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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
columns: int64
critical_nonmissing_counts: struct<cofold_aggregate_score: int64, cofold_confidence: int64, cofold_iptm: int64, cofold_primary_s (... 159 chars omitted)
child 0, cofold_aggregate_score: int64
child 1, cofold_confidence: int64
child 2, cofold_iptm: int64
child 3, cofold_primary_score: int64
child 4, cofold_ptm: int64
child 5, structure_anchor_contact_pass: int64
child 6, structure_contact_atom_pairs_4p5a: int64
child 7, structure_min_ligand_protein_distance_a: int64
csv_path: string
data_dictionary_csv: string
data_dictionary_sha256: string
derived_has_structural_features_counts: struct<true: int64>
child 0, true: int64
hf_upload_layout: string
primary_score_source_counts: struct<aggregate_score: int64, confidence_score: int64, iptm: int64>
child 0, aggregate_score: int64
child 1, confidence_score: int64
child 2, iptm: int64
remote_aligned_cif_relpath_missing_count: int64
rows: int64
rows_by_consolidated_method_setup: struct<boltz2::boltz2_no_template: int64, boltz2::boltz2_self_template: int64, boltz::boltz_no_templ (... 221 chars omitted)
child 0, boltz2::boltz2_no_template: int64
child 1, boltz2::boltz2_self_template: int64
child 2, boltz::boltz_no_template: int64
child 3, chai1::chai1_msa: int64
child 4, chai1::chai1_no_template: int64
child 5, chai1::chai1_self_template: int64
child 6, openfold3::openfold3_msa: int64
child 7, openfold3::openfold3_no_template: int64
child 8, openfold3::openfold3_self_template: int64
...
2_no_template: int64, boltz2::boltz2_self_template: int64, boltz::boltz_no_templ (... 253 chars omitted)
child 0, boltz2::boltz2_no_template: int64
child 1, boltz2::boltz2_self_template: int64
child 2, boltz::boltz_no_template: int64
child 3, chai1::chai1_msa_seed11_25_50_67: int64
child 4, chai1::chai1_no_template: int64
child 5, chai1::chai1_self_template: int64
child 6, openfold3::openfold3_msa_seed11_25_50_67: int64
child 7, openfold3::openfold3_no_template: int64
child 8, openfold3::openfold3_self_template: int64
seed_list_rows_remaining_in_consolidated_setup_labels: int64
sha256: string
sha256sums_entries_regenerated: int64
unique_canonical_cif_names: int64
unique_structure_ids: int64
out: string
canonical_filename_precheck_unique: bool
total_bytes_in_output_dir: int64
ok_rows: int64
collation_status_counts: struct<ok: int64>
child 0, ok: int64
duplicate_cif_names: int64
sha256_entries: int64
source_revision: string
sha256sums: string
alignment_status_counts: struct<aligned: int64, reference_first_structure: int64>
child 0, aligned: int64
child 1, reference_first_structure: int64
cofolding_info_rows: int64
unique_aligned_cif_names: int64
selected_rows: int64
source_repo: string
cif_counts_by_consolidated_dir: struct<activity_challenge: int64, pdb64: int64, structure_challenge: int64>
child 0, activity_challenge: int64
child 1, pdb64: int64
child 2, structure_challenge: int64
missing_aligned_cifs: int64
failed_rows: int64
written_rows: int64
to
{'alignment_status_counts': {'aligned': Value('int64'), 'reference_first_structure': Value('int64')}, 'canonical_filename_precheck_unique': Value('bool'), 'cif_counts_by_consolidated_dir': {'activity_challenge': Value('int64'), 'pdb64': Value('int64'), 'structure_challenge': Value('int64')}, 'cofolding_info_rows': Value('int64'), 'collation_status_counts': {'ok': Value('int64')}, 'duplicate_cif_names': Value('int64'), 'failed_rows': Value('int64'), 'missing_aligned_cifs': Value('int64'), 'ok_rows': Value('int64'), 'out': Value('string'), 'rows_by_ligand_set': {'activity_challenge': Value('int64'), 'pdb64': Value('int64'), 'structure_challenge': Value('int64')}, 'selected_rows': Value('int64'), 'sha256_entries': Value('int64'), 'sha256sums': Value('string'), 'source_repo': Value('string'), 'source_revision': Value('string'), 'total_bytes_in_output_dir': Value('int64'), 'unique_aligned_cif_names': Value('int64'), 'written_rows': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
columns: int64
critical_nonmissing_counts: struct<cofold_aggregate_score: int64, cofold_confidence: int64, cofold_iptm: int64, cofold_primary_s (... 159 chars omitted)
child 0, cofold_aggregate_score: int64
child 1, cofold_confidence: int64
child 2, cofold_iptm: int64
child 3, cofold_primary_score: int64
child 4, cofold_ptm: int64
child 5, structure_anchor_contact_pass: int64
child 6, structure_contact_atom_pairs_4p5a: int64
child 7, structure_min_ligand_protein_distance_a: int64
csv_path: string
data_dictionary_csv: string
data_dictionary_sha256: string
derived_has_structural_features_counts: struct<true: int64>
child 0, true: int64
hf_upload_layout: string
primary_score_source_counts: struct<aggregate_score: int64, confidence_score: int64, iptm: int64>
child 0, aggregate_score: int64
child 1, confidence_score: int64
child 2, iptm: int64
remote_aligned_cif_relpath_missing_count: int64
rows: int64
rows_by_consolidated_method_setup: struct<boltz2::boltz2_no_template: int64, boltz2::boltz2_self_template: int64, boltz::boltz_no_templ (... 221 chars omitted)
child 0, boltz2::boltz2_no_template: int64
child 1, boltz2::boltz2_self_template: int64
child 2, boltz::boltz_no_template: int64
child 3, chai1::chai1_msa: int64
child 4, chai1::chai1_no_template: int64
child 5, chai1::chai1_self_template: int64
child 6, openfold3::openfold3_msa: int64
child 7, openfold3::openfold3_no_template: int64
child 8, openfold3::openfold3_self_template: int64
...
2_no_template: int64, boltz2::boltz2_self_template: int64, boltz::boltz_no_templ (... 253 chars omitted)
child 0, boltz2::boltz2_no_template: int64
child 1, boltz2::boltz2_self_template: int64
child 2, boltz::boltz_no_template: int64
child 3, chai1::chai1_msa_seed11_25_50_67: int64
child 4, chai1::chai1_no_template: int64
child 5, chai1::chai1_self_template: int64
child 6, openfold3::openfold3_msa_seed11_25_50_67: int64
child 7, openfold3::openfold3_no_template: int64
child 8, openfold3::openfold3_self_template: int64
seed_list_rows_remaining_in_consolidated_setup_labels: int64
sha256: string
sha256sums_entries_regenerated: int64
unique_canonical_cif_names: int64
unique_structure_ids: int64
out: string
canonical_filename_precheck_unique: bool
total_bytes_in_output_dir: int64
ok_rows: int64
collation_status_counts: struct<ok: int64>
child 0, ok: int64
duplicate_cif_names: int64
sha256_entries: int64
source_revision: string
sha256sums: string
alignment_status_counts: struct<aligned: int64, reference_first_structure: int64>
child 0, aligned: int64
child 1, reference_first_structure: int64
cofolding_info_rows: int64
unique_aligned_cif_names: int64
selected_rows: int64
source_repo: string
cif_counts_by_consolidated_dir: struct<activity_challenge: int64, pdb64: int64, structure_challenge: int64>
child 0, activity_challenge: int64
child 1, pdb64: int64
child 2, structure_challenge: int64
missing_aligned_cifs: int64
failed_rows: int64
written_rows: int64
to
{'alignment_status_counts': {'aligned': Value('int64'), 'reference_first_structure': Value('int64')}, 'canonical_filename_precheck_unique': Value('bool'), 'cif_counts_by_consolidated_dir': {'activity_challenge': Value('int64'), 'pdb64': Value('int64'), 'structure_challenge': Value('int64')}, 'cofolding_info_rows': Value('int64'), 'collation_status_counts': {'ok': Value('int64')}, 'duplicate_cif_names': Value('int64'), 'failed_rows': Value('int64'), 'missing_aligned_cifs': Value('int64'), 'ok_rows': Value('int64'), 'out': Value('string'), 'rows_by_ligand_set': {'activity_challenge': Value('int64'), 'pdb64': Value('int64'), 'structure_challenge': Value('int64')}, 'selected_rows': Value('int64'), 'sha256_entries': Value('int64'), 'sha256sums': Value('string'), 'source_repo': Value('string'), 'source_revision': Value('string'), 'total_bytes_in_output_dir': Value('int64'), 'unique_aligned_cif_names': Value('int64'), 'written_rows': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PXR Challenge Multi-method Cofolding
This dataset contains >45,000 cofolding predictions using three different methods (OpenFold3, Boltz2, Chai1) for the nuclear hormone receptor hPXR and with >600 ligands. Ligands are derived from the OpenADMET PXR Challenge and contain known binders, known agonists, and inactives. More on the ligand set can be found here: https://huggingface.co/spaces/openadmet/pxr-challenge
Each cofolding method was run using default settings and untemplated, except where noted. Each protein/ligand/method/parameter set generated 20-25 structures (5 samples * 4 or 5 random seeds)
Deposited is the raw cofolding output with all confidence predictions and other data files.
Contents:
input_data: raw SMILES tables, PDB64 rerefined input structures, hPXR LBD sequence, and ColabFold MSA used for all cofolding runs.pdb64: cofolding predictions for a 70-system rerefined PXR crystal set. Untemplated and templated with the protein crystal coordinates.structure_challenge: cofolding predictions and inputs for 184 structure-challenge ligands.activity_challenge: cofolding predictions for 513 activity-challenge ligands.consolidated: Extracted and aligned .cif files from all cofolding runs. A .csv file with various structure and cofolding-based features for each sample.
Top-level metadata:
dataset_manifest.csv: dataset/archive summary.checksums.sha256: SHA256 checksums for repository files, excluding itself and.gitattributes.*/manifests/*/model_manifest.csv: row-level prediction manifests.*/manifests/*/archive_inventory.csv: complete file inventories for prediction/input archives.
Data to be deposited soon:
- 120 ligands with high-quality hPXR activity values of various ranges
- PXR cofolding with multiple copies of ligand (structure and activity sets)
- Downloads last month
- 3,831