OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow
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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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Cites
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 · see citing works
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
Wang, S., Sun, S., Li, Z., Zhang, R., & Xu, J. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005324 · Cited by 931 · see citing works
Zhou, H., & Zhou, Y. (2002) · Protein Science · doi:10.1110/ps.0217002 · Cited by 902 · see citing works
Haas, J., Barbato, A., Behringer, D., Studer, G., Roth, S., Bertoni, M., Mostaguir, K., Gumienny, R., & Schwede, T. (2018) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.25431 · Cited by 168 · see citing works
Giri, N., Roy, R. S., & Cheng, J. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102536 · Cited by 59 · see citing works
Xu, G., Wang, Q., & Ma, J. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbab529 · Cited by 24 · see citing works
Self-citationOPUS-Mut: Studying the Effect of Protein Mutation through Side-Chain Modeling
Xu, G., Wang, Q., & Ma, J. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00847 · Cited by 12 · see citing works
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- Authors
- Xu, G., Luo, Z., Zhou, R., Wang, Q., & Ma, J.
- Affiliations
- Fudan University (CN)
- Zhejiang University (CN)
- Harcam Biomedicines Center for Biomolecular Innovation, , Shanghai, 200131 , China
- Corresponding author
- Ma, Jianpeng
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-09-22
- Volume
- 24
- Issue
- 6
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W4387637087
- Cited by
- 1
- References
- 7
- 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
- Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study (SN-ZJU-SIAS-003)
- Shanghai Artificial Intelligence Lab (P22KN00272, P22KN00271)
- National Center of Technology Innovation for Biopharmaceuticals (NCTIB2022HS02010)
- National Independent Innovation Demonstration Zone Shanghai Zhangjiang Major Projects (ZJZX2020014)
- National Natural Science Foundation of China (U1967217, 32300535)
- National Key R&D Program of China (2021YFF1200404, 2021YFA1201200)
- Shanghai Municipal Science and Technology Major (2018SHZDZX01)
- National Key Research and Development Program of China (. 2021YFF1200400)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › 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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