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Peer-reviewedCC BYProtein Science

When can AlphaFold predict the oligomeric states of proteins?

  • Yiechang Lin1
  • Ciara Wallis1
  • Ben Corry1
  1. 1Research School of Biology The Australian National University Canberra Australian Capital Territory Australia
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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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Cite

BibTeXRIS
BibTeX
@article{lin2026when,
  title = {{When can AlphaFold predict the oligomeric states of proteins?}},
  author = {Yiechang Lin and Ciara Wallis and Ben Corry},
  journal = {Protein Science},
  year = {2026},
  month = jun,
  doi = {10.1002/pro.70686},
  url = {https://doi.org/10.1002/pro.70686},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - When can AlphaFold predict the oligomeric states of proteins?
AU  - Yiechang Lin
AU  - Ciara Wallis
AU  - Ben Corry
PY  - 2026
DA  - 2026/06/16
JO  - Protein Science
DO  - 10.1002/pro.70686
UR  - https://doi.org/10.1002/pro.70686
AB  - 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.
SN  - 0961-8368
SN  - 1469-896X
ER  -