Abstract
Although traditional molecular dynamics simulations successfully capture a variety of different molecular interactions, the protonation states of titratable residues are kept static. A recent constant-pH molecular dynamics implementation in the GROMACS package allows pH effects to be captured dynamically, and promises to provide both the accuracy and computational performance required for studying pH-mediated conformational dynamics in large, complex systems containing hundreds of titratable residues. Here, we demonstrate the applicability of this constant-pH implementation by simulating the proton-gated ion channel GLIC at resting and activating pH, starting from closed and open structures. Our simulations identify residues E26 and E35 as especially pH-sensitive, and reveal state-dependent pKa shifts at multiple residues, as well as side chain and domain rearrangements in line with the early stages of gating. Our results are consistent with several previous experimental findings, demonstrating the applicability of constant-pH simulations to elucidate pH-mediated activation mechanisms in multidomain membrane proteins, likely extensible to other complex systems.
Significance statement Electrostatic interactions play important roles in protein structure and function. Since changes in pH will (de)protonate residues and thereby modify such interactions, pH itself is a critical environmental parameter. However, protonation states of titratable residues are static during classical molecular dynamics simulations. Recently, a constant-pH algorithm was implemented in the GROMACS package, allowing pH effects to be captured dynamically. Here, we used this implementation to perform constant-pH simulations of the proton-gated ion channel GLIC, providing insight into its activation mechanism by revealing state-dependent shifts in protonation as well as pH-dependent side chain and domain-level rearrangements. The results show that constant-pH simulations are both accurate and capable of modeling dozens of titratable sites, with important implications for e.g. drug design.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Text restructured and edited; data deposition link updated; supplemental figures S2, S4-S7 added.
