Role of Water Models in Simulations of Ion Conduction in Potassium Channels

Stefano Bosio, Diego Gazzoni, Carmen Domene, Matteo Masetti, Simone Furini

Research output: Contribution to journalArticlepeer-review

Abstract

Potassium channels exhibit high selectivity and conductance, yet the atomic details of ion permeation, particularly the involvement of water molecules, remain debated. Two main conduction mechanisms have been proposed: the hard knock-on, in which ions traverse the selectivity filter in direct contact, and the soft knock-on, which involves copermeation of water molecules. Using microsecond molecular dynamics simulations with the OPC water model, the AMBER19SB protein force field, and the 12-6-4 Sengupta et al. ion model, and an analysis strategy based on Markov State Models, we observed that both hard and soft knock-on mechanisms are accessible and, notably, can reversibly transition in the MthK and KcsA channels across all simulated membrane potentials. These reversible transitions contrast with previous observations using the TIP3P water model, where water entry either disrupted conduction or was expelled, favoring exclusive hard knock-on events. Our results suggest that the choice of the water model, force field, and ion parameters significantly influences the observed conduction mechanism. Importantly, the coexistence of hard and soft knock-on in these simulations provides a reconciliation between structural data supporting hard knock-on and streaming potential measurements demonstrating water copermeation. These findings reintroduce soft knock-on as a viable conduction mechanism and highlight the critical role of simulation parameters in reproducing potassium channel permeation behavior.

Original languageEnglish
Pages (from-to)1177-1186
Number of pages10
JournalJournal of Chemical Theory and Computation
Volume22
Issue number2
Early online date8 Jan 2026
DOIs
Publication statusPublished - 27 Jan 2026

Data Availability Statement

Configuration files, atomic models, discretized MD trajectories,
and the python code used for the analyses of the MSM are
available at the github repository: https://github.com/sfurini/
kchannels_water_models

Funding

We acknowledge CINECA for awarding access to computational resources through the ISCRA Initiative (grant numbers HP10B597 KB and HP10B5IPGG). Riccardo Ocello is gratefully acknowledged for useful discussion. We acknowledge EuroHPC for awarding access to computational resources in several of the European platforms including LUMI (CSC, Finland), Marenostrum (BSC, Spain) and Leonardo (CINECA, Italy).

ASJC Scopus subject areas

  • Computer Science Applications
  • Physical and Theoretical Chemistry

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