Molecular dynamics simulation of the truncated NMDA receptor in the open state

The GluN1/GluN2A N-methyl-D-aspartate receptor (NMDAR) is a critical ligand-gated ion channel in the central nervous system, playing essential roles in synaptic plasticity, learning, and memory. Understanding its dynamics in the open/active state is paramount for deciphering its physiological functions and for developing targeted therapeutics. Despite many past efforts, the active/open state has not yet been fully resolved at atomic resolutions. To elucidate the molecular mechanism of the NMDAR activation, computer modeling and simulation are instrumental in providing detailed information about the dynamics and energetics of the receptor in various functional states. In this study, we started from a previously built open-state model of a truncated NMDAR, and then explored its energetics and dynamics with extensive molecular dynamics (MD) simulation (total simulation time is 5.6 {micro}s). Based on the MD simulation, we employed an array of analysis tools to study the fluctuations/motions at the levels of individual residues, the channel pore, and the global structure, and identified a dynamic network of polar/nonpolar interactions between residues. Furthermore, we used machine learning to identify key interactions and residues relevant to channel opening/closing and validated them with evolutionary conservation grades and annotations of disease mutations in NMDAR. Taken together, our modeling and simulation provided rich structural and dynamic information which will guide functional studies of the activation of this key receptor.