ArticleProtein science : a publication of the Protein Society2026
When can AlphaFold predict the oligomeric states of proteins?
Article in Protein science : a publication of the Protein Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- AnThe Journal of general virology · 2026Article
- A functional atlas of transposon-encoded products and their integration into host networks.Nature communications · 2026Article
- When can AlphaFold predict the oligomeric states of proteins?Protein science : a publication of the Protein Society · 2026Article
- Comprehensive Biophysical Profiling Evidences Self-Oligomerization of Bacterially Expressed Pc Protein.Chembiochem : a European journal of chemical biology · 2026Article
- Computational prediction resolves thousands of homooligomeric phage protein structures.bioRxiv : the preprint server for biology · 2026Article
- Bromodomain dimers: A case study of BRD4 and family-wide AlphaFold predictions.Structural dynamics (Melville, N.Y.) · 2026Article
- The transformative power of structural predictions with AI in plant science.The Plant journal : for cell and molecular biology · 2026Review
- Oligomerization and exocyst coupling underlie Spa2-mediated focusing of polarized growth in fission yeast.Journal of cell science · 2025Article
- The iron metalloproteome of Pseudomonas aeruginosa under oxic and anoxic conditions.Metallomics : integrated biometal science · 2025Article
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Authors and funding
3 authors.
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Abstract
Homooligomerisation is a prevalent and important process that many proteins undergo to form the quaternary structures required for biological function. However, determining oligomeric states and structures experimentally remains technically challenging and time-consuming for many proteins. Here, we show that the protein structure prediction tools AlphaFold2-Multimer and AlphaFold3 can be used to quickly and accurately predict oligomeric states and structures for a range of soluble and membrane proteins. Across over 4700 proteins, AlphaFold2-Multimer provides reliable oligomeric state predictions in the majority of cases, however accuracy is more limited for proteins lacking close structural representatives in the AlphaFold training set, highlighting the dependence of these methods on robust training data. Together, our results suggest both the utility and current limitations of AlphaFold-based oligomeric state prediction, highlight cases where multiple physiologically relevant assemblies may be plausible, and provide practical guidance for minimizing computational cost, identifying challenging cases, and applying these methods to proteins lacking experimental structural data.
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