Title:	Modelling pathogenic mutants and protein-protein interactions of the Kv7 ion channels
DNr:	Berzelius-2024-189
Project Type:	LiU Berzelius
Principal Investigator:	Sara Liin <sara.liin@liu.se>
Affiliation:	Linköpings universitet
Duration:	2024-05-03 – 2024-12-01
Classification:	10603
Homepage:	https://liu.se/medarbetare/sarbo42
Keywords:

Abstract

The Kv7 family of proteins are voltage gated ion channels that facilitate electrical cellular signalling through potassium efflux across the membrane. This family comprises five isoforms, termed Kv7.1 to Kv7.5 which are distributed across a range of tissues where they perform a multitude of physiological roles. This includes Kv7.1 channels in the heart, Kv7.2 and Kv7.3 in the brain, Kv7.4 in the ear and both Kv7.4 and Kv7.5 in smooth muscles. As such, loss of function in Kv7 channels contributes to serious disorders including long-QT syndrome, epilepsy, deafness, and loss of bladder control. Mutants causing these disorders have been documented in the form of genetic profiling yet little is known about how they impair Kv7 protein function. This knowledge may be the key to developing drugs that target the deficient proteins and restore their function. Furthermore, it is important to bear in mind that the Kv7 proteins do not carry out their roles in isolation and frequently interact with other proteins. For instance, KCNE4 is known to interact with Kv7.4 and modulate vascular contractility. Yet the structural basis for this effect is unknown since no structures exist for this protein complex. In a previous allocation (Berzelius-2023-71) we have generated several Kv7 models providing insight into previously unresolved Kv7 protein regions or predictions of Kv7 proteins with no structures to date, i.e. the Kv7.3 and Kv7.5 channels. In this allocation we propose to make models of Kv7 ion channels containing pathogenic mutants including Long-QT mutants of Kv7.1 and DFNA2-associated hearing loss mutants of Kv7.4. We also plan to predict the structure of physiologically relevant protein complexes of Kv7 proteins. This includes Kv7.1/KCNE1, Kv7.1/KCNE2 and Kv7.4/KCNE4. The predictions will be done using the AlphaFold2 program that we have experience in using as part of the previous allocation. We are well aware of the limitations in using AlphaFold2 and especially for modelling single residue mutations. However, we have tested modelling of some pathogenic mutants in a single Kv7 subunit through ColabFold and obtained more promising results compared to homology modelling. For instance, the prediction of R216H DFNA2 mutant in Kv7.4, places the histidine inside the voltage sensing domain (VSD) cavity, whereas homology modelling using available Kv7.4 templates places it outside. The inside placement is consistent with a homologous protein (Kv7.1) where a histidine residue in this position is indeed placed inside the VSD cavity. The reason that we require a Berzelius allocation is that its supercomputer resources are necessary to model the full length, multiple subunit structures of the Kv7 proteins. We plan to test the stability of these constructs using molecular dynamics simulations, which will be done on existing SIGMA and DARDEL allocations. Our research group has an extensive background in electrophysiology experiments. Experiments will be conducted to the validate hypothesis regarding the impact of pathogenic mutants and previously unresolved protein-protein complexes.