Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport

Abstract

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain.

Keywords: Electrophysiology; Ion channel; Ion transport; Kinetic modeling; Molecular dynamics; Structural biology.

Figure 1

Comparative space and time scales accessed by representative experimental methods in ion transport research, including structural/spectroscopic (green), electrophysiology (blue), and molecular simulations (red) approaches.

Figure 2

Potassium channel gating models. (A) Functional and computational experiments suggest that in MthK, the pore-lining helices do not form a tight bundle-crossing when channels are in the closed state; instead these helices appear to mediate a conformational change in the cytosolic domains to gate K+ permeation at the selectivity filter. (B) In KcsA, conformational changes at the bundle-crossing lead to channel opening, and these movements are coupled to closing at the selectivity filter (inactivation).

Figure 3

Multi-site model for modulation via the transmembrane domain of pentameric ligand-gated ion channels. (A) Examples of positive (above) and negative (below) modulation of pLGIC currents, typical of n-alcohols and other general anesthetizing agents, measured by two-electrode voltage-clamp in Xenopus oocytes. Representative current traces show successive activations of GLIC by pH 5.5 (conditions producing ~10% maximal activation, pEC₁₀) in the presence and absence of 590 mM methanol (above) or 570 μM 1-hexanol (below) (scale bars, 2 μA, 5 min). (B) Enhancement of pLGIC potentiation upon point mutagenesis of the transmembrane subunit interface. Columns represent modulation (% ± standard error of the mean) of GLIC pEC10 currents in wild-type (black) and F(14′)C (gray) GLIC variants by a range of n-alcohols: 590 mM methanol, 600 mM ethanol, 86 mM 1-propanol, 11 mM 1-butanol, and 36 μM 1-octanol. Asterisks indicate significant difference vs. wild-type, unpaired t-test, **P < 0.01, ***P < 0.001. (C) Computational evidence for expansion of a binding cavity for n-alcohols and general anesthetics by mutagenesis of the transmembrane subunit interface. Curves represent average cavity volumes within (above, purple axes) or between (below, orange axes) subunits, as measured by mdpocket [229] during 1-μs fully solvated molecular dynamics simulations of wild-type (red) and F(14′)A (blue) GLIC variants in the absence (solid) or presence (semi-transparent) of 600 mM ethanol. (D) Co-crystal structure (PDB ID: 4HFE) of GLIC variant F(14′)A showing ethanol (black) contacting the mutated residue (blue) and other amino acids (orange) at the subunit interface, distal to residues (purple) in the neighboring intrasubunit cavity. Wild-type residue F(14′) (red, PDB ID: 4HFI) is superimposed for comparison, clashing with the van der Waals radius (semi-transparent orange) of ethanol. (E) Representative binding sites for general anesthetics superimposed onto GLIC in an apparent open state. Anesthetic positions are signified by selected bromoform molecules in wild-type (intrasubunit, purple, PDB ID: 4HFH), F(14′)A (intersubunit, orange, PDB ID: 4HFD), and locally closed (pore, green, PDB ID: 5HCJ) GLIC structures under activating conditions. Panels A–B modified from [208], copyright 2011 National Academy of Sciences; panel C modified from [230], licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).

Figure 4

Multidisciplinary insights into voltage sensor domain activation. (A) The voltage sensor domain is thought to activate through the outward motion of S4, one of its four transmembrane segments carrying positive charges (blue), in a ratchet-like motion that involves salt bridges with negative charges of the protein (red) and of the lipid headgroups (green). A conserved phenylalanine residue (yellow) is thought to act as the gating charge transfer center. (B) Representative whole-cell recordings of gating currents in full-length Kv1.2 for pulses to −70, −50, −30, −10, 10, and 30 mV from a holding potential of −100 mV. Image courtesy of Leon Islas. (C) Free energy landscape of voltage sensor domain activation along the gating charge reaction coordinate, and atomistic models of the representative metastable states and transition state ensembles. Note the three low free energy barriers in the early activation sequence (~5 kcal/mol) and the single high free energy barrier in the late activation sequence (~12 kcal/mol) (D) Comparison between gating currents obtained from kinetic modeling using the free energy landscape calculated by molecular dynamics simulations (black) and inferred from electrophysiology recordings (green). From [236], licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).