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pretty_name: CATH Domain Classification
license: cc-by-4.0
tags:
- biology
- proteins
- protein-structure
- cath
- parquet
configs:
- config_name: default
data_files:
- split: train
path: data/train-*.parquet
- split: test
path: data/test-*.parquet
---
# CATH Domain Classification
CATH is a hierarchical classification database for protein domain structures, organizing domains by class, architecture, topology, and homologous superfamily.
## Splits
| Split | Rows |
|---|---:|
| train | 541,123 |
| test | 60,205 |
| total | 601,328 |
The split is deterministic and S35-cluster-aware: all domains sharing the same CATH homologous superfamily and S35 cluster key are kept in the same split. This avoids putting close S35-cluster relatives in both train and test.
## Dataset Statistics
| Metric | Value |
|---|---:|
| Domains | 601,328 |
| Unique S35 cluster keys | 37,350 |
| Unique homologous superfamilies | 6,630 |
| Unique topologies | 1,472 |
| Unique architectures | 43 |
| Train/test S35 cluster overlap | 0 |
| Unknown structure-resolution sentinel rows | 9,726 |
Class distribution:
| CATH class | Rows |
|---|---:|
| Alpha Beta | 305,361 |
| Mainly Beta | 158,943 |
| Mainly Alpha | 126,178 |
| Few Secondary Structures | 6,034 |
| Special | 4,812 |
Sequence length ranges from 9 to 1,275 amino acids, with a median length of 140.
## Load With `datasets`
```python
from datasets import load_dataset
ds = load_dataset("LiteFold/CATH")
print(ds)
train = ds["train"]
test = ds["test"]
print(train[0])
```
Load one split directly:
```python
from datasets import load_dataset
train = load_dataset("LiteFold/CATH", split="train")
test = load_dataset("LiteFold/CATH", split="test")
```
Stream rows without downloading the full dataset first:
```python
from datasets import load_dataset
streamed = load_dataset("LiteFold/CATH", split="train", streaming=True)
first_row = next(iter(streamed))
```
Filter to one of the CATH nonredundant representative subsets:
```python
from datasets import load_dataset
ds = load_dataset("LiteFold/CATH", split="train")
s35_train = ds.filter(lambda row: row["in_s35_nonredundant_subset"])
```
## Main Columns
| Column | Description |
|---|---|
| `domain_id` | CATH domain identifier, for example `1oaiA00`. |
| `pdb_id`, `chain_id`, `pdb_chain_id` | Parsed PDB and chain identifiers. |
| `cath_version` | CATH release version from the FASTA headers. |
| `cath_code` | Full CATH classification code at homologous superfamily level. |
| `class_*`, `architecture_*`, `topology_*`, `homologous_superfamily_*` | Numeric codes, full hierarchy codes, names, and example domains. |
| `s35_cluster_id`, `s60_cluster_id`, `s95_cluster_id`, `s100_cluster_id` | CATH sequence cluster identifiers from the domain list. |
| `s35_cluster_key` | Composite key used for leakage-aware splitting. |
| `domain_length` | Domain length from the CATH domain list. |
| `raw_structure_resolution_angstrom` | Original structure resolution value. |
| `structure_resolution_angstrom` | Resolution with CATH's `999.000` unknown sentinel converted to null. |
| `sequence` | Amino acid sequence from `cath-domain-seqs.fa`. |
| `sequence_length` | Length of `sequence`. |
| `sequence_range` | Source FASTA residue range, including discontinuous ranges such as `2-78_187-208`. |
| `sequence_range_start`, `sequence_range_end` | Parsed min start and max end residue positions when available. |
| `sequence_segment_count` | Number of underscore-separated residue segments in `sequence_range`. |
| `in_s35_nonredundant_subset`, `in_s60_nonredundant_subset`, `in_s95_nonredundant_subset`, `in_s100_nonredundant_subset` | Whether the domain appears in the corresponding CATH nonredundant subset list. |
## Source Files Used
- `cath-domain-list.txt`
- `cath-domain-list-S35.txt`
- `cath-domain-list-S60.txt`
- `cath-domain-list-S95.txt`
- `cath-domain-list-S100.txt`
- `cath-domain-seqs.fa`
- `cath-names.txt`
The raw PDB tarball remains in the repository, but it is not embedded in the Parquet table.
# Citation
```
@article{sillitoe2021cath,
title = {{CATH}: increased structural coverage of functional space},
author = {Sillitoe, Ian and Bordin, Nicola and Dawson, Natalie and others},
journal = {Nucleic Acids Research},
volume = {49},
number = {D1},
pages = {D266--D273},
year = {2021},
doi = {10.1093/nar/gkaa1079}
}
``` |