ccccc12 \n",
1201
+ "2333385 CC(C)c1onc(c1COc1ccc(\\C=C\\c2cccc(c2)C(O)=O)c(C... \n",
1202
+ "\n",
1203
+ " can_smiles \n",
1204
+ "0 COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1 \n",
1205
+ "29 C=CCN1C(=O)N(CC=C)[C@H](Cc2ccccc2)[C@H](O)[C@@... \n",
1206
+ "34 CC[C@H](C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O... \n",
1207
+ "129 O=C1N(Cc2ccc(CO)cc2)[C@H](Cc2ccccc2)[C@H](O)[C... \n",
1208
+ "130 Nc1cccc(CN2C(=O)N(Cc3cccc(N)c3)[C@H](Cc3ccccc3... \n",
1209
+ "... ... \n",
1210
+ "2333375 Cc1cccc(C)c1OCC(=O)N[C@@H](Cc1ccccc1)[C@@H](O)... \n",
1211
+ "2333376 CC(C)CN(C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)O[C@H]... \n",
1212
+ "2333380 CC(C)NCC(O)COc1cccc2ccccc12 \n",
1213
+ "2333384 CC(C)NCC(O)COc1cccc2ccccc12 \n",
1214
+ "2333385 CC(C)c1onc(-c2c(Cl)cccc2Cl)c1COc1ccc(/C=C/c2cc... \n",
1215
+ "\n",
1216
+ "[123385 rows x 3 columns]"
1217
+ ]
1218
+ },
1219
+ "execution_count": 29,
1220
+ "metadata": {},
1221
+ "output_type": "execute_result"
1222
+ }
1223
+ ],
1224
+ "source": [
1225
+ "df_pdb"
1226
+ ]
1227
+ },
1228
  {
1229
  "cell_type": "code",
1230
  "execution_count": null,
1231
+ "id": "593c9aec",
1232
  "metadata": {},
1233
  "outputs": [],
1234
  "source": []
combine_dbs.ipynb CHANGED
@@ -2,7 +2,7 @@
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
- "execution_count": 1,
6
  "id": "95bd761a-fe51-4a8e-bc70-1365260ba5f8",
7
  "metadata": {},
8
  "outputs": [],
@@ -1332,12 +1332,14 @@
1332
  },
1333
  {
1334
  "cell_type": "code",
1335
- "execution_count": 61,
1336
  "id": "c6c64066-4032-4247-a8b9-00388176cc7b",
1337
  "metadata": {},
1338
  "outputs": [],
1339
  "source": [
 
1340
  "#df.to_parquet('data/all.parquet')\n",
 
1341
  "#df = pd.read_parquet('data/all.parquet')"
1342
  ]
1343
  },
@@ -1513,12 +1515,14 @@
1513
  },
1514
  {
1515
  "cell_type": "code",
1516
- "execution_count": 70,
1517
  "id": "47966268-c97c-4bd9-9c90-eb568249f2ef",
1518
  "metadata": {},
1519
  "outputs": [],
1520
  "source": [
1521
- "df_nokras.to_parquet('data/all_nokras.parquet')"
 
 
1522
  ]
1523
  },
1524
  {
@@ -1531,7 +1535,7 @@
1531
  },
1532
  {
1533
  "cell_type": "code",
1534
- "execution_count": 71,
1535
  "id": "c0d250a3-5680-446c-9c98-7d6623643304",
1536
  "metadata": {},
1537
  "outputs": [],
@@ -1542,7 +1546,7 @@
1542
  },
1543
  {
1544
  "cell_type": "code",
1545
- "execution_count": 72,
1546
  "id": "0c7c0b26-1f2a-4b80-8117-f1e02719aac9",
1547
  "metadata": {},
1548
  "outputs": [
@@ -1550,14 +1554,14 @@
1550
  "name": "stderr",
1551
  "output_type": "stream",
1552
  "text": [
1553
- "RDKit WARNING: [13:20:36] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1554
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1555
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1556
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1557
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1558
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1559
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1560
- "RDKit WARNING: [13:20:37] Warning: molecule is tagged as 3D, but all Z coords are zero\n"
1561
  ]
1562
  }
1563
  ],
@@ -1578,28 +1582,166 @@
1578
  },
1579
  {
1580
  "cell_type": "code",
1581
- "execution_count": 75,
1582
  "id": "ee3fa0bc-9ad3-4ea7-9393-cbc7504f634c",
1583
  "metadata": {},
1584
  "outputs": [],
1585
  "source": [
1586
- "df_cov.reset_index(drop=True).to_parquet('data/cov.parquet')"
 
 
1587
  ]
1588
  },
1589
  {
1590
  "cell_type": "code",
1591
- "execution_count": null,
1592
  "id": "5c12fedc-4236-4587-a744-c0c9ec21ceaa",
1593
  "metadata": {},
1594
- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
1595
  "source": [
1596
- "l"
1597
  ]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1598
  }
1599
  ],
1600
  "metadata": {
1601
  "kernelspec": {
1602
- "display_name": "Python 3",
1603
  "language": "python",
1604
  "name": "python3"
1605
  },
@@ -1613,7 +1755,7 @@
1613
  "name": "python",
1614
  "nbconvert_exporter": "python",
1615
  "pygments_lexer": "ipython3",
1616
- "version": "3.9.4"
1617
  }
1618
  },
1619
  "nbformat": 4,
 
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
+ "execution_count": 2,
6
  "id": "95bd761a-fe51-4a8e-bc70-1365260ba5f8",
7
  "metadata": {},
8
  "outputs": [],
 
1332
  },
1333
  {
1334
  "cell_type": "code",
1335
+ "execution_count": 7,
1336
  "id": "c6c64066-4032-4247-a8b9-00388176cc7b",
1337
  "metadata": {},
1338
  "outputs": [],
1339
  "source": [
1340
+ "df = df.astype({'affinity_uM': 'float32', 'neg_log10_affinity_M': 'float32', 'affinity': 'float32'})\n",
1341
  "#df.to_parquet('data/all.parquet')\n",
1342
+ "\n",
1343
  "#df = pd.read_parquet('data/all.parquet')"
1344
  ]
1345
  },
 
1515
  },
1516
  {
1517
  "cell_type": "code",
1518
+ "execution_count": 10,
1519
  "id": "47966268-c97c-4bd9-9c90-eb568249f2ef",
1520
  "metadata": {},
1521
  "outputs": [],
1522
  "source": [
1523
+ "#df_nokras = df_nokras.astype({'affinity_uM': 'float32', 'neg_log10_affinity_M': 'float32', 'affinity': 'float32'})\n",
1524
+ "#df_nokras.to_parquet('data/all_nokras.parquet')\n",
1525
+ "#df_nokras = pd.read_parquet('data/all_nokras.parquet')"
1526
  ]
1527
  },
1528
  {
 
1535
  },
1536
  {
1537
  "cell_type": "code",
1538
+ "execution_count": 89,
1539
  "id": "c0d250a3-5680-446c-9c98-7d6623643304",
1540
  "metadata": {},
1541
  "outputs": [],
 
1546
  },
1547
  {
1548
  "cell_type": "code",
1549
+ "execution_count": 90,
1550
  "id": "0c7c0b26-1f2a-4b80-8117-f1e02719aac9",
1551
  "metadata": {},
1552
  "outputs": [
 
1554
  "name": "stderr",
1555
  "output_type": "stream",
1556
  "text": [
1557
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1558
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1559
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1560
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1561
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1562
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1563
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n",
1564
+ "RDKit WARNING: [13:44:45] Warning: molecule is tagged as 3D, but all Z coords are zero\n"
1565
  ]
1566
  }
1567
  ],
 
1582
  },
1583
  {
1584
  "cell_type": "code",
1585
+ "execution_count": 12,
1586
  "id": "ee3fa0bc-9ad3-4ea7-9393-cbc7504f634c",
1587
  "metadata": {},
1588
  "outputs": [],
1589
  "source": [
1590
+ "df_cov = df_cov.astype({'affinity_uM': 'float32', 'neg_log10_affinity_M': 'float32', 'affinity': 'float32'})\n",
1591
+ "#df_cov.reset_index(drop=True).to_parquet('data/cov.parquet')\n",
1592
+ "#df_cov = pd.read_parquet('data/cov.parquet')"
1593
  ]
1594
  },
1595
  {
1596
  "cell_type": "code",
1597
+ "execution_count": 77,
1598
  "id": "5c12fedc-4236-4587-a744-c0c9ec21ceaa",
1599
  "metadata": {},
1600
+ "outputs": [
1601
+ {
1602
+ "data": {
1603
+ "text/plain": [
1604
+ "346"
1605
+ ]
1606
+ },
1607
+ "execution_count": 77,
1608
+ "metadata": {},
1609
+ "output_type": "execute_result"
1610
+ }
1611
+ ],
1612
  "source": [
1613
+ "len(df_cov)"
1614
  ]
1615
+ },
1616
+ {
1617
+ "cell_type": "code",
1618
+ "execution_count": 78,
1619
+ "id": "1b73cea5-e6d9-427f-a31e-7ab38b5e6e4e",
1620
+ "metadata": {},
1621
+ "outputs": [
1622
+ {
1623
+ "data": {
1624
+ "text/plain": [
1625
+ "2.703125"
1626
+ ]
1627
+ },
1628
+ "execution_count": 78,
1629
+ "metadata": {},
1630
+ "output_type": "execute_result"
1631
+ }
1632
+ ],
1633
+ "source": [
1634
+ "346/128"
1635
+ ]
1636
+ },
1637
+ {
1638
+ "cell_type": "code",
1639
+ "execution_count": 80,
1640
+ "id": "2d1d2955-7839-45e0-9a11-07dda2d51b24",
1641
+ "metadata": {},
1642
+ "outputs": [
1643
+ {
1644
+ "data": {
1645
+ "text/plain": [
1646
+ "<AxesSubplot:>"
1647
+ ]
1648
+ },
1649
+ "execution_count": 80,
1650
+ "metadata": {},
1651
+ "output_type": "execute_result"
1652
+ },
1653
+ {
1654
+ "data": {
1655
+ "image/png": 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+ },
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+ "output_type": "display_data"
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+ }
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+ ],
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+ "source": [
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+ "df_cov['neg_log10_affinity_M'].hist()"
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+ ]
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+ },
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+ "cell_type": "code",
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+ "execution_count": 92,
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+ "id": "ab2e429b-d84c-42b7-b0dc-55e6728b9f81",
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+ "execution_count": 94,
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+ "outputs": [
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+ "data": {
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ "execution_count": 96,
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+ "id": "f59aa644-f848-447f-b82a-cff5b0507738",
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+ "execution_count": null,
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  ],
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  "metadata": {
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  "kernelspec": {
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  "language": "python",
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  "name": "python3"
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  },
 
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  "pygments_lexer": "ipython3",
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+ " <td>invalid</td>\n",
130
+ " <td>NaN</td>\n",
131
+ " <td>NaN</td>\n",
132
+ " <td>NaN</td>\n",
133
+ " <td>NaN</td>\n",
134
+ " <td>[O-]S(=O)(=O)[O-]</td>\n",
135
+ " <td>NaN</td>\n",
136
+ " </tr>\n",
137
+ " <tr>\n",
138
+ " <th>...</th>\n",
139
+ " <td>...</td>\n",
140
+ " <td>...</td>\n",
141
+ " <td>...</td>\n",
142
+ " <td>...</td>\n",
143
+ " <td>...</td>\n",
144
+ " <td>...</td>\n",
145
+ " <td>...</td>\n",
146
+ " <td>...</td>\n",
147
+ " <td>...</td>\n",
148
+ " <td>...</td>\n",
149
+ " <td>...</td>\n",
150
+ " </tr>\n",
151
+ " <tr>\n",
152
+ " <th>306520</th>\n",
153
+ " <td>NaN</td>\n",
154
+ " <td>NaN</td>\n",
155
+ " <td>NaN</td>\n",
156
+ " <td>CA:D:1950</td>\n",
157
+ " <td>Part of Protein</td>\n",
158
+ " <td>NaN</td>\n",
159
+ " <td>NaN</td>\n",
160
+ " <td>NaN</td>\n",
161
+ " <td>NaN</td>\n",
162
+ " <td>[Ca+2]</td>\n",
163
+ " <td>NaN</td>\n",
164
+ " </tr>\n",
165
+ " <tr>\n",
166
+ " <th>306521</th>\n",
167
+ " <td>NaN</td>\n",
168
+ " <td>NaN</td>\n",
169
+ " <td>NaN</td>\n",
170
+ " <td>NGA NAG:F:1</td>\n",
171
+ " <td>valid</td>\n",
172
+ " <td>Ka</td>\n",
173
+ " <td>=</td>\n",
174
+ " <td>5910.0</td>\n",
175
+ " <td>M^-1</td>\n",
176
+ " <td>NaN</td>\n",
177
+ " <td>NaN</td>\n",
178
+ " </tr>\n",
179
+ " <tr>\n",
180
+ " <th>306522</th>\n",
181
+ " <td>NaN</td>\n",
182
+ " <td>NaN</td>\n",
183
+ " <td>NaN</td>\n",
184
+ " <td>NGA NAG:E:1</td>\n",
185
+ " <td>valid</td>\n",
186
+ " <td>Ka</td>\n",
187
+ " <td>=</td>\n",
188
+ " <td>5910.0</td>\n",
189
+ " <td>M^-1</td>\n",
190
+ " <td>NaN</td>\n",
191
+ " <td>NaN</td>\n",
192
+ " </tr>\n",
193
+ " <tr>\n",
194
+ " <th>306523</th>\n",
195
+ " <td>NaN</td>\n",
196
+ " <td>NaN</td>\n",
197
+ " <td>NaN</td>\n",
198
+ " <td>NGA NAG:H:1</td>\n",
199
+ " <td>valid</td>\n",
200
+ " <td>Ka</td>\n",
201
+ " <td>=</td>\n",
202
+ " <td>5910.0</td>\n",
203
+ " <td>M^-1</td>\n",
204
+ " <td>NaN</td>\n",
205
+ " <td>NaN</td>\n",
206
+ " </tr>\n",
207
+ " <tr>\n",
208
+ " <th>306524</th>\n",
209
+ " <td>NaN</td>\n",
210
+ " <td>NaN</td>\n",
211
+ " <td>NaN</td>\n",
212
+ " <td>A2G NAG:G:1</td>\n",
213
+ " <td>invalid</td>\n",
214
+ " <td>NaN</td>\n",
215
+ " <td>NaN</td>\n",
216
+ " <td>NaN</td>\n",
217
+ " <td>NaN</td>\n",
218
+ " <td>NaN</td>\n",
219
+ " <td>NaN</td>\n",
220
+ " </tr>\n",
221
+ " </tbody>\n",
222
+ "</table>\n",
223
+ "<p>306525 rows × 11 columns</p>\n",
224
+ "</div>"
225
+ ],
226
+ "text/plain": [
227
+ " 0 1 pdb ligand_name \\\n",
228
+ "0 NaN NaN NaN HAE:C:989 \n",
229
+ "1 NaN NaN NaN NI:C:574 \n",
230
+ "2 NaN NaN NaN NI:C:575 \n",
231
+ "3 NaN Family. Representative Entry is 6H8J NaN \n",
232
+ "4 NaN NaN NaN SO4:C:611 \n",
233
+ "... ... ... ... ... \n",
234
+ "306520 NaN NaN NaN CA:D:1950 \n",
235
+ "306521 NaN NaN NaN NGA NAG:F:1 \n",
236
+ "306522 NaN NaN NaN NGA NAG:E:1 \n",
237
+ "306523 NaN NaN NaN NGA NAG:H:1 \n",
238
+ "306524 NaN NaN NaN A2G NAG:G:1 \n",
239
+ "\n",
240
+ " ligand_valid affinity_quantity 6 affinity_val affinity_unit \\\n",
241
+ "0 valid NaN NaN NaN NaN \n",
242
+ "1 Part of Protein NaN NaN NaN NaN \n",
243
+ "2 Part of Protein NaN NaN NaN NaN \n",
244
+ "3 NaN NaN NaN NaN NaN \n",
245
+ "4 invalid NaN NaN NaN NaN \n",
246
+ "... ... ... ... ... ... \n",
247
+ "306520 Part of Protein NaN NaN NaN NaN \n",
248
+ "306521 valid Ka = 5910.0 M^-1 \n",
249
+ "306522 valid Ka = 5910.0 M^-1 \n",
250
+ "306523 valid Ka = 5910.0 M^-1 \n",
251
+ "306524 invalid NaN NaN NaN NaN \n",
252
+ "\n",
253
+ " smiles 10 \n",
254
+ "0 CC(=O)NO NaN \n",
255
+ "1 [Ni+2] NaN \n",
256
+ "2 [Ni+2] NaN \n",
257
+ "3 NaN NaN \n",
258
+ "4 [O-]S(=O)(=O)[O-] NaN \n",
259
+ "... ... .. \n",
260
+ "306520 [Ca+2] NaN \n",
261
+ "306521 NaN NaN \n",
262
+ "306522 NaN NaN \n",
263
+ "306523 NaN NaN \n",
264
+ "306524 NaN NaN \n",
265
+ "\n",
266
+ "[306525 rows x 11 columns]"
267
+ ]
268
+ },
269
+ "execution_count": 3,
270
+ "metadata": {},
271
+ "output_type": "execute_result"
272
+ }
273
+ ],
274
+ "source": [
275
+ "df"
276
+ ]
277
+ },
278
  {
279
  "cell_type": "code",
280
  "execution_count": 3,
 
839
  },
840
  {
841
  "cell_type": "code",
842
+ "execution_count": 5,
843
  "id": "49a160d6-4599-488a-ba02-a65a79535f38",
844
  "metadata": {},
845
  "outputs": [],
846
+ "source": [
847
+ "df_all = pd.read_parquet('data/moad.parquet')"
848
+ ]
849
+ },
850
+ {
851
+ "cell_type": "code",
852
+ "execution_count": null,
853
+ "id": "bebcbe84-fa6d-4e39-bd26-40ed173e0e67",
854
+ "metadata": {},
855
+ "outputs": [],
856
  "source": []
857
  }
858
  ],
pdbbind.ipynb CHANGED
@@ -10,7 +10,7 @@
10
  },
11
  {
12
  "cell_type": "code",
13
- "execution_count": 27,
14
  "id": "86476f6e-802a-463b-a1b0-2ae228bb92af",
15
  "metadata": {},
16
  "outputs": [],
@@ -20,7 +20,7 @@
20
  },
21
  {
22
  "cell_type": "code",
23
- "execution_count": 45,
24
  "id": "9b2be11c-f4bb-4107-af49-abd78052afcf",
25
  "metadata": {},
26
  "outputs": [],
@@ -34,7 +34,7 @@
34
  },
35
  {
36
  "cell_type": "code",
37
- "execution_count": 46,
38
  "id": "68983ab8-bf11-4ed6-ba06-f962dbdc077e",
39
  "metadata": {},
40
  "outputs": [],
@@ -44,7 +44,7 @@
44
  },
45
  {
46
  "cell_type": "code",
47
- "execution_count": 47,
48
  "id": "3acbca3c-9c0b-43a1-a45e-331bf153bcfa",
49
  "metadata": {},
50
  "outputs": [],
@@ -67,7 +67,7 @@
67
  },
68
  {
69
  "cell_type": "code",
70
- "execution_count": 48,
71
  "id": "58e5748b-2cea-43ff-ab51-85a5021bd50b",
72
  "metadata": {},
73
  "outputs": [],
@@ -78,7 +78,7 @@
78
  },
79
  {
80
  "cell_type": "code",
81
- "execution_count": 49,
82
  "id": "d92f0004-68c1-4487-94b9-56b4fd598de4",
83
  "metadata": {},
84
  "outputs": [
@@ -88,7 +88,7 @@
88
  "<AxesSubplot:>"
89
  ]
90
  },
91
- "execution_count": 49,
92
  "metadata": {},
93
  "output_type": "execute_result"
94
  },
@@ -111,7 +111,7 @@
111
  },
112
  {
113
  "cell_type": "code",
114
- "execution_count": 50,
115
  "id": "aa358835-55f3-4551-9217-e76a15de4fe8",
116
  "metadata": {},
117
  "outputs": [],
@@ -121,7 +121,7 @@
121
  },
122
  {
123
  "cell_type": "code",
124
- "execution_count": 51,
125
  "id": "d6dda488-f709-4fe7-b372-080042cf7c66",
126
  "metadata": {},
127
  "outputs": [],
@@ -131,7 +131,7 @@
131
  },
132
  {
133
  "cell_type": "code",
134
- "execution_count": 52,
135
  "id": "df7929e3-c7fd-4e1b-a165-92f8d53b9011",
136
  "metadata": {},
137
  "outputs": [],
@@ -139,6 +139,186 @@
139
  "df_all = df_complex.merge(df_filter,on='name').drop('affinity',axis=1)"
140
  ]
141
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
142
  {
143
  "cell_type": "code",
144
  "execution_count": 53,
 
10
  },
11
  {
12
  "cell_type": "code",
13
+ "execution_count": 1,
14
  "id": "86476f6e-802a-463b-a1b0-2ae228bb92af",
15
  "metadata": {},
16
  "outputs": [],
 
20
  },
21
  {
22
  "cell_type": "code",
23
+ "execution_count": 12,
24
  "id": "9b2be11c-f4bb-4107-af49-abd78052afcf",
25
  "metadata": {},
26
  "outputs": [],
 
34
  },
35
  {
36
  "cell_type": "code",
37
+ "execution_count": 13,
38
  "id": "68983ab8-bf11-4ed6-ba06-f962dbdc077e",
39
  "metadata": {},
40
  "outputs": [],
 
44
  },
45
  {
46
  "cell_type": "code",
47
+ "execution_count": 14,
48
  "id": "3acbca3c-9c0b-43a1-a45e-331bf153bcfa",
49
  "metadata": {},
50
  "outputs": [],
 
67
  },
68
  {
69
  "cell_type": "code",
70
+ "execution_count": 15,
71
  "id": "58e5748b-2cea-43ff-ab51-85a5021bd50b",
72
  "metadata": {},
73
  "outputs": [],
 
78
  },
79
  {
80
  "cell_type": "code",
81
+ "execution_count": 16,
82
  "id": "d92f0004-68c1-4487-94b9-56b4fd598de4",
83
  "metadata": {},
84
  "outputs": [
 
88
  "<AxesSubplot:>"
89
  ]
90
  },
91
+ "execution_count": 16,
92
  "metadata": {},
93
  "output_type": "execute_result"
94
  },
 
111
  },
112
  {
113
  "cell_type": "code",
114
+ "execution_count": 17,
115
  "id": "aa358835-55f3-4551-9217-e76a15de4fe8",
116
  "metadata": {},
117
  "outputs": [],
 
121
  },
122
  {
123
  "cell_type": "code",
124
+ "execution_count": 18,
125
  "id": "d6dda488-f709-4fe7-b372-080042cf7c66",
126
  "metadata": {},
127
  "outputs": [],
 
131
  },
132
  {
133
  "cell_type": "code",
134
+ "execution_count": 20,
135
  "id": "df7929e3-c7fd-4e1b-a165-92f8d53b9011",
136
  "metadata": {},
137
  "outputs": [],
 
139
  "df_all = df_complex.merge(df_filter,on='name').drop('affinity',axis=1)"
140
  ]
141
  },
142
+ {
143
+ "cell_type": "code",
144
+ "execution_count": 21,
145
+ "id": "41711825-b110-472b-a9f3-2eccc5afbfd9",
146
+ "metadata": {},
147
+ "outputs": [
148
+ {
149
+ "data": {
150
+ "text/html": [
151
+ "<div>\n",
152
+ "<style scoped>\n",
153
+ " .dataframe tbody tr th:only-of-type {\n",
154
+ " vertical-align: middle;\n",
155
+ " }\n",
156
+ "\n",
157
+ " .dataframe tbody tr th {\n",
158
+ " vertical-align: top;\n",
159
+ " }\n",
160
+ "\n",
161
+ " .dataframe thead th {\n",
162
+ " text-align: right;\n",
163
+ " }\n",
164
+ "</style>\n",
165
+ "<table border=\"1\" class=\"dataframe\">\n",
166
+ " <thead>\n",
167
+ " <tr style=\"text-align: right;\">\n",
168
+ " <th></th>\n",
169
+ " <th>name</th>\n",
170
+ " <th>seq</th>\n",
171
+ " <th>smiles</th>\n",
172
+ " <th>affinity_uM</th>\n",
173
+ " <th>affinity_quantity</th>\n",
174
+ " </tr>\n",
175
+ " </thead>\n",
176
+ " <tbody>\n",
177
+ " <tr>\n",
178
+ " <th>0</th>\n",
179
+ " <td>2lbv</td>\n",
180
+ " <td>MTVPDRSEIAGKWYVVALASNTEFFLREKDKMKMAMARISFLGEDE...</td>\n",
181
+ " <td>CCCCCCCCCCCCCCCCCCCC(=O)O</td>\n",
182
+ " <td>0.02600</td>\n",
183
+ " <td>Kd</td>\n",
184
+ " </tr>\n",
185
+ " <tr>\n",
186
+ " <th>1</th>\n",
187
+ " <td>1lt6</td>\n",
188
+ " <td>APQTITELCSEYRNTQIYTINDKILSYTESMAGKREMVIITFKSGE...</td>\n",
189
+ " <td>OC[C@H]1O[C@H](Oc2cccc(c2)N(=O)=O)[C@@H]([C@H]...</td>\n",
190
+ " <td>500.00000</td>\n",
191
+ " <td>IC50</td>\n",
192
+ " </tr>\n",
193
+ " <tr>\n",
194
+ " <th>2</th>\n",
195
+ " <td>4lwi</td>\n",
196
+ " <td>VETFAFQAEIAQLMSLIINTFYSNKEIFLRELISNSSDALDKIRYE...</td>\n",
197
+ " <td>COc1ccc(cc1)c1c(onc1c1cc(C(C)C)c(cc1O)O)NC(=O)...</td>\n",
198
+ " <td>0.02300</td>\n",
199
+ " <td>IC50</td>\n",
200
+ " </tr>\n",
201
+ " <tr>\n",
202
+ " <th>3</th>\n",
203
+ " <td>3t4p</td>\n",
204
+ " <td>AAPFDKSKNVAQSIDQLIGQTPALYLNKLNNTKAKVVLKMECENPM...</td>\n",
205
+ " <td>OC[C@@H](C(=O)N[C@@H]([C@H](CC)C)C(=O)O)NC(=O)...</td>\n",
206
+ " <td>6.43000</td>\n",
207
+ " <td>Kd</td>\n",
208
+ " </tr>\n",
209
+ " <tr>\n",
210
+ " <th>4</th>\n",
211
+ " <td>6oyz</td>\n",
212
+ " <td>YITFRSFTAVLIAFFLTLVLSPSFINRLRKIQRKKYTPTMGGIVIL...</td>\n",
213
+ " <td>CO[C@@H]1[C@H](O[C@H]([C@@H]1O)n1ccc(=O)[nH]c1...</td>\n",
214
+ " <td>0.18500</td>\n",
215
+ " <td>IC50</td>\n",
216
+ " </tr>\n",
217
+ " <tr>\n",
218
+ " <th>...</th>\n",
219
+ " <td>...</td>\n",
220
+ " <td>...</td>\n",
221
+ " <td>...</td>\n",
222
+ " <td>...</td>\n",
223
+ " <td>...</td>\n",
224
+ " </tr>\n",
225
+ " <tr>\n",
226
+ " <th>24754</th>\n",
227
+ " <td>4j46</td>\n",
228
+ " <td>GTIYPRNPAMYSEEARLKSFQNWPDYAHLTPRELASAGLYYTGIGD...</td>\n",
229
+ " <td>CC[C@@H]([C@@H](C(=O)O)NC(=O)[C@@H]1CCCN1C(=O)...</td>\n",
230
+ " <td>5.24000</td>\n",
231
+ " <td>Ki</td>\n",
232
+ " </tr>\n",
233
+ " <tr>\n",
234
+ " <th>24755</th>\n",
235
+ " <td>2c80</td>\n",
236
+ " <td>DHIKVIYFNGRGRAESIRMTLVAAGVNYEDERISFQDWPKIKPTIP...</td>\n",
237
+ " <td>CCCCCCSC[C@@H](C(=O)NCC(=O)O)NC(=O)CC[C@@H](C(...</td>\n",
238
+ " <td>4.70000</td>\n",
239
+ " <td>Kd</td>\n",
240
+ " </tr>\n",
241
+ " <tr>\n",
242
+ " <th>24756</th>\n",
243
+ " <td>2c80</td>\n",
244
+ " <td>DHIKVIYFNGRGRAESIRMTLVAAGVNYEDERISFQDWPKIKPTIP...</td>\n",
245
+ " <td>CCCCCCSC[C@@H](C(=O)NCC(=O)O)NC(=O)CC[C@@H](C(...</td>\n",
246
+ " <td>4.70000</td>\n",
247
+ " <td>Kd</td>\n",
248
+ " </tr>\n",
249
+ " <tr>\n",
250
+ " <th>24757</th>\n",
251
+ " <td>5wl0</td>\n",
252
+ " <td>NDDIDQSLIIAARNIVRRASVSADPLASLLEMCHSTQIGGTRMVDI...</td>\n",
253
+ " <td>OC(=O)[C@H]1[C@@H]2CC[C@H]([C@@H]1Nc1nc(ncc1F)...</td>\n",
254
+ " <td>0.00067</td>\n",
255
+ " <td>Kd</td>\n",
256
+ " </tr>\n",
257
+ " <tr>\n",
258
+ " <th>24758</th>\n",
259
+ " <td>5wl0</td>\n",
260
+ " <td>NDDIDQSLIIAARNIVRRASVSADPLASLLEMCHSTQIGGTRMVDI...</td>\n",
261
+ " <td>OC(=O)[C@H]1[C@@H]2CC[C@H]([C@@H]1Nc1nc(ncc1F)...</td>\n",
262
+ " <td>0.00067</td>\n",
263
+ " <td>Kd</td>\n",
264
+ " </tr>\n",
265
+ " </tbody>\n",
266
+ "</table>\n",
267
+ "<p>24759 rows × 5 columns</p>\n",
268
+ "</div>"
269
+ ],
270
+ "text/plain": [
271
+ " name seq \\\n",
272
+ "0 2lbv MTVPDRSEIAGKWYVVALASNTEFFLREKDKMKMAMARISFLGEDE... \n",
273
+ "1 1lt6 APQTITELCSEYRNTQIYTINDKILSYTESMAGKREMVIITFKSGE... \n",
274
+ "2 4lwi VETFAFQAEIAQLMSLIINTFYSNKEIFLRELISNSSDALDKIRYE... \n",
275
+ "3 3t4p AAPFDKSKNVAQSIDQLIGQTPALYLNKLNNTKAKVVLKMECENPM... \n",
276
+ "4 6oyz YITFRSFTAVLIAFFLTLVLSPSFINRLRKIQRKKYTPTMGGIVIL... \n",
277
+ "... ... ... \n",
278
+ "24754 4j46 GTIYPRNPAMYSEEARLKSFQNWPDYAHLTPRELASAGLYYTGIGD... \n",
279
+ "24755 2c80 DHIKVIYFNGRGRAESIRMTLVAAGVNYEDERISFQDWPKIKPTIP... \n",
280
+ "24756 2c80 DHIKVIYFNGRGRAESIRMTLVAAGVNYEDERISFQDWPKIKPTIP... \n",
281
+ "24757 5wl0 NDDIDQSLIIAARNIVRRASVSADPLASLLEMCHSTQIGGTRMVDI... \n",
282
+ "24758 5wl0 NDDIDQSLIIAARNIVRRASVSADPLASLLEMCHSTQIGGTRMVDI... \n",
283
+ "\n",
284
+ " smiles affinity_uM \\\n",
285
+ "0 CCCCCCCCCCCCCCCCCCCC(=O)O 0.02600 \n",
286
+ "1 OC[C@H]1O[C@H](Oc2cccc(c2)N(=O)=O)[C@@H]([C@H]... 500.00000 \n",
287
+ "2 COc1ccc(cc1)c1c(onc1c1cc(C(C)C)c(cc1O)O)NC(=O)... 0.02300 \n",
288
+ "3 OC[C@@H](C(=O)N[C@@H]([C@H](CC)C)C(=O)O)NC(=O)... 6.43000 \n",
289
+ "4 CO[C@@H]1[C@H](O[C@H]([C@@H]1O)n1ccc(=O)[nH]c1... 0.18500 \n",
290
+ "... ... ... \n",
291
+ "24754 CC[C@@H]([C@@H](C(=O)O)NC(=O)[C@@H]1CCCN1C(=O)... 5.24000 \n",
292
+ "24755 CCCCCCSC[C@@H](C(=O)NCC(=O)O)NC(=O)CC[C@@H](C(... 4.70000 \n",
293
+ "24756 CCCCCCSC[C@@H](C(=O)NCC(=O)O)NC(=O)CC[C@@H](C(... 4.70000 \n",
294
+ "24757 OC(=O)[C@H]1[C@@H]2CC[C@H]([C@@H]1Nc1nc(ncc1F)... 0.00067 \n",
295
+ "24758 OC(=O)[C@H]1[C@@H]2CC[C@H]([C@@H]1Nc1nc(ncc1F)... 0.00067 \n",
296
+ "\n",
297
+ " affinity_quantity \n",
298
+ "0 Kd \n",
299
+ "1 IC50 \n",
300
+ "2 IC50 \n",
301
+ "3 Kd \n",
302
+ "4 IC50 \n",
303
+ "... ... \n",
304
+ "24754 Ki \n",
305
+ "24755 Kd \n",
306
+ "24756 Kd \n",
307
+ "24757 Kd \n",
308
+ "24758 Kd \n",
309
+ "\n",
310
+ "[24759 rows x 5 columns]"
311
+ ]
312
+ },
313
+ "execution_count": 21,
314
+ "metadata": {},
315
+ "output_type": "execute_result"
316
+ }
317
+ ],
318
+ "source": [
319
+ "df_all"
320
+ ]
321
+ },
322
  {
323
  "cell_type": "code",
324
  "execution_count": 53,