AlphaFold prediction of structural ensembles of disordered proteins
Open accessPublished version of a preprint
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. To address this problem, we introduce the AlphaFold-Metainference method to use AlphaFold-derived distances as structural restraints in molecular dynamics simulations to construct structural ensembles of ordered and disordered proteins. The results obtained using AlphaFold-Metainference illustrate the possibility of making predictions of the conformational properties of disordered proteins using deep learning methods trained on the large structural databases available for folded proteins.
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Self-citation
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- Authors
- Brotzakis, Z. F., Zhang, S., Murtada, M. H., & Vendruscolo, M.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Vendruscolo, Michele
- Venue
- Nature Communications
- Published
- 2025-02-14
- Volume
- 16
- Issue
- 1
- Pages
- 1632-1632
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC11829000
- OpenAlex
- W4407565291
- Cited by
- 99
- References
- 14
- Citations by year
- 2026: 58 · 2025: 41
- FWCI
- 29.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- UK Research and Innovation (10061100, 10059436)
- Bodossaki Foundation
- HORIZON EUROPE Framework Programme
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- intrinsically disordered proteins, structural ensembles, AlphaFold, protein structure prediction, molecular dynamics simulation, structural restraints, conformational heterogeneity, protein dynamics
- MeSH terms
- Deep Learning, Protein Conformation, Proteins, Protein Folding, Computational Biology, Databases, Protein, Molecular Dynamics Simulation, Intrinsically Disordered Proteins
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