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Sanders, C. R.

Publications and source records attributed to Sanders, C. R..

2 recordsLinked to original sources

Upgraded molecular models of the human KCNQ1 potassium channel

The voltage-gated potassium channel KCNQ1 (KV7.1) assembles with the KCNE1 accessory protein to generate the slow delayed rectifier current, IKS, which is critical for membrane repolarization as part of the cardiac action potential. Loss-of-function (LOF) mutations in KCNQ1 are the most common cause of congenital long QT syndrome (LQTS), type 1 LQTS, an inherited genetic predisposition to cardiac arrhythmia and sudden cardiac death. A detailed structural understanding of KCNQ1 is needed to elucidate the molecular basis for KCNQ1 LOF in disease and to enable structure-guided design of new anti-arrhythmic drugs. In this work, advanced structural models of human KCNQ1 in the resting/closed and activated/open states were developed by Rosetta homology modeling guided by newly available experimentally-based templates: X. leavis KCNQ1 and resting voltage sensor structures. Using molecular dynamics (MD) simulations, the models capability to describe experimentally established channel properties including state-dependent voltage sensor gating charge interactions and pore conformations, PIP2 binding sites, and voltage sensor - pore domain interactions were validated. Rosetta energy calculations were applied to assess the models utility in interpreting mutation-evoked KCNQ1 dysfunction by predicting the change in protein thermodynamic stability for 50 characterized KCNQ1 variants with mutations located in the voltage-sensing domain. Energetic destabilization was successfully predicted for folding-defective KCNQ1 LOF mutants whereas wild type-like mutants had no significant energetic frustrations, which supports growing evidence that mutation-induced protein destabilization is an especially common cause of KCNQ1 dysfunction. The new KCNQ1 Rosetta models provide helpful tools in the study of the structural mechanisms of KCNQ1 function and can be used to generate structure-based hypotheses to explain KCNQ1 dysfunction.\n\nAuthor SummaryCardiac rhythm is maintained by synchronized electrical impulses conducted throughout the heart. The potassium ion channel KCNQ1 is important for the repolarization phase of the cardiac action potential that underlies these electrical impulses. Heritable mutations in KCNQ1 can lead to channel loss-of-function (LOF) and predisposition to a life-threatening cardiac arrhythmia. Knowledge of the three-dimensional structure of KCNQ1 is important to understand how mutations lead to LOF and to support structurally-guided design of new anti-arrhythmic drugs. In this work, we present the development and validation of molecular models of human KCNQ1 inferred by homology from the structure of frog KCNQ1. Models were developed for the open channel state in which potassium ions can pass through the channel and the closed state in which the channel is not conductive. Using molecular dynamics simulations, interactions in the voltage-sensing and pore domain of KCNQ1 and with the membrane lipid PIP2 were analyzed. Energy calculations for KCNQ1 mutations in the voltage-sensing domain reveled that most of the mutations that lead to LOF cause energetic destabilization of the KCNQ1 protein. The results support both the utility of the new models and growing evidence that mutation-induced protein destabilization is a common cause of KCNQ1 dysfunction.

biophysics

Do available protein 3D structures reflect human genetic and functional diversity?

Genomic databases are substantially biased towards European ancestry populations, and this bias contributes to health disparities. Here, we quantify how well 66,971 experimentally characterized human protein 3D structures represent the diversity of protein sequences observed across the 1000 Genomes Project. More than 85% of available structures do not match a sequence observed in at least one individual, and on average structures match the sequence of 74% of individuals. Nearly 23% of human structures do not match any observed sequences; however, after masking engineered/known mutations, this decreases to ~4%. African ancestry sequences are modestly, but significantly, less likely to be represented by structures (73.5% vs. 74.0%). These differences are mainly driven by the greater genetic diversity of African populations. We identify thousands of variants unrepresented in available structures that influence protein structure and function. Thus, the use of a single structure as representative of \"the wild type\" protein will often bias results against many individuals. The diversity of protein sequence and structure must be considered to enable accurate, reproducible, and generalizable conclusions from structural analyses.

genetics