Marco Cecchini, Associate Professor - University of Strasbourg

Synaptic receptors are integral transmembrane proteins that convert a chemical into an ion flux through the post-synaptic membrane. Functional and structural studies demonstrated that these proteins accomplish their function by switching between a discrete number of conformations: an apo resting state with a closed ion channel; an ion-permeable active state in complex with the neurotransmitter; and one or more desensitized states, where the channel shuts with the neurotransmitter bound.
 
Markov State Models (MSMs) are stochastic models that describe the temporal evolution of complex molecular systems beyond the timescales accessible by all-atom molecular dynamics (MD) simulations. The construction of an MSM requires the collection of a large set of MD trajectories, clustering into metastable states, and the generation of a transition probability matrix, which opens to the population of states at equilibrium, the conformational transition pathways and kinetics.
By capitalizing on a generous allocation of 20-million CPU hours by GENCI (Grand équipement national de calcul intensif), we constructed two MSMs of the glycine receptor (GlyR), one with no ligand bound (APO) and one with the partial agonist taurine (TAU) bound. These models highlight a complex free energy surface underlying synaptic receptor function and predict that agonist binding results in a population shift towards open channel state. Second, the MSM transition probability matrix provides access to the opening/shut times of the channel and enables the characterization of the functional transition pathways with atomic resolution. Third, the combination of in-silico electrophysiology with MSM opens to the simulation of single-channel recordings, which allows direct comparison with experiments.

The results collected so far highlight that the combination of high-resolution structures with Markov-state modeling of MD simulations powered by HPC resources provide an effective multiscale simulation approach to bridge the gap between synaptic receptor structure and function.
 

Contact : Paulo Telles de Souza