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--- |
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tags: |
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- proteins |
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- molecules |
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- chemistry |
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- SMILES |
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- complex structures |
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--- |
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## How to use the data sets |
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This dataset contains about 36,000 unique pairs of protein sequences and ligand SMILES, and the coordinates |
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of their complexes from the PDB. |
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SMILES are assumed to be tokenized by the regex from P. Schwaller. |
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## Ligand selection criteria |
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Only ligands |
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- that have at least 3 atoms, |
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- a molecular weight >= 100 Da, |
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- and which are not among the 280 most common ligands in the PDB (this includes common additives like PEG, ADP, ..) |
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are considered. |
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### Use the already preprocessed data |
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Load a test/train split using |
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``` |
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import pandas as pd |
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train = pd.read_pickle('data/pdb_train.p') |
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test = pd.read_pickle('data/pdb_test.p') |
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``` |
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Receptor features contain protein frames and side chain angles in OpenFold/AlphaFold format. |
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Ligand tokens which do not correspond to atoms have `nan` as their coordinates. |
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Documentation by example: |
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``` |
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>>> import pandas as pd |
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>>> test = pd.read_pickle('data/pdb_test.p') |
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>>> test.head(5) |
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pdb_id lig_id ... ligand_xyz_2d ligand_bonds |
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0 7k38 VTY ... [(-2.031355975502858, -1.6316778784387098, 0.0... [(0, 1), (1, 4), (4, 5), (5, 10), (10, 9), (9,... |
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1 6prt OWA ... [(4.883261310160714, -0.37850716807626705, 0.0... [(11, 18), (18, 20), (20, 8), (8, 7), (7, 2), ... |
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2 4lxx FNF ... [(8.529427756002057, 2.2434809270065372, 0.0),... [(51, 49), (49, 48), (48, 46), (46, 53), (53, ... |
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3 4lxx FON ... [(-10.939694946697701, -1.1876214529096956, 0.... [(13, 1), (1, 0), (0, 3), (3, 4), (4, 7), (7, ... |
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4 7bp1 CAQ ... [(-1.9485571585149868, -1.499999999999999, 0.0... [(4, 3), (3, 1), (1, 0), (0, 7), (7, 9), (7, 6... |
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[5 rows x 8 columns] |
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>>> test.columns |
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Index(['pdb_id', 'lig_id', 'seq', 'smiles', 'receptor_features', 'ligand_xyz', |
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'ligand_xyz_2d', 'ligand_bonds'], |
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dtype='object') |
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>>> test.iloc[0]['receptor_features'] |
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{'rigidgroups_gt_frames': array([[[[-5.3122622e-01, 2.0922849e-01, -8.2098854e-01, |
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1.7295000e+01], |
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[-7.1005428e-01, -6.3858479e-01, 2.9670244e-01, |
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-9.1399997e-01], |
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[-4.6219218e-01, 7.4056256e-01, 4.8779655e-01, |
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3.3284000e+01], |
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[ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, |
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1.0000000e+00]], |
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... |
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[[ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, |
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-3.5030000e+00], |
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[ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, |
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2.6764999e+01], |
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[ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, |
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1.5136000e+01], |
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[ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, |
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1.0000000e+00]]]], dtype=float32), 'torsion_angles_sin_cos': array([[[-1.90855725e-09, 3.58859784e-02], |
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[ 1.55730803e-01, 9.87799530e-01], |
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[ 6.05505241e-01, -7.95841312e-01], |
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..., |
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[-2.92459433e-01, -9.56277928e-01], |
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[ 9.96634814e-01, -8.19697779e-02], |
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[ 0.00000000e+00, 0.00000000e+00]], |
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... |
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[[ 2.96455977e-04, -9.99999953e-01], |
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[-8.15660990e-01, 5.78530158e-01], |
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[-3.17915569e-01, 9.48119024e-01], |
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..., |
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[ 0.00000000e+00, 0.00000000e+00], |
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[ 0.00000000e+00, 0.00000000e+00], |
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[ 0.00000000e+00, 0.00000000e+00]]])} |
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>>> test.iloc[0]['receptor_features'].keys() |
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dict_keys(['rigidgroups_gt_frames', 'torsion_angles_sin_cos']) |
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>>> test.iloc[0]['ligand_xyz'] |
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[(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)] |
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``` |
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### Manual update from PDB |
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``` |
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# download the PDB archive into folder pdb/ |
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sh rsync.sh 24 # number of parallel download processes |
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# extract sequences and coordinates in parallel |
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sbatch pdb.slurm |
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# or |
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mpirun -n 42 parse_complexes.py # desired number of tasks |
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``` |
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