add protein local frames

data/pdbbind.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7fda9d4f86f91a5469a2bcaa3ecedd009e4e27abf412a1de377a65095033481b
-size 179039843
+oid sha256:cf8f01b7178290658968bc0bd73851dfcdde1937c7e5f27f6a03e058e82a8333
+size 712225770

pdbbind.py

@@ -88,12 +88,24 @@ def parse_complex(fn):
             warnings.simplefilter("ignore")
             structure = parser.get_structure('protein',fn+'/'+name+'_protein.pdb')
 
+        res_frames = []
+
+        # extract sequence, Calpha positions and local coordinate frames using the AF2 convention
         ppb = CaPPBuilder()
         seq = []
         xyz_receptor = []
+        R_receptor = []
         for pp in ppb.build_peptides(structure):
             seq.append(str(pp.get_sequence()))
             xyz_receptor += [tuple(a.get_vector()) for a in pp.get_ca_list()]
+
+            for res in pp:
+                N = np.array(tuple(res['N'].get_vector()))
+                C = np.array(tuple(res['C'].get_vector()))
+                CA = np.array(tuple(res['CA'].get_vector()))
+
+                R_receptor.append(rot_from_two_vecs(N-CA,C-CA).flatten().tolist())
+
         seq = ''.join(seq)
 
         # parse ligand, convert to SMILES and map atoms
@@ -125,7 +137,7 @@ def parse_complex(fn):
                 token_pos.append((np.nan, np.nan, np.nan))
                 token_rot.append(np.eye(3).flatten().tolist())
 
-        return name, seq, smi, xyz_receptor, token_pos, token_rot
+        return name, seq, smi, xyz_receptor, token_pos, token_rot, R_receptor
 
     except Exception as e:
         print(e)
@@ -149,11 +161,13 @@ if __name__ == '__main__':
             all_xyz_receptor = [r[3] for r in result if r is not None]
             all_xyz_ligand = [r[4] for r in result if r is not None]
             all_rot_ligand = [r[5] for r in result if r is not None]
+            all_rot_receptor = [r[6] for r in result if r is not None]
 
             import pandas as pd
             df = pd.DataFrame({'name': names, 'seq': seqs,
                                'smiles': all_smiles,
                                'receptor_xyz': all_xyz_receptor,
                                'ligand_xyz': all_xyz_ligand,
-                               'ligand_rot': all_rot_ligand})
+                               'ligand_rot': all_rot_ligand,
+                               'receptor_rot': all_rot_receptor})
             df.to_parquet('data/pdbbind.parquet',index=False)

pdbbind_complexes.py

@@ -57,7 +57,7 @@ _URLs = {name: _URL+_file_names[name] for name in _file_names}
 class PDBBindComplexes(datasets.ArrowBasedBuilder):
     """List of protein sequences, ligand SMILES, and complex coordinates."""
 
-    VERSION = datasets.Version("1.2.0")
+    VERSION = datasets.Version("1.3.0")
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
@@ -78,6 +78,8 @@ class PDBBindComplexes(datasets.ArrowBasedBuilder):
                 "smiles": datasets.Value("string"),
                 "ligand_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
                 "receptor_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
+                "ligand_rot": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
+                "receptor_rot": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
                 # These are the features of your dataset like images, labels ...
             }
         )