(436c) Pushing the Boundaries of Multiscale Simulation to Model Proton Transport in SERCA

The sarcoplasmic reticulum Ca²⁺-ATPase (SERCA) calcium pump is ubiquitous in cells, exchanging Ca²⁺ ions for protons (powered by ATP) to maintain homeostasis and regulate muscle contraction. Its dysfunction has been indicated in multiple diseases including heart failure, respiratory diseases (e.g. cystic fibrosis), diabetes, and Alzheimer's disease. While SERCA structures have been solved and multiple experimental and computational studies have elucidated calcium transport mechanisms, a proton transport mechanism has yet to be determined. Computational molecular modeling could allow investigation of such mechanisms, but to do so required advances in multiscale modeling. The full system requires including the ~1000 residues of SERCA, any associated ligands (such as its natural inhibitor phospholamban), a lipid bilayer, and surrounding water, with sub-Angstrom resolution in the regions involved in proton transport. The dynamics of the conformational flexibility of the protein, the majority of which resides outside the lipid bilayer, are orders of magnitude slower than the fast but infrequent dynamics of proton transport. To span the time and length scales required to sample the ensemble of relevant protein conformations with the resolution needed to simulate proton transport, we combined enhanced sampling methods with our multi-scale reactive molecular dynamics (MS-RMD), which allows modeling of the bond-formation and cleavage required for proton transport at significantly lower computational cost than ab initio molecular dynamics or QM/MM simulations. Advances in applying these methodologies to bio-molecular systems have allowed us to determine a mechanism for passive proton permeability through SERCA in its inactive, phospholamban-bound state, which had been hypothesized to explain how the sarco- or endoplasmic reticulum maintains equilibrium with the cytosol during calcium release via separate calcium channels. The methods described here continue to expand the power of simulation to model more complex systems of interest.