M-TASSER: An Algorithm for Protein Quaternary Structure Prediction
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In a cell, it has been estimated that each protein on average interacts with roughly 10 others, resulting in tens of thousands of proteins known or suspected to have interaction partners; of these, only a tiny fraction have solved protein structures. To partially address this problem, we have developed M-TASSER, a hierarchical method to predict protein quaternary structure from sequence that involves template identification by multimeric threading, followed by multimer model assembly and refinement. The final models are selected by structure clustering. M-TASSER has been tested on a benchmark set comprising 241 dimers having templates with weak sequence similarity and 246 without multimeric templates in the dimer library. Of the total of 207 targets predicted to interact as dimers, 165 (80%) were correctly assigned as interacting with a true positive rate of 68% and a false positive rate of 17%. The initial best template structures have an average root mean-square deviation to native of 5.3, 6.7, and 7.4 A for the monomer, interface, and dimer structures. The final model shows on average a root mean-square deviation improvement of 1.3, 1.3, and 1.5 A over the initial template structure for the monomer, interface, and dimer structures, with refinement evident for 87% of the cases. Thus, we have developed a promising approach to predict full-length quaternary structure for proteins that have weak sequence similarity to proteins of solved quaternary structure.
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Template-based methods for predicting protein complex structures utilize experimentally resolved multimeric structures.
“A second class of approaches is template-based methods, which utilize experimentally resolved multimeric structures12–16.”
From AF2Complex predicts direct physical interactions in multimeric proteins with deep learning (2022) · cites this paper as [13]
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- Authors
- Chen, H., & Skolnick, J.
- Affiliations
- Georgia Institute of Technology (US)
- Corresponding author
- Skolnick, Jeffrey
- Venue
- Biophysical Journal
- Publisher
- Elsevier BV
- Published
- 2008-02
- Volume
- 94
- Issue
- 3
- Pages
- 918-928
- ISSN
- 0006-3495 (ISSN-L)
- PMC
- PMC2186260
- OpenAlex
- W2010859992
- Cited by
- 68
- References
- 52
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 5 · 2022: 4 · 2021: 3 · 2020: 4 · 2019: 3 · 2018: 2 · 2017: 1 · 2016: 7 · 2015: 2 · 2014: 3 · 2013: 6 · 2012: 6
- FWCI
- 1.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Biophysical Journal (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- SMARTech Repository (Georgia Institute of Technology) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (GM-48835, R01GM048835)
- 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
- protein dimerization, structure refinement, structural clustering, protein-protein interaction
- MeSH terms
- Algorithms, Computer Simulation, Models, Chemical, Models, Molecular, Proteins, Software, Protein Structure, Quaternary
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