CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2
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Abstract
Deep learning models, such as AlphaFold2 and RosettaFold, enable high-accuracy protein structure prediction. However, large protein complexes are still challenging to predict due to their size and the complexity of interactions between multiple subunits. Here we present CombFold, a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise interactions between subunits predicted by AlphaFold2. CombFold accurately predicted (TM-score >0.7) 72% of the complexes among the top-10 predictions in two datasets of 60 large, asymmetric assemblies. Moreover, the structural coverage of predicted complexes was 20% higher compared to corresponding Protein Data Bank entries. We applied the method on complexes from Complex Portal with known stoichiometry but without known structure and obtained high-confidence predictions. CombFold supports the integration of distance restraints based on crosslinking mass spectrometry and fast enumeration of possible complex stoichiometries. CombFold’s high accuracy makes it a promising tool for expanding structural coverage beyond monomeric proteins.
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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
ColabFold - Making protein folding accessible to all
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Protein complex prediction with AlphaFold-Multimer
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Madaj, R., Martinez‐Goikoetxea, M., Kaminski, K., Ludwiczak, J., & Dunin‐Horkawicz, S. (2025) · Protein Science · doi:10.1002/pro.5244 · Cited by 23 · see citing works
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- Authors
- Shor, B., & Schneidman-Duhovny, D.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Venue
- Nature Methods
- Published
- 2024-02-07
- Volume
- 21
- Issue
- 3
- Pages
- 477-487
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC10927564
- OpenAlex
- W4391604520
- Cited by
- 85
- References
- 6
- Citations by year
- 2026: 24 · 2025: 35 · 2024: 24 · 2023: 2
- FWCI
- 11.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Methods (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by)
- Funders
- Israel Science Foundation (1466/18)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- large protein complexes, protein complex structure prediction, hierarchical assembly, AlphaFold2, complex stoichiometry, structural coverage
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