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Predicting the Effect of Mutations on Protein Folding and Protein-Protein Interactions

  • Alexey Strokach
  • Carles Corbi-Verge
  • Joan Teyra
  • Philip M. Kim
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1851)

Abstract

The function of a protein is largely determined by its three-dimensional structure and its interactions with other proteins. Changes to a protein’s amino acid sequence can alter its function by perturbing the energy landscapes of protein folding and binding. Many tools have been developed to predict the energetic effect of amino acid changes, utilizing features describing the sequence of a protein, the structure of a protein, or both. Those tools can have many applications, such as distinguishing between deleterious and benign mutations and designing proteins and peptides with attractive properties. In this chapter, we describe how to use one of such tools, ELASPIC, to predict the effect of mutations on the stability of proteins and the affinity between proteins, in the context of a human protein-protein interaction network. ELASPIC uses a wide range of sequential and structural features to predict the change in the Gibbs free energy for protein folding and protein-protein interactions. It can be used both through a web server and as a stand-alone application. Since ELASPIC was trained using homology models and not crystal structures, it can be applied to a much broader range of proteins than traditional methods. It can leverage precalculated sequence alignments, homology models, and other features, in order to drastically lower the amount of time required to evaluate individual mutations and make tractable the analysis of millions of mutations affecting the majority of proteins in a genome.

Key words

Computational biology Structural biology Bioinformatics Protein stability Mutations Protein engineering 

Notes

Acknowledgments

Funding: P.M.K. acknowledges support from a NSERC Discovery Grant (RGPIN-2017-064).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Alexey Strokach
    • 1
    • 2
  • Carles Corbi-Verge
    • 2
  • Joan Teyra
    • 2
  • Philip M. Kim
    • 1
    • 2
    • 3
  1. 1.Department of Computer ScienceUniversity of TorontoTorontoCanada
  2. 2.Terrence Donnelly Centre for Cellular and Biomolecular ResearchUniversity of TorontoTorontoCanada
  3. 3.Department of Molecular GeneticsUniversity of TorontoTorontoCanada

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