Datasets:

Knlife
/

SwiwwProtIPG

This repository provides benchmark datasets for protein function evaluation, constructed from UniProt/SwissProt, InterPro (IPR), and Gene Ontology (GO).
It includes both test sets and training sets, supporting keyword-guided and description-guided protein design/evaluation tasks.

📖 Dataset Overview

Keyword-guided protein tasks previously lacked a publicly available, high-quality evaluation dataset. To address this gap, we curated a novel dataset from SwissProt, together with their IPR entries and GO terms. Note that the GO terms are restricted to Molecular Function (MF).

Subset	Num of Proteins	Num of IPR entries	Num of GO terms
Test Set	1,057	1,297	380
Train Set	555543	39431	8110

🔧 Dataset Construction

Protein selection Extracted proteins from UniProt/SwissProt released between 2025-01-01 and 2025-08-25 for testing. The remaining proteins are used for training.
Keyword collection Retrieved corresponding protein sequences, InterPro IDs, and GO terms.
Instruction construction for description-guided task Following Mol-Instructions, we concatenated text descriptions of InterPro entries and GO terms to form natural-language prompts.

Keyword	Description
InterPro (Domain)	The protein should contain one or more {} that are essential for its biological function
InterPro (Family)	The protein should belong to {} that shares evolutionary origin and functional similarity
InterPro (Homologous_Superfamily)	The protein should be classified within {} sharing conserved structural features
InterPro (Repeat)	The protein should include one or more {} that provide structural or functional support
InterPro (Conserved_Site)	The protein should contain {} that is preserved across related proteins
InterPro (Active_Site)	The protein must have {} that is conserved among related catalytic enzymes
InterPro (Binding_Site)	The protein should include a {} that enables ligand binding under diverse conditions
InterPro (PTM)	The protein should contain {} that allow regulation through chemical modifications
Gene Ontology (molecular function)	The protein must be able to perform the {} required for its activity.

Final curation Curated into test and train sets with consistent formats.

📂 Dataset Structure

File	Func-Seq Pairs	Description
`go_test.json`	693	Test set for GO task.
`go_train.json`	492124	Train set for GO task.
`ipr_test.json`	870	Test set for IPR task.
`ipr_train.json`	555543	Train set for IPR task.
`ipr_go_test.json`	674	Test set for IPR&GO task.
`ipr_go_train.json`	487848	Train set for IPR&GO task.
`SwissIPG.py`	-	Building Class

🎯 Intended Use

Benchmarking protein design models under keyword-guided and description-guided settings
Training and fine-tuning models using consistent annotation standards
Facilitating fair comparison across models through a unified dataset

🔍 Evaluation Metrics

Our work, PDFBench, provides a comprehensive evaluation for both tasks. For further details, please refer to the repository.

📑 Citation

If you use this dataset, please cite:

@misc{kuang2025pdfbenchbenchmarknovoprotein,
      title={PDFBench: A Benchmark for De novo Protein Design from Function}, 
      author={Jiahao Kuang and Nuowei Liu and Changzhi Sun and Tao Ji and Yuanbin Wu},
      year={2025},
      eprint={2505.20346},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2505.20346}, 
}