Coevolution-based prediction of key allosteric residues for protein function regulation
Abstract
Allostery is fundamental to many biological processes. Due to the distant regulation nature, how allosteric mutations, modifications and effector binding impact protein function is difficult to forecast. In protein engineering, remote mutations cannot be rationally designed without large-scale experimental screening. Allosteric drugs have raised much attention due to their high specificity and possibility of overcoming existing drug-resistant mutations. However, optimization of allosteric compounds remains challenging. Here, we developed a novel computational method KeyAlloSite to predict allosteric site and to identify key allosteric residues (allo-residues) based on the evolutionary coupling model. We found that protein allosteric sites are strongly coupled to orthosteric site compared to non-functional sites. We further inferred key allo-residues by pairwise comparing the difference of evolutionary coupling scores of each residue in the allosteric pocket with the functional site. Our predicted key allo-residues are in accordance with previous experimental studies for typical allosteric proteins like BCR-ABL1, Tar and PDZ3, as well as key cancer mutations. We also showed that KeyAlloSite can be used to predict key allosteric residues distant from the catalytic site that are important for enzyme catalysis. Our study demonstrates that weak coevolutionary couplings contain important information of protein allosteric regulation function. KeyAlloSite can be applied in studying the evolution of protein allosteric regulation, designing and optimizing allosteric drugs, performing functional protein design and enzyme engineering.
Data availability
All data that support the results of this study are included in the manuscript, supplementary files, and GitHub repository(https://github.com/huilan1210/KeyAlloSite). Source Data files have been provided for all Figures(except Figure 6 and Figure 1-figure supplement 1).
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ASBench: benchmarking sets for allosteric discoveryASBench, http://mdl.shsmu.edu.cn/asbench.
Article and author information
Author details
Funding
National Key R&D Program of China (2022YFA1303700)
- Luhua Lai
National Natural Science Foundation of China (21633001,22237002)
- Luhua Lai
Chinese Academy of Medical Sciences (2021-I2M-5-014)
- Luhua Lai
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Shozeb Haider, University College London, United Kingdom
Version history
- Received: July 13, 2022
- Preprint posted: July 26, 2022 (view preprint)
- Accepted: February 16, 2023
- Accepted Manuscript published: February 17, 2023 (version 1)
- Version of Record published: March 2, 2023 (version 2)
Copyright
© 2023, Xie et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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