The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find a dataset script at /src/services/worker/jglaser/pdb_protein_ligand_complexes/pdb_protein_ligand_complexes.py or any data file in the same directory. Couldn't find 'jglaser/pdb_protein_ligand_complexes' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in jglaser/pdb_protein_ligand_complexes. 
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response
                  for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find a dataset script at /src/services/worker/jglaser/pdb_protein_ligand_complexes/pdb_protein_ligand_complexes.py or any data file in the same directory. Couldn't find 'jglaser/pdb_protein_ligand_complexes' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in jglaser/pdb_protein_ligand_complexes.

Need help to make the dataset viewer work? Open a discussion for direct support.

How to use the data sets

This dataset contains about 36,000 unique pairs of protein sequences and ligand SMILES, and the coordinates of their complexes from the PDB.

SMILES are assumed to be tokenized by the regex from P. Schwaller.

Ligand selection criteria

Only ligands

  • that have at least 3 atoms,
  • a molecular weight >= 100 Da,
  • and which are not among the 280 most common ligands in the PDB (this includes common additives like PEG, ADP, ..)

are considered.

Use the already preprocessed data

Load a test/train split using

import pandas as pd
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

# download the PDB archive into folder pdb/
sh rsync.sh 24 # number of parallel download processes

# extract sequences and coordinates in parallel
sbatch pdb.slurm
# or
mpirun -n 42 parse_complexes.py # desired number of tasks
Downloads last month
2
Edit dataset card