Modeling Protein Macrostates with Transition Probabilities

NMDA receptors are a type of ion channel found in the central nervous system that contribute to excitatory neurotransmission. Fluorescence resonance energy transfer (FRET) experiments have yielded some information about distances between a residue pair on this protein, but the structures of various macrostates are still unknown. Distance distributions from FRET experiments have previously been used in our group to solve for an ideal set of simulation model parameters and gain structural information about the macrostates of the protein. A drawback to FRET distance fitting is that it lacks time information. In this study, fitting was performed on a transition matrix, which shows the probability of the protein transitioning from one state to another in a given lag time. Transition matrices calculated from C-alpha model trajectories were fit to an experimental transition matrix. Results from different transition lag times and starting model parameters are presented.