Evaluation of AlphaFold-Multimer prediction on multi-chain protein complexes
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Abstract
Motivation: Despite near-experimental accuracy on single-chain predictions, there is still scope for improvement among multimeric predictions. Methods like AlphaFold-Multimer and FoldDock can accurately model dimers. However, how well these methods fare on larger complexes is still unclear. Further, evaluation methods of the quality of multimeric complexes are not well established. Results: We analysed the performance of AlphaFold-Multimer on a homology-reduced dataset of homo- and heteromeric protein complexes. We highlight the differences between the pairwise and multi-interface evaluation of chains within a multimer. We describe why certain complexes perform well on one metric (e.g. TM-score) but poorly on another (e.g. DockQ). We propose a new score, Predicted DockQ version 2 (pDockQ2), to estimate the quality of each interface in a multimer. Finally, we modelled protein complexes (from CORUM) and identified two highly confident structures that do not have sequence homology to any existing structures. Availability and implementation: All scripts, models, and data used to perform the analysis in this study are freely available at https://gitlab.com/ElofssonLab/afm-benchmark.
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- Authors
- Zhu, W., Shenoy, A., Kundrotas, P., & Elofsson, A.
- Affiliations
- Stockholm University (SE)
- University of Kansas (US)
- Corresponding author
- Elofsson, Arne
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-07-01
- Volume
- 39
- Issue
- 7
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC10348836
- OpenAlex
- W4383216409
- Cited by
- 202
- References
- 9
- Citations by year
- 2026: 75 · 2025: 60 · 2024: 51 · 2023: 15 · 2022: 1
- FWCI
- 17.76
- 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)
- KU ScholarWorks (University of Kansas) (submittedVersion, cc-by)
- Funders
- Vetenskapsrådet (2021-03979)
- Knut and Alice Wallenberg Foundation
- 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
- AlphaFold-Multimer, protein complex structure prediction, user interface evaluation, TM-score
- MeSH terms
- Protein Conformation, Computational Biology
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