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 language | English (US) |
---|---|
Pages (from-to) | 206-214 |
Number of pages | 9 |
Journal | Computational and Structural Biotechnology Journal |
Volume | 17 |
DOIs | |
State | Published - 2019 |
Keywords
- And protein function
- Function prediction
- KCNQ1
- Protein structure
- SCN5A
ASJC Scopus subject areas
- Biotechnology
- Biophysics
- Structural Biology
- Biochemistry
- Genetics
- Computer Science Applications