Ionotropic Glutamate receptors (iGluRs) influence the timescales at which neurons communicate with each other. The dynamics and flexibility of the response of iGluRs to neurotransmitter binding give rise to the synaptic plasticity responsible for normal human intelligence. Dysfunction of the iGluRs is causally responsible for diseases such as Alzheimer's and Amyotrophic lateral sclerosis. It is therefore medically important to understand how the structure-function relationship in the iGluRs operates at the molecular level. Many drugs attempt to target iGluRs to treat neuropathologies. However, due to the inherent complexity of the dynamics of iGluRs it is difficult to accurately target the causative function of the iGluRs thus making it difficult to form a viable pharmaceutical strategy, without insight into the dynamics of iGluRs at the atomic level. Additionally, although the individual members of the iGluR family are structurally very similar, they display very different kinetic and allosteric behaviour. The proposed project aims to focus on the comprehensive picture of the comparative dynamics of the members of the iGluRs. In close collaborations with experimental and computational methods development groups, I plan to investigate how the relatively small differences in the structures of the iGluRs give rise to the complex behaviours of the iGluRs. This will be accomplished via state of the art Molecular Dynamics (MD) simulations and a large library of computational thermodynamics techniques. From this dataset, using Machine Learning (ML) techniques in combination with Markov State Models (MSMs) I will create robust and testable models that can determine the commonalities and variances between the dynamics of the members of the iGluRs while throwing light on their mechanisms of action.
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