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Deep-Learning Structure Elucidation from Single-Mutant Deep Mutational Scanning
Open accessPreprint — published as 10.1038/s41467-025-62261-4
Abstract
Deep learning has revolutionized the field of protein structure prediction. AlphaFold2, a deep neural network, vastly outperformed previous algorithms to provide near atomic-level accuracy when predicting protein structures. Despite its success, there still are limitations which prevent accurate predictions for numerous protein systems. Here we show that sparse residue burial restraints from deep mutational scanning (DMS) can refine AlphaFold2 to significantly enhance results. Burial information extracted from DMS is used to explicitly guide residue placement during structure generation. DMS-Fold was validated on both simulated and experimental single-mutant DMS, with DMS-Fold outperforming AlphaFold2 for 89% of protein targets and with 253 proteins having an improvement greater than 0.1 in TM-score. DMS-Fold is free and publicly available: https://github.com/LindertLab/DMS-Fold .
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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
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Metadata
- Authors
- Drake, Z. C., Day, E., Toth, P., & Lindert, S.
- Affiliations
- University of California, Los Angeles (US)
- The Ohio State University (US)
- Corresponding author
- Lindert, Steffen
- Venue
- Nature Communications
- Publisher
- openRxiv
- Published
- 2024-05-19
- Volume
- 16
- Issue
- 1
- Pages
- 6874-6874
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC12297490
- OpenAlex
- W4412707732
- Cited by
- 10
- References
- 1
- Citations by year
- 2026: 6 · 2025: 2 · 2024: 2
- FWCI
- 2.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- protein structure prediction, deep mutational scanning, AlphaFold2, residue burial, TM-score, protein structure refinement
- MeSH terms
- Deep Learning, Algorithms, Models, Molecular, Mutation, Protein Conformation, Proteins, Protein Folding, Computational Biology
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