Can Predicted Protein 3D Structures Provide Reliable Insights into whether Missense Variants Are Disease Associated?

Authors:
Suhail A Islam
Suhail A Islam
Imperial College of Science
Tarun Khanna
Tarun Khanna
Harvard Business School
United States
Alessia David
Alessia David
William Harvey Research Institute
United Kingdom

J Mol Biol 2019 May 14;431(11):2197-2212. Epub 2019 Apr 14.

Structural Bioinformatics Group, Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Sir Ernst Chain Building, Imperial College London, London SW7 2AZ, UK. Electronic address:

Knowledge of protein structure can be used to predict the phenotypic consequence of a missense variant. Since structural coverage of the human proteome can be roughly tripled to over 50% of the residues if homology-predicted structures are included in addition to experimentally determined coordinates, it is important to assess the reliability of using predicted models when analyzing missense variants. Accordingly, we assess whether a missense variant is structurally damaging by using experimental and predicted structures. We considered 606 experimental structures and show that 40% of the 1965 disease-associated missense variants analyzed have a structurally damaging change in the mutant structure. Only 11% of the 2134 neutral variants are structurally damaging. Importantly, similar results are obtained when 1052 structures predicted using Phyre2 algorithm were used, even when the model shares low (<40%) sequence identity to the template. Thus, structure-based analysis of the effects of missense variants can be effectively applied to homology models. Our in-house pipeline, Missense3D, for structurally assessing missense variants was made available at http://www.sbg.bio.ic.ac.uk/~missense3d.

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Source
http://dx.doi.org/10.1016/j.jmb.2019.04.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544567PMC
May 2019

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