AlphaFold Prediction of Structural Ensembles of Disordered Proteins
Open accessPreprint — published as 10.1038/s41467-025-56572-9 · Paper page
Abstract
Deep learning methods of predicting protein structures have reached an accuracy comparable to that of high-resolution experimental methods. It is thus possible to generate accurate models of the native states of hundreds of millions of proteins. An open question, however, concerns whether these advances can be translated to disordered proteins, which should be represented as structural ensembles because of their heterogeneous and dynamical nature. Here we show that the inter-residue distances predicted by AlphaFold for disordered proteins can be used to construct accurate structural ensembles. These results illustrate the application to disordered proteins of deep learning methods originally trained for predicting the structures of folded proteins.
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Self-citation
- Authors
- Brotzakis, Z. F., Zhang, S., & Vendruscolo, M.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Vendruscolo, Michele
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2023-01-19
- OpenAlex
- W4317493265
- Cited by
- 22
- References
- 32
- Citations by year
- 2025: 4 · 2024: 10 · 2023: 8
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- UK Research and Innovation (10061100, 10059436)
- Bodossaki Foundation
- HORIZON EUROPE Framework Programme (101 087 471)
- 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
- AlphaFold, intrinsically disordered proteins, structural ensembles, protein structure prediction, deep learning, protein dynamics, ensemble construction
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