Big K⁺ (BK) channels regulate neuronal and muscle excitability, integrating changes in membrane potential and intracellular Ca²⁺ into hyperpolarizing current.  Dysfunction of these channels is implicated in several neurological disorders, including those associated with mutations in KCNMA1, the gene encoding the BK channel pore-forming alpha subunit.  The image on the cover of the July 16 issue of Biophysical Journal is a side view of two BK channel subunits reconstructed from the cryo-EM structure of the Ca²⁺-bound tetramer. Each subunit is composed of seven transmembrane domains, comprising a voltage sensor and pore, regulated by a large intracellular gating ring that binds Ca²⁺. The image shows the 53 patient-associated missense mutations at residues resolved within the structure (in red) and their distribution within the voltage sensor (shown in green), pore (shown in orange), and gating ring (regulator of K⁺ conductance, RCK1, shown in blue; RCK2, shown in yellow) domains. The image was created in Visual Molecular Dynamics by Hans Moldenhauer and Kelly Tammen from Andrea Meredith’s lab at the University of Maryland School of Medicine.

In the Meredith Lab, our research is focused on understanding how state-dependent changes in BK channel gating regulate excitability in neurons and muscle. In human BK channelopathies, both gain of function (GOF) and loss of function (LOF) are associated with epilepsy, dyskinesia, and other neurodevelopmental disorders. This structural map guides our understanding of genotype-phenotype correlations at the channel level, showing the locations and relationships for residues altered by patient-associated mutations. Our study reveals clustering of LOF residues, but not GOF residues, within known BK channel functional domains. These clusters of pathogenic residues (defined as three or more residues <5 Å apart) are found within the pore, the βA–αC (AC) region of RCK1, and near sites of pharmacological or endogenous modulation, such as the Ca²⁺ bowl of RCK2. Surprisingly, GOF mutations showed little structural relationship; yet, these comprise a larger proportion of the patient cohort and are generally associated with more severe disease. This discrepancy highlights important gaps in our understanding of the ways in which KCNMA1 variants disrupt BK channel function.

Creating this map led us to integrate the structural factors into pathogenicity evaluation for BK channelopathies by developing the KCNMA1 Meta Score (KMS) algorithm. We trained KMS on LOF and GOF mutations previously substantiated functionally by electrophysiology. Applying KMS to evaluate variants of uncertain significance, we found that incorporating structural parameters improved performance in four of five test cases compared to an initial assessment that used ClinVar-based pathogenicity analysis.

Channelopathies are an area in need of multi-modal variant prediction capabilities, based on the suboptimal performance of standard genetic algorithms on membrane proteins and the limited functional datasets associated with rare channelopathy disease. We anticipate that this structural map, along with improvements in KMS pathogenicity assessments, will facilitate continued studies on genotype-phenotype correlation in BK channelopathies and support new means of establishing and understanding the causality of KCNMA1 variants in neurological disease. You can find more information on our work at https://meredithlab.org/.

— Hans J. Moldenhauer, Kelly Tammen, and Andrea L. Meredith