Literature DB >> 17999538

Structural models for the KCNQ1 voltage-gated potassium channel.

Jarrod A Smith1, Carlos G Vanoye, Alfred L George, Jens Meiler, Charles R Sanders.   

Abstract

Mutations in the human voltage-gated potassium channel KCNQ1 are associated with predisposition to deafness and various cardiac arrhythmia syndromes including congenital long QT syndrome, familial atrial fibrillation, and sudden infant death syndrome. In this work 3-D structural models were developed for both the open and closed states of human KCNQ1 to facilitate structurally based hypotheses regarding mutation-phenotype relationships. The KCNQ1 open state was modeled using Rosetta in conjunction with Molecular Operating Environment software, and is based primarily on the recently determined open state structure of rat Kv1.2 (Long, S. B., et al. (2005) Science 309, 897-903). The closed state model for KCNQ1 was developed based on the crystal structures of bacterial potassium channels and the closed state model for Kv1.2 of Yarov-Yarovoy et al. ((2006) Proc. Natl. Acad. Sci. U.S.A. 103, 7292-7207). Using the new models for KCNQ1, we generated a database for the location and predicted residue-residue interactions for more than 85 disease-linked sites in both open and closed states. These data can be used to generate structure-based hypotheses for disease phenotypes associated with each mutation. The potential utility of these models and the database is exemplified by the surprising observation that four of the five known mutations in KCNQ1 that are associated with gain-of-function KCNQ1 defects are predicted to share a common interface in the open state structure between the S1 segment of the voltage sensor in one subunit and both the S5 segment and top of the pore helix from another subunit. This interface evidently plays an important role in channel gating.

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Year:  2007        PMID: 17999538      PMCID: PMC2565492          DOI: 10.1021/bi701597s

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


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