Improved protein complex prediction with AlphaFold-multimer by denoising the MSA profile
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Abstract
Structure prediction of protein complexes has improved significantly with AlphaFold2 and AlphaFold-multimer (AFM), but only 60% of dimers are accurately predicted. Here, we learn a bias to the MSA representation that improves the predictions by performing gradient descent through the AFM network. We demonstrate the performance on seven difficult targets from CASP15 and increase the average MMscore to 0.76 compared to 0.63 with AFM. We evaluate the procedure on 487 protein complexes where AFM fails and obtain an increased success rate (MMscore>0.75) of 33% on these difficult targets. Our protocol, AFProfile, provides a way to direct predictions towards a defined target function guided by the MSA. We expect gradient descent over the MSA to be useful for different tasks.
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HF3 w/ AFsample adopts a more sophisticated multi-setting approach according to the AlphaFold settings used in AFsample.
“Notably, the inference configuration for HF3 w/ AFsample adopts a more sophisticated multi-setting approach, according to the AlphaFold settings used in AFsample [12].”
From Reshaping biomolecular structure prediction through strategic conformational exploration with HelixFold-S1 (2026) · cites this paper as [12]
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Liu, L., Liu, Y., Ye, X., Zhang, S., Li, Y., Zhu, K., Xue, Y., Zhou, J., Zhang, X., & Fang, X. (2026) · Nature Machine Intelligence · doi:10.1038/s42256-026-01264-2 · Cited by 1 · see citing works
- Authors
- Bryant, P., & Noé, F.
- Affiliations
- Stockholm University (SE)
- Microsoft (United States) (US)
- Corresponding author
- Bryant, Patrick
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2024-07-25
- Volume
- 20
- Issue
- 7
- Pages
- e1012253
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC11302914
- OpenAlex
- W4400974946
- Cited by
- 53
- References
- 11
- Citations by year
- 2026: 15 · 2025: 25 · 2024: 8 · 2023: 5
- FWCI
- 6.51
- Type
- journal article
- Language
- en
- Update notices
- new_version (2024-08-06)
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Refubium (Universitätsbibliothek der Freien Universität Berlin) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Universitätsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver (cc-by)
- Funders
- FP7 Ideas: European Research Council (772230 “ScaleCell”)
- Berlin Mathematics Research Center MATH+ (AA1-6, AA1-10)
- Deutsche Forschungsgemeinschaft (SFB 1114/C03)
- SciLifeLab & Wallenberg Data Driven Life Science Program (KAW 2020.0239)
- Zentrum für Informationsdienste und Hochleistungsrechnen, Technische Universität Dresden (p_scads_protein_na)
- National Supercomputer Centre, Linköpings Universitet (Berzelius-2023-267)
- 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
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- protein complex structure prediction, AlphaFold-Multimer, multiple sequence alignment, CASP15
- MeSH terms
- Algorithms, Models, Molecular, Protein Conformation, Proteins, Protein Folding, Computational Biology, Multiprotein Complexes, Protein Multimerization
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