KvDB; mining and mapping sequence variants in voltage-gated potassium channels

Abstract

We have created KvDB: a voltage-gated potassium (Kv) channel-specific database that houses natural and experimental variant data and includes highly curated multiple sequence alignments and additional analytical tools, such as structural variant mapping and transmembrane segment prediction. KvDB is available at www.bioinformatics.leeds.ac.uk/KvDB. Analyzing the characterized gene variants in terms of topological location revealed the following. The S4, S4-S5, S5, S5-S6, and S6 segments are most likely to house disease-causing variants. Neurological disorders are more likely to be caused by variants affecting voltage sensing, whereas cardiac disorders are more likely to be caused by variants in the pore. Long QT Syndrome 2 (LQT2) is more often caused by N-terminus variation, a region containing a domain that affects deactivation, suggesting a potential disease mechanism. Conversely, a higher proportion of LQT1-causing variants reside in S4-S5, suggesting communication of voltage-sensing to the pore as a disease mechanism. By structurally mapping functionally characterized variants, we also provide mechanistic insight into Kv channel function; identifying an intersubunit interaction that may be partly responsible for setting activation voltage. Investigating phenotypically characterized variants that map to the same position as functionally characterized ones indicates only weak association between locations that cause disease and those that alter electrophysiological properties.