Protein structure aids predicting functional perturbation of missense variants in SCN5A and KCNQ1

Brett M. Kroncke; Jeffrey Mendenhall; Derek K. Smith; Charles R. Sanders; John A. Capra; Alfred L. George; Jeffrey D. Blume; Jens Meiler; Dan M. Roden

doi:10.1016/j.csbj.2019.01.008

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Protein structure aids predicting functional perturbation of missense variants in SCN5A and KCNQ1

Journal article

Peer reviewed

Protein structure aids predicting functional perturbation of missense variants in SCN5A and KCNQ1

Brett M. Kroncke, Jeffrey Mendenhall, Derek K. Smith, Charles R. Sanders, John A. Capra, Alfred L. George, Jeffrey D. Blume, Jens Meiler and Dan M. Roden

Computational and structural biotechnology journal, Vol.17, pp.206-214

01/01/2019

DOI: 10.1016/j.csbj.2019.01.008

PMCID: PMC6383132

PMID: 30828412

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Abstract

Rare variants in the cardiac potassium channel KV7.1 (KCNQ1) and sodium channel NaV1.5 (SCN5A) are implicated in genetic disorders of heart rhythm, including congenital long QT and Brugada syndromes (LQTS, BrS), but also occur in reference populations. We previously reported two sets of NaV1.5 (n = 356) and KV7.1 (n = 144) variants with in vitro characterized channel currents gathered from the literature. Here we investigated the ability to predict commonly reported NaV1.5 and KV7.1 variant functional perturbations by leveraging diverse features including variant classifiers PROVEAN, PolyPhen-2, and SIFT; evolutionary rate and BLAST position specific scoring matrices (PSSM); and structure-based features including “functional densities” which is a measure of the density of pathogenic variants near the residue of interest. Structure-based functional densities were the most significant features for predicting NaV1.5 peak current (adj. R2 = 0.27) and KV7.1 + KCNE1 half-maximal voltage of activation (adj. R2 = 0.29). Additionally, use of structure-based functional density values improves loss-of-function classification of SCN5A variants with an ROC-AUC of 0.78 compared with other predictive classifiers (AUC = 0.69; two-sided DeLong test p = .01). These results suggest structural data can inform predictions of the effect of uncharacterized SCN5A and KCNQ1 variants to provide a deeper understanding of their burden on carriers. [Display omitted]

And protein function

Function prediction

KCNQ1

Protein structure

SCN5A

Details

Title: Subtitle: Protein structure aids predicting functional perturbation of missense variants in SCN5A and KCNQ1
Creators: Brett M. Kroncke - Vanderbilt University Medical Center
Jeffrey Mendenhall - Vanderbilt University
Derek K. Smith - Vanderbilt University
Charles R. Sanders - Vanderbilt University
John A. Capra - Vanderbilt University
Alfred L. George - Northwestern University
Jeffrey D. Blume - Vanderbilt University
Jens Meiler - Vanderbilt University
Dan M. Roden - Vanderbilt University Medical Center
Resource Type: Journal article
Publication Details: Computational and structural biotechnology journal, Vol.17, pp.206-214
DOI: 10.1016/j.csbj.2019.01.008
PMID: 30828412
PMCID: PMC6383132
NLM abbreviation: Comput Struct Biotechnol J
ISSN: 2001-0370
eISSN: 2001-0370
Publisher: Elsevier B.V
Number of pages: 9
Language: English
Date published: 01/01/2019
Academic Unit: Preventive and Community Dentistry; Dental Research
Record Identifier: 9984966744902771

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