OPUS-Mut: Studying the Effect of Protein Mutation through Side-Chain Modeling
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Abstract
Predicting the effect of protein mutation is crucial in many applications such as protein design, protein evolution, and genetic disease analysis. Structurally, mutation is basically the replacement of the side chain of a particular residue. Therefore, accurate side-chain modeling is useful in studying the effect of mutation. Here, we propose a computational method, namely, OPUS-Mut, which significantly outperforms other backbone-dependent side-chain modeling methods including our previous method OPUS-Rota4. We evaluate OPUS-Mut by four case studies on Myoglobin, p53, HIV-1 protease, and T4 lysozyme. The results show that the predicted structures of side chains of different mutants are consistent well with their experimentally determined results. In addition, when the residues with significant structural shifts upon the mutation are considered, it is found that the extent of the predicted structural shift of these affected residues can be correlated reasonably well with the functional changes of the mutant measured by experiments. OPUS-Mut can also help one to identify the harmful and benign mutations and thus may guide the construction of a protein with relatively low sequence homology but with a similar structure.
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- Authors
- Xu, G., Wang, Q., & Ma, J.
- Affiliations
- Fudan University (CN)
- Center for Biomolecular Innovation, Harcam Biomedicines, Shanghai 200131, China
- Corresponding author
- Ma, Jianpeng
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2023-02-22
- Volume
- 19
- Issue
- 5
- Pages
- 1629-1640
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- PMC
- PMC10018731
- OpenAlex
- W4321479867
- Cited by
- 12
- References
- 62
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 1 · 2022: 1
- FWCI
- 0.98
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Chemical Theory and Computation (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- Ministry of Science and Technology of the People's Republic of China (2021YFF1200400)
- Science and Technology Commission of Shanghai Municipality (2018SHZDZX01)
- ZJLab
- 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
- protein design, protein evolution, structural change, protein structure prediction, myoglobin, p53, HIV-1 protease, T4 lysozyme
- MeSH terms
- Models, Molecular, Mutation, Protein Conformation, Proteins
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