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Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches

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  • Tobias Sikosek
  • Heinrich Krobath
  • Hue Sun Chan

Abstract

Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a protein’s folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the GA all-α and GB α+β folds is extensively characterized; but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between GA and GB. In agreement with experiment, we observe conformational switching from GA to GB upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp GA/GB switch may arise from the orientation dependence of aromatic π-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches.Author Summary: The biological functions of globular proteins are intimately related to their folded structures and their associated conformational fluctuations. Evolution of new structures is an important avenue to new functions. Although many mutations do not change the folded state, experiments indicate that a single amino acid substitution can lead to a drastic change in the folded structure. The physics of this switch-like behavior remains to be elucidated. Here we develop a computational model for the relevant physical forces, showing that mutations can lead to new folds by passing through intermediate sequences where the old and new folds occur with varying probabilities. Our approach helps provide a general physical account of conformational switching in evolution and mutational effects on conformational dynamics.

Suggested Citation

  • Tobias Sikosek & Heinrich Krobath & Hue Sun Chan, 2016. "Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-27, June.
  • Handle: RePEc:plo:pcbi00:1004960
    DOI: 10.1371/journal.pcbi.1004960
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    References listed on IDEAS

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    1. Tobias Sikosek & Erich Bornberg-Bauer & Hue Sun Chan, 2012. "Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts," PLOS Computational Biology, Public Library of Science, vol. 8(9), pages 1-17, September.
    2. Guillaume Bouvignies & Pramodh Vallurupalli & D. Flemming Hansen & Bruno E. Correia & Oliver Lange & Alaji Bah & Robert M. Vernon & Frederick W. Dahlquist & David Baker & Lewis E. Kay, 2011. "Solution structure of a minor and transiently formed state of a T4 lysozyme mutant," Nature, Nature, vol. 477(7362), pages 111-114, September.
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    Cited by:

    1. Devlina Chakravarty & Shwetha Sreenivasan & Liskin Swint-Kruse & Lauren L. Porter, 2023. "Identification of a covert evolutionary pathway between two protein folds," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Pengfei Tian & Robert B Best, 2020. "Exploring the sequence fitness landscape of a bridge between protein folds," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-19, October.

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