OPUS-Mut: studying the effect of protein mutation through side-chain modeling
Abstract
Predicting the effect of protein mutation is crucial in many applications such as protein design, protein evolution, and genetic disease analysis. Structurally, the 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 similar structure.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 12
- FWCI
- 0.98
- Field percentile
- top 29%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Studying protein-protein interaction through side-chain modeling method OPUS-Mut
Gang Xu, Yilin Wang, … Jianpeng Ma·Briefings in BioinformaticsPeer-reviewed·Aug 12, 2022
- Accurate Mutation Effect Prediction using RoseTTAFold
S. Mansoor, M. Baek, … D. Baker·bioRxiv·Nov 4, 2022
- MutaStruct: Revisiting Benchmarks for Single-Site Mutation-Induced Structural Change Prediction
Huynh Tan-Phat, Dang-Manh Ho, … Truong Son Hy·bioRxiv·Oct 22, 2026
- Missense mutations: Backbone structure positional effects
Raul Ivan Perez Martell, Ulrike Stege, Hosna Jabbari·bioRxiv·Dec 23, 2024
- Using AlphaFold2 to Predict the Conformations of Side Chains in Folded Proteins
Gia G. Maisuradze, Abhishek Thakur, … Ronald M. Levy·bioRxiv·Feb 10, 2025
- Rapid sequence-based screening of structure-disrupting protein mutations
Jaemin Oh, Xiaoning Qian, Byung-Jun Yoon·bioRxiv·Feb 25, 2026