update README.md

README.md

@@ -14,12 +14,6 @@ of their complexes from the PDB.
 
 SMILES are assumed to be tokenized by the regex from P. Schwaller.
 
-Every (x,y,z) ligand coordinate maps onto a SMILES token, and is *nan* if the token does not represent an atom
-
-Every receptor coordinate maps onto the Calpha coordinate of that residue.
-
-The dataset can be used to fine-tune a language model.
-
 ## Ligand selection criteria
 
 Only ligands
@@ -40,6 +34,65 @@ train = pd.read_pickle('data/pdb_train.p')
 test = pd.read_pickle('data/pdb_test.p')
 ```
 
+Receptor features contain protein frames and side chain angles in OpenFold/AlphaFold format.
+Ligand tokens which do not correspond to atoms have `nan` as their coordinates.
+
+Documentation by example:
+
+```
+>>> import pandas as pd
+>>> test = pd.read_pickle('data/pdb_test.p')
+>>> test.head(5)
+  pdb_id lig_id  ...                                      ligand_xyz_2d                                       ligand_bonds
+0   7k38    VTY  ...  [(-2.031355975502858, -1.6316778784387098, 0.0...  [(0, 1), (1, 4), (4, 5), (5, 10), (10, 9), (9,...
+1   6prt    OWA  ...  [(4.883261310160714, -0.37850716807626705, 0.0...  [(11, 18), (18, 20), (20, 8), (8, 7), (7, 2), ...
+2   4lxx    FNF  ...  [(8.529427756002057, 2.2434809270065372, 0.0),...  [(51, 49), (49, 48), (48, 46), (46, 53), (53, ...
+3   4lxx    FON  ...  [(-10.939694946697701, -1.1876214529096956, 0....  [(13, 1), (1, 0), (0, 3), (3, 4), (4, 7), (7, ...
+4   7bp1    CAQ  ...  [(-1.9485571585149868, -1.499999999999999, 0.0...  [(4, 3), (3, 1), (1, 0), (0, 7), (7, 9), (7, 6...
+
+[5 rows x 8 columns]
+>>> test.columns
+Index(['pdb_id', 'lig_id', 'seq', 'smiles', 'receptor_features', 'ligand_xyz',
+       'ligand_xyz_2d', 'ligand_bonds'],
+      dtype='object')
+>>> test.iloc[0]['receptor_features']
+{'rigidgroups_gt_frames': array([[[[-5.3122622e-01,  2.0922849e-01, -8.2098854e-01,
+           1.7295000e+01],
+         [-7.1005428e-01, -6.3858479e-01,  2.9670244e-01,
+          -9.1399997e-01],
+         [-4.6219218e-01,  7.4056256e-01,  4.8779655e-01,
+           3.3284000e+01],
+         [ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,
+           1.0000000e+00]],
+...
+         [[ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,
+          -3.5030000e+00],
+         [ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,
+           2.6764999e+01],
+         [ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,
+           1.5136000e+01],
+         [ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,
+           1.0000000e+00]]]], dtype=float32), 'torsion_angles_sin_cos': array([[[-1.90855725e-09,  3.58859784e-02],
+        [ 1.55730803e-01,  9.87799530e-01],
+        [ 6.05505241e-01, -7.95841312e-01],
+        ...,
+        [-2.92459433e-01, -9.56277928e-01],
+        [ 9.96634814e-01, -8.19697779e-02],
+        [ 0.00000000e+00,  0.00000000e+00]],
+...
+
+       [[ 2.96455977e-04, -9.99999953e-01],
+        [-8.15660990e-01,  5.78530158e-01],
+        [-3.17915569e-01,  9.48119024e-01],
+        ...,
+        [ 0.00000000e+00,  0.00000000e+00],
+        [ 0.00000000e+00,  0.00000000e+00],
+        [ 0.00000000e+00,  0.00000000e+00]]])}
+>>> test.iloc[0]['receptor_features'].keys()
+dict_keys(['rigidgroups_gt_frames', 'torsion_angles_sin_cos'])
+>>> test.iloc[0]['ligand_xyz']
+[(22.289, 11.985, 9.225), (21.426, 11.623, 7.959), (nan, nan, nan), (nan, nan, nan), (21.797, 11.427, 6.574), (20.556, 11.56, 5.792), (nan, nan, nan), (20.507, 11.113, 4.552), (nan, nan, nan), (19.581, 10.97, 6.639), (20.107, 10.946, 7.954), (nan, nan, nan), (nan, nan, nan), (19.645, 10.364, 8.804)]
+```
 ### Manual update from PDB
 
 ```