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Proc Natl Acad Sci U S A. 2018 Apr 17;115(16):4164-4169. doi: 10.1073/pnas.1715896115. Epub 2018 Apr 2.

Structural dynamics is a determinant of the functional significance of missense variants.

Author information

1
Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261.
2
Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261 bahar@pitt.edu.

Abstract

Accurate evaluation of the effect of point mutations on protein function is essential to assessing the genesis and prognosis of many inherited diseases and cancer types. Currently, a wealth of computational tools has been developed for pathogenicity prediction. Two major types of data are used to this aim: sequence conservation/evolution and structural properties. Here, we demonstrate in a systematic way that another determinant of the functional impact of missense variants is the protein's structural dynamics. Measurable improvement is shown in pathogenicity prediction by taking into consideration the dynamical context and implications of the mutation. Our study suggests that the class of dynamics descriptors introduced here may be used in conjunction with existing features to not only increase the prediction accuracy of the impact of variants on biological function, but also gain insight into the physical basis of the effect of missense variants.

KEYWORDS:

elastic network models; machine learning; missense variants; structural dynamics

PMID:
29610305
PMCID:
PMC5910821
DOI:
10.1073/pnas.1715896115
[Indexed for MEDLINE]
Free PMC Article

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