The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
FlowPacker: protein side-chain packing with torsional flow matching
Open accessPublished version of a preprint
Abstract
Motivation: Accurate prediction of protein side-chain conformations is necessary to understand protein folding, protein–protein interactions and facilitate de novo protein design. Results: Here, we apply torsional flow matching and equivariant graph attention to develop FlowPacker, a fast and performant model to predict protein side-chain conformations conditioned on the protein sequence and backbone. We show that FlowPacker outperforms previous state-of-the-art baselines across most metrics with improved runtime. We further show that FlowPacker can be used to inpaint missing side-chain coordinates and also for multimeric targets, and exhibits strong performance on a test set of antibody–antigen complexes. Availability and implementation: Code is available at https://gitlab.com/mjslee0921/flowpacker.
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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
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · doi:10.1101/2022.12.09.519842 · Cited by 2,369
De novo design of protein structure and function with RFdiffusion
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature · doi:10.1038/s41586-023-06415-8 · Cited by 2,325
The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design
Alford, R. F., Leaver-Fay, A., Jeliazkov, J. R., O’Meara, M. J., DiMaio, F. P., Park, H., Shapovalov, M. V., Renfrew, P. D., Mulligan, V. K., Kappel, K., et al. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00125 · Cited by 1,532
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Dao, T., Fu, D. Y., Ermon, S., Rudra, A., & Ré, C. (2022) · arXiv · doi:10.48550/arxiv.2205.14135 · Cited by 1,214
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Rafailov, R., Sharma, A., Mitchell, E., Ermon, S., Manning, C. D., & Finn, C. (2023) · arXiv · doi:10.48550/arxiv.2305.18290 · Cited by 293
Flow Matching for Generative Modeling
Lipman, Y., Chen, R. T. Q., Ben-Hamu, H., Nickel, M., & Le, M. (2022) · arXiv · doi:10.48550/arxiv.2210.02747 · Cited by 192
ProteinSGM: Score-based generative modeling for de novo protein design
Lee, J. S., Kim, J., & Kim, P. M. (2022) · doi:10.1101/2022.07.13.499967 · Cited by 94
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Research works printed but not linked: 10
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Metadata
- Authors
- Lee, J. S., & Kim, P. M.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Kim, Philip M
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2025-01-09
- Volume
- 41
- Issue
- 3
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC11886813
- OpenAlex
- W4406213027
- Cited by
- 8
- References
- 9
- Citations by year
- 2026: 5 · 2025: 3
- FWCI
- 2.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Canadian Institutes of Health Research (PJT-166008)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- protein folding, de novo protein design, multimeric proteins, immune complexes
- MeSH terms
- Algorithms, Antigen-Antibody Complex, Models, Molecular, Protein Conformation, Proteins, Software, Protein Folding, Computational Biology
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