Ligand-gated ion channels conduct currents in response to chemical stimuli, mediating electrochemical signaling in neurons and other excitable cells. For many channels, the details of gating remain unclear, partly due to limited structural data and simulation timescales.

Here, we used enhanced sampling to simulate the pH-gated channel GLIC, and construct Markov state models (MSMs) of gating. Consistent with new functional recordings, we report in oocytes, our analysis revealed differential effects of protonation and mutation on free-energy wells.

Clustering of closed- versus open-like states enabled estimation of open probabilities and transition rates, while higher-order clustering affirmed conformational trends in gating. Furthermore, our models uncovered state- and protonation-dependent symmetrization.

This demonstrates the applicability of MSMs to map energetic and conformational transitions between ion-channel functional states, and how they reproduce shifts upon activation or mutation, with implications for modeling neuronal function and developing state-selective drugs.

[maxbutton id=”4″ url=”https://doi.org/10.7554/eLife.68369″ text=”Read more” linktitle=”eLife: Markov state models of proton- and pore-dependent activation in a pentameric ligand-gated ion channel” ]

Citation

Cathrine Bergh, Stephanie A Heusser, Rebecca Howard, Erik Lindahl (2021):
Markov state models of proton- and pore-dependent activation in a pentameric ligand-gated ion channel.
eLife 10:e68369
https://doi.org/10.7554/eLife.68369

About the author

Stian works in School of Computer Science, at the University of Manchester in Carole Goble‘s eScience Lab as a technical software architect and researcher. In addition to BioExcel, Stian’s involvements include Open PHACTS (pharmacological data warehouse), Common Workflow Language (CWL), Apache Taverna (scientific workflow system), Linked Data and identifiers, research objects (open science) and digital preservation, myExperiment (sharing scientific workflows), provenance (where did things come from and who did it) and annotations (who said what). orcid.org/0000-0001-9842-9718