add deepcoy DEKOIS and DUDE predictions

combine_predictions.py

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+import dask.dataframe as dd
+import sys
+
+if __name__ == '__main__':
+    import glob
+
+    filenames = glob.glob(sys.argv[2])
+
+    ddf = dd.read_parquet(filenames)
+    ddf.compute().to_parquet(sys.argv[1])

data/deepcoy_dekois_predict.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c50a7887a034c148c07ed24a6eba35e04e1319fd9e62a7364fa68ace63fedcab
+size 3597858

data/deepcoy_dude_predict.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:81412340663965b4495b9d13961ca9b86bd65b02b01ec11d218faafbd814e257
+size 38819110

deepcoy_combine.py

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+import dask.dataframe as dd
+import pandas as pd
+import sys
+import os
+import numpy as np
+
+from Bio.PDB import PDBList
+from Bio import SeqIO
+
+import warnings
+
+def get_sequence(pdb_id):
+    try:
+        pdbfile = PDBList().retrieve_pdb_file(pdb_id.upper(),file_format='pdb',pdir='/tmp')
+        seq = str(next(SeqIO.parse(pdbfile, "pdb-seqres")).seq)
+        os.unlink(pdbfile)
+
+        return seq
+    except Exception as e:
+        print(e)
+        pass
+
+if __name__ == '__main__':
+    import glob
+
+    filenames = glob.glob(sys.argv[3])
+
+    seqs = []
+    smiles = []
+    active = []
+
+    targets = pd.read_csv(sys.argv[1],sep=' ',keep_default_na=False)
+    for fn in filenames:
+        df = pd.read_csv(fn,header=None,sep=' ')
+        actives = df[0].unique()
+        decoys = df[1].unique()
+        smiles += actives.tolist()+decoys.tolist()
+        active += [True]*len(actives) + [False]*len(decoys)
+        split = os.path.basename(fn).split('-')
+        target = split[2].upper()
+        if len(split) > 5:
+            target += '-'+split[3].upper()
+        print(target)
+        seq = get_sequence(targets[targets.name.str.upper()==target].pdb.values[0])
+        seqs += [seq]*(len(actives)+len(decoys))
+
+    ddf = dd.from_pandas(pd.DataFrame({'seq': seqs, 'smiles': smiles, 'active': active}),npartitions=1)
+    ddf = ddf.repartition(partition_size='1M')
+    ddf.to_parquet(sys.argv[2])