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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Rare variants in the cardiac potassium channel K V 7.1 (KCNQ1) and sodium channel Na V 1.5 (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 Na V 1.5 (n = 356) and K V 7.1 (n = 144) variants with in vitro characterized channel currents gathered from the literature. Here we investigated the ability to predict commonly reported Na V 1.5 and K V 7.1 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 Na V 1.5 peak current (adj. R 2 = 0.27) and K V 7.1 + KCNE1 half-maximal voltage of activation (adj. R 2 = 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.

Original languageEnglish (US)
Pages (from-to)206-214
Number of pages9
JournalComputational and Structural Biotechnology Journal
Volume17
DOIs
StatePublished - 2019

Keywords

  • And protein function
  • Function prediction
  • KCNQ1
  • Protein structure
  • SCN5A

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

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