A co-operative knock-on mechanism underpins Ca²⁺-selective cation permeation in TRPV channels

Abstract

The selective exchange of ions across cellular membranes is a vital biological process. Ca2+-mediated signalling is implicated in a broad array of physiological processes in cells, whilst elevated intracellular concentrations of Ca2+ are cytotoxic. Due to the significance of this cation, strict Ca2+ concentration gradients are maintained across the plasma and organelle membranes. Therefore, Ca2+ signalling relies on permeation through selective ion channels that control the flux of Ca2+ ions. A key family of Ca2+-permeable membrane channels are the polymodal signal-detecting Transient Receptor Potential (TRP) ion channels. TRP channels are activated by a wide variety of cues including temperature, small molecules, transmembrane voltage and mechanical stimuli. Whilst most members of this family permeate a broad range of cations non-selectively, TRPV5 and TRPV6 are unique due to their strong Ca2+-selectivity. Here, we address the question of how some members of the TRPV subfamily show a high degree of Ca2+-selectivity whilst others conduct a wider spectrum of cations. We present results from all-atom molecular dynamics simulations of ion permeation through two Ca2+-selective and two non-selective TRPV channels. Using a new method to quantify permeation co-operativity based on mutual information, we show that Ca2+-selective TRPV channel permeation occurs by a three binding site knock-on mechanism, whereas a two binding site knock-on mechanism is observed in non-selective TRPV channels. Each of the ion binding sites involved displayed greater affinity for Ca2+ over Na+. As such, our results suggest that coupling to an extra binding site in the Ca2+-selective TRPV channels underpins their increased selectivity for Ca2+ over Na+ ions. Furthermore, analysis of all available TRPV channel structures shows that the selectivity filter entrance region is wider for the non-selective TRPV channels, slightly destabilising ion binding at this site, which is likely to underlie mechanistic decoupling.

Calcium binding and permeation in TRPV channels: insights from molecular dynamics simulations

“…Therefore, multiple Ca 2+ ions must line up and march in a concerted manner to permeate more efficiently. Consequently, multiple Ca 2+ binding sites lead to a concerted permeation manner, which is a characteristic that discriminates the Ca 2+ permeation in TRPV6 from TRPV1, as also observed by Ives et al (Ives et al, 2022). In fact, increasing the number of Ca 2+ -binding sites in channel pores has long been proposed to improve channel selectivity for Ca 2+ (Tsien et al, 1987).…”

“…Thus, monovalent cations can probably still push Ca 2+ through SF, resulting in a lower valence selectivity than expected. Indeed, Ives et al’s work observed similar behavior for multiple TRPV channels, as well as that the selectivity increases in TRPV5 with decreasing the transmembrane potential (Ives et al, 2022).…”

“…4B). However, it should be noted that here we only focus on the ions in the SF, while the ions in the cavity would probably be involved in the concerted permeation as well, as observed in the work by Ives et al (Ives et al, 2022). Therefore, multiple ion binding and concerted permeation appears to be a universal phenomenon in the TRPV channels.…”

A hydrophobic funnel governs monovalent cation selectivity in the ion channel TRPM5

“…In the case of simulations containing Ca 2+ , the standard CHARMM36m Ca 2+ ions were then replaced with the multi-site Ca 2+ of Zhang et al Zhang et al ( 2020 ). This multi-site model has used been used to investigate Ca 2+ permeation in a number of channels, including including the type-1 ryanodine receptor Zhang et al ( 2020 ); Liu et al ( 2021 ), AMPA receptors Schackert et al ( 2022 ), the E protein of SARS-CoV-2 Antonides et al ( 2022 ), and TRPV channels Ives et al ( 2022 ); Liu and Song ( 2022 ).…”

“…To characterise the level of co-operativity in the knock-on permeation mechanisms of the TRPM5 channel, we used PENSA to calculate the state-specific information (SSI) shared between discrete state transitions in the occupancy distributions of both of the binding sites Thomson et al ( 2021 ); Vögele et al ( 2022 ). The methodology used is the same as that described in detail in our previous work Ives et al ( 2022 ).…”