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• W4280497674 abstract "Abstract Computationally modeling how mutations affect protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein-protein interactions. Traditional high-throughput methods for estimating binding free energies are currently limited to mutations directly at the interface due to difficulties in accurately modeling how more distant allosterically acting mutations propagate their effects through the protein structure. However, the modeling and design of such allosteric mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict allosterically acting mutational perturbations to protein binding. Our approach uses an analytical framework grounded in rigorous alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict allosteric perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of non-allosteric interface mutations. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions. Author Summary Protein-protein interactions are vital to almost all biological processes, and therefore the ability to accurately and efficiently predict how mutations alter protein binding has far-reaching applications in protein analysis and design. Current approaches to predict such mutational free energy changes are limited to mutations directly at the interaction interface. Much research has underlined the prevalence of allosteric protein regulation in biological processes, indicating the importance of understanding and predicting the effects of mutations which act over long distances. In this work we develop a novel method based on theoretically rigorous alchemical free energy calculations and the Rosetta macromolecular modeling suite which can predict the effects of allosteric mutations with levels of accuracy rivaling state of the art interface-specific methods. We hope that our method will serve as a novel framework for high-throughput allosteric mutational analysis and therefore benefit future protein design efforts." @default.
• W4280497674 created "2022-05-22" @default.
• W4280497674 creator A5023229392 @default.
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• W4280497674 date "2022-04-27" @default.
• W4280497674 modified "2023-10-15" @default.
• W4280497674 title "Prediction of allosterically acting mutations using MD simulations and Rosetta" @default.
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• W4280497674 doi "https://doi.org/10.1101/2022.04.26.489494" @default.
• W4280497674 hasPublicationYear "2022" @default.
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