PISCES-CulledPDB database as of January 2026

Recurated on Hugging Face on March 5th 2026

The PISCES dataset provides curated sets of protein sequences from the Protein Data Bank (PDB) based on sequence identity and structural quality criteria. PISCES yields non-redundant subsets of protein chains by applying filters such as sequence identity, experimental resolution, R-factor, chain length, and experimental method (e.g., X-ray, NMR, cryo-EM). The goal is to maximize structural reliability while minimizing sequence redundancy. Unlike culling tools that rely on BLAST or global alignments, PISCES uses PSI-BLAST for position-specific scoring matrices, improving detection of homologs below 40% sequence identity.

Dataset sources

• Server: PISCES
• Reference: Wang, G., & Dunbrack, R. L. Jr. (2003). Bioinformatics 19(12), 1589–1591.

Citation

@article{wang2003pisces,
  title={PISCES: a protein sequence culling server},
  author={Wang, Guoying and Dunbrack, Roland L. Jr.},
  journal={Bioinformatics},
  volume={19},
  number={12},
  pages={1589--1591},
  year={2003},
  publisher={Oxford University Press}
}

Recurated for Hugging Face by Akshaya Narayanasamy akshayanarayanasamy[at]gmail.com.

Uses

• Non-redundant protein chain datasets for ML and statistical analysis
• Benchmarking protein structure prediction or homology modeling
• Studying evolutionary relationships at chosen sequence identity thresholds
• High-quality training sets filtered by resolution and R-factor
• Structure-based ML datasets for protein modeling

Dataset structure

Item	Description
Main CSV	curated_csv/cullpdb_combined_chains.csv — full chain table
Subsets	curated_csv/subsets/*.csv — 242 files (same columns)
Index	curated_csv/cullpdb_list_fasta_index.csv

Subset paths: curated_csv/dataset_metadata.json (keys data_paths, subset_paths).

Columns (chain CSVs)

Column	Description
pdb_chain	PDB chain ID (e.g. 1ABC_A)
pdb	PDB ID (first 4 chars)
chain	Chain ID
sequence	Amino acid sequence (one-letter)
len	Sequence length
method	Experimental method (e.g. XRAY, NMR)
resolution	Resolution in Å
rfac	R-factor
freerfac	Free R-factor
pc	Sequence identity cutoff % for this subset
no_breaks	Whether chain has no breaks (yes/no)
R	R-factor cutoff for this subset
source_list	Subset list basename (curation parameters)

Usage

from huggingface_hub import hf_hub_download
import pandas as pd

path = hf_hub_download(
    repo_id="RosettaCommons/PISCES-CulledPDB",
    filename="curated_csv/cullpdb_combined_chains.csv",
    repo_type="dataset"
)
df = pd.read_csv(path)

File naming convention

Subset filenames follow:

cullpdb_pc{pc}_res{res_min}-{res_max}[_noBrks]_len40-10000_R{R}_{methods}_d2026_01_26_chains{N}.csv

Parameter	Meaning
pc	Percent sequence identity cutoff (15, 20, …, 95)
res	Resolution range in Å (e.g. 0.0-1.0, 0.0-2.5)
noBrks	Optional: exclude chains with breaks
R	R-factor cutoff (0.2, 0.25, 0.3, 1.0)
methods	Xray, Xray+EM, or Xray+Nmr+EM
N	Number of chains in the list

License

Apache-2.0