Modeling Alternate Conformations with Alphafold2 via Modification of the Multiple Sequence Alignment
Open accessPreprint — published as 10.1371/journal.pcbi.1010483 · Paper page
Abstract
The unprecedented performance of Deepmind’s Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes is reshaping structural biology. Moreover, the availability of Alphafold2’s architecture and code has stimulated a number of questions on how to harness the capabilities of this remarkable tool. A question of central importance is whether Alphafold2’s architecture is amenable to predict the intrinsic conformational heterogeneity of proteins. A general approach presented here builds on a simple manipulation of the multiple sequence alignment, via in silico mutagenesis, and subsequent modeling by Alphafold2. The approach is based in the concept that the multiple sequence alignment encodes for the structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations and potentially structural alterations due to point mutations. This modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design.
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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
Impact of protein conformational diversity on AlphaFold predictions
Saldaño, T., Escobedo, N., Marchetti, J., Zea, D. J., Mac Donagh, J., Velez Rueda, A. J., Gonik, E., Melani, A. G., Novomisky Nechcoff, J., Salas, M. N., et al. (2021) · doi:10.1101/2021.10.27.466189 · Cited by 196 · cited 1× · see citing works
“A recent report examining a curated subset of apo and ligand bound structures 302 suggested that pLDDT values infer local conformational changes.(31) The results presented here do not 303 suggest that these regions of low confidence are incorrect in their two- or three-dimensional structure, 304 but appear to be regio…”
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Predicting multiple conformations via sequence clustering and AlphaFold2
Wayment-Steele, H. K., Ojoawo, A., Otten, R., Apitz, J. M., Pitsawong, W., Hömberger, M., Ovchinnikov, S., Colwell, L., & Kern, D. (2024) · Nature · doi:10.1038/s41586-023-06832-9 · Cited by 545 · see citing works
- Authors
- Stein, R. A., & Mchaourab, H. S.
- Affiliations
- Vanderbilt University (US)
- Corresponding author
- Stein, Richard A.
- Venue
- PLoS Computational Biology
- Publisher
- openRxiv
- Published
- 2021-11-29
- Volume
- 18
- Issue
- 8
- Pages
- e1010483-e1010483
- ISSN
- 1553-734X (ISSN-L)
- PMC
- PMC9436118
- OpenAlex
- W4292636432
- Cited by
- 258
- References
- 2
- Citations by year
- 2026: 55 · 2025: 64 · 2024: 76 · 2023: 51 · 2022: 12
- FWCI
- 16.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (GM077659)
- National Institute of General Medical Sciences (R01GM077659, R01GM128087)
- 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
- AlphaFold2, protein conformational heterogeneity, protein ensembles, multiple sequence alignment, in silico mutagenesis, protein flexibility, membrane proteins, conformational landscape, structure-based drug design, protein structure prediction
- MeSH terms
- Amino Acid Sequence, Protein Conformation, Proteins, Drug Design, Sequence Alignment
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