Datasetpublic

AI4Protein/MetalIonBinding_AlphaFold2

MetalIonBinding Dataset with AlphaFold2 Structural Sequence Description: Metal-binding proteins are proteins or protein domains that chelate a metal ion. Number of labels: 2 Problem Type: single_label_classification Columns: aa_seq: protein amino acid sequence foldseek_seq: foldseek 20 3di structural sequence ss8_seq: DSSP 8 secondary structure sequence ss3_seq: DSSP 3 secondary structure sequence esm3_structure_seq: ESM3 structure sequence encoded by VQ-VAE… See the full description on the dataset page: https://huggingface.co/datasets/AI4Protein/MetalIonBinding_AlphaFold2.

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face

0likes108downloads

Dataset Card

MetalIonBinding Dataset with AlphaFold2 Structural Sequence

—Description: Metal-binding proteins are proteins or protein domains that chelate a metal ion.
—Number of labels: 2
—Problem Type: singlelabelclassification
—Columns:
—aa_seq: protein amino acid sequence
—foldseek_seq: foldseek 20 3di structural sequence
—ss8_seq: DSSP 8 secondary structure sequence
—ss3_seq: DSSP 3 secondary structure sequence
—esm3structureseq: ESM3 structure sequence encoded by VQ-VAE

Github

Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models

https://github.com/tyang816/SES-Adapter

VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning

https://github.com/ai4protein/VenusFactory

Citation

Please cite our work if you use our dataset.

@article{tan2024ses-adapter,
  title={Simple, Efficient, and Scalable Structure-Aware Adapter Boosts Protein Language Models},
  author={Tan, Yang and Li, Mingchen and Zhou, Bingxin and Zhong, Bozitao and Zheng, Lirong and Tan, Pan and Zhou, Ziyi and Yu, Huiqun and Fan, Guisheng and Hong, Liang},
  journal={Journal of Chemical Information and Modeling},
  year={2024},
  publisher={ACS Publications}
}

@article{tan2025venusfactory,
  title={VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning},
  author={Tan, Yang and Liu, Chen and Gao, Jingyuan and Wu, Banghao and Li, Mingchen and Wang, Ruilin and Zhang, Lingrong and Yu, Huiqun and Fan, Guisheng and Hong, Liang and Zhou, Bingxin},
  journal={arXiv preprint arXiv:2503.15438},
  year={2025}
}