Simulating ligand receptor binding at a membrane interface with graphics processing accelerated coarse-grained molecular dynamics

Motivated by a deeper understanding of the immunological synapse, we develop a molecular-based model to understand receptor-polymer/ligand binding at a membrane interface. ~ We examine the case of weak ligand binding in the limit of confined polymer chains as a function of chain length, binding constant, and system size. ~We utilize a coarse-grained (CG) model of poly(ethylene oxide) and dimyristoylphosphatidylcholine (DMPC) previously developed by the Klein group and mimic weak binding with a sticky potential. ~This work employs graphics processing units (GPU) to accelerate the CG-MD simulations, where each simulation is run with multiple random-walker replicas to enhance sampling and facilitate statistical convergence of physical observables. ~Our results demonstrate that such an aggressive combination of GPU acceleration with CG modeling can yield accurate and precise data on polymer-DMPC binding, and, more importantly, hints at the mechanism behind empirical data of polymer binding to a T-cell receptor protein.