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OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow
Open accessPreprint — published as 10.1093/bib/bbad365 · Paper page
Abstract
For refining and designing protein structures, it is essential to have an efficient protein folding and docking framework that generates a protein 3D structure based on given constraints. In this study, we introduce OPUS-Fold3 as a gradient-based, all-atom protein folding and docking framework, which accurately generates 3D protein structures in compliance with specified constraints, such as a potential function as long as it can be expressed as a function of positions of heavy atoms. Our tests show that, for example, OPUS-Fold3 achieves performance comparable to pyRosetta in backbone folding, and significantly better in side-chain modeling. Developed using Python and TensorFlow 2.4, OPUS-Fold3 is user-friendly for any source-code level modifications and can be seamlessly combined with other deep learning models, thus facilitating collaboration between the biology and AI communities. The source code of OPUS-Fold3 can be downloaded from http://github.com/OPUS-MaLab/opus_fold3 . It is freely available for academic usage.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Metadata
- Authors
- Xu, G., Luo, Z., Zhou, R., Wang, Q., & Ma, J.
- Affiliations
- Fudan University (CN)
- Zhejiang University (CN)
- Corresponding author
- Ma, Jianpeng
- Venue
- Briefings in Bioinformatics
- Publisher
- openRxiv
- Published
- 2022-09-03
- Volume
- 24
- Issue
- 6
- ISSN
- 1467-5463 (ISSN-L)
- OpenAlex
- W4387637087
- Cited by
- 1
- References
- 1
- Citations by year
- 2025: 1
- FWCI
- 0.09
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Briefings in Bioinformatics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (U1967217, 32300535, 2018SHZDZX01)
- Zhejiang University (SN-ZJU-SIAS-003)
- National Key Research and Development Program of China (2021YFF1200400, 2018SHZDZX01, 2021YFA1201200, 2021YFF1200404)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- protein folding, protein docking, gradient-based optimization, TensorFlow, protein structure refinement, protein structure design, potential energy function
- MeSH terms
- Models, Molecular, Proteins, Software, Protein Folding
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