Markov state models of proton- and pore-dependent activation in a pentameric ligand-gated ion channel
Abstract
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.
Data availability
Additional data including simulation parameters and sampled conformations from the MSMs can be accessed at doi:10.5281/zenodo.4594193.
Article and author information
Author details
Funding
Knut och Alice Wallenbergs Stiftelse
- Erik Lindahl
Vetenskapsrådet (2017-04641)
- Erik Lindahl
Vetenskapsrådet (2018-06479)
- Erik Lindahl
Vetenskapsrådet (2019-02433)
- Erik Lindahl
Swedish e-Science Research Centre
- Rebecca Howard
- Erik Lindahl
European Union Horizon 2020 (BioExcel (823830))
- Erik Lindahl
Swedish National Infrastructure for Computing
- Erik Lindahl
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Toby W Allen, RMIT University, Australia
Version history
- Preprint posted: March 12, 2021 (view preprint)
- Received: March 13, 2021
- Accepted: October 14, 2021
- Accepted Manuscript published: October 15, 2021 (version 1)
- Version of Record published: December 1, 2021 (version 2)
Copyright
© 2021, Bergh et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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