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Accurate Prediction of Protein Thermodynamic Stability Changes upon Residue Mutation using Free Energy Perturbation.
- Source :
-
Journal of molecular biology [J Mol Biol] 2022 Jan 30; Vol. 434 (2), pp. 167375. Date of Electronic Publication: 2021 Nov 23. - Publication Year :
- 2022
-
Abstract
- This work describes the application of a physics-based computational approach to predict the relative thermodynamic stability of protein variants, and evaluates the quantitative accuracy of those predictions compared to experimental data obtained from a diverse set of protein systems assayed at variable pH conditions. Physical stability is a key determinant of the clinical and commercial success of biological therapeutics, vaccines, diagnostics, enzymes and other protein-based products. Although experimental techniques for measuring the impact of amino acid residue mutation on the stability of proteins exist, they tend to be time consuming and costly, hence the need for accurate prediction methods. In contrast to many of the commonly available computational methods for stability prediction, the Free Energy Perturbation approach applied in this paper explicitly accounts for solvent effects and samples conformational dynamics using a rigorous molecular dynamics simulation process. On the entire validation dataset, consisting of 328 single point mutations spread across 14 distinct protein structures, our results show good overall correlation with experiment with an R <superscript>2</superscript> of 0.65 and a low mean unsigned error of 0.95 kcal/mol. Application of the FEP approach in conjunction with experimental assessment techniques offers opportunities to lower the time and expense of product development and reduce the risk of costly late-stage failures.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2021 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1089-8638
- Volume :
- 434
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Journal of molecular biology
- Publication Type :
- Academic Journal
- Accession number :
- 34826524
- Full Text :
- https://doi.org/10.1016/j.jmb.2021.167375