# SCN5A (Nav1.5): Predicting the Consequence of Missense Single- Nucleotide Polymorphisms.

> **NIH NIH R00** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2021 · $246,330

## Abstract

Project Summary/Abstract
Candidate Background: In graduate school at the University of Virginia, I built on my undergraduate
spectroscopy education by using spectroscopic tools to investigate membrane protein flexibility. As a
Postdoctoral Fellow at Vanderbilt, I transitioned to membrane protein structural biology involved in human
disease, specifically KCNQ and KCNE family-associated channelopathies. As a Postdoctoral Fellow, I have
been involved in several projects concerning the structural underpinnings of disease mechanisms, most recently
proposing a mechanism for diminished apical chloride secretion through an estrogen-induced loss of KCNQ1-
KCNE3 channel conduction.
Research Strategy: The human voltage-gated sodium channel Nav1.5 (encoded by SCN5A) is implicated in
several diseases of the heart including dilated cardiomyopathy, cardiac conduction disease, sick sinus syndrome,
type 3 longQT syndrome, and Brugada syndrome. Several algorithms accurately predict SCN5A variants that
are ultimately harmful (SIFT, PolyPhen-2, PredSNP, etc.). However, there is a significant gap in the negative
predictive ability of these methods, i.e. the ability to accurately classify a variant as benign. The approach I am
proposing is to tackle this problem on two fronts: 1) incorporating channel-specific, quantitative information-rich
data into predictive model construction—the objective being to predict channel function, instead of disease-
inducing propensity—and 2) including a set of point mutation variants enriched in WT/neutral phenotypes to
improve discrimination power during model training and evaluation. This project aims to ultimately predict Nav1.5
channel phenotypes for all possible amino-acid changing single nucleotide polymorphisms (nsSNP) by balancing
high-throughput computation and rigorous experimental validation with model systems: predicting the nearly
15,000 possible SCN5A missense nsSNPs is currently only feasible in silico, i.e. leveraging calculable
channel-specific protein sequence and structure-based features. The availability of a high-throughput
electrophysiology instrument allows for an unprecedented amassing of ion channel functional output from
heterologously expressed Nav1.5; the evaluation of SCN5A variants impact on action potential in the more native
like human induced pluripotent stem cell cardiomyocytes is possible in low-throughput. During the mentored
(K99) phase of this award, I will generate (mis)trafficking and electrophysiology current output data from
missense nsSNPs of SCN5A, focusing on the Voltage-Sensing Module (VSM) of domain IV (Aim 1) and train an
SCN5A VSM IV-specific phenotype prediction model using trafficking and electrophysiology data from Aim 1 and
the literature (Aim 2). As an independent investigator, I will determine structure and flexibility-induced changes
from selected variants using a combination of Rosetta modeling and nuclear magnetic resonance (NMR) to refine
the predictive model (Aim 3).
Career De...

## Key facts

- **NIH application ID:** 10101663
- **Project number:** 5R00HL135442-05
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Brett M Kroncke
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $246,330
- **Award type:** 5
- **Project period:** 2019-02-05 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10101663

## Citation

> US National Institutes of Health, RePORTER application 10101663, SCN5A (Nav1.5): Predicting the Consequence of Missense Single- Nucleotide Polymorphisms. (5R00HL135442-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10101663. Licensed CC0.

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