(442g) Predicting Interactions of A? and the NMDA Receptor Using Molecular Docking and Simulations
AIChE Annual Meeting
2021 Annual Meeting
Computational Molecular Science and Engineering Forum
Practical Applications of Computational Chemistry and Molecular Simulation III
Tuesday, November 16, 2021 - 2:10pm to 2:30pm
Despite decades of research, the fundamental molecular mechanism of Alzheimerâs disease (AD) is unknown. AÎ², a 40-42 amino acid long peptide, has been proposed as a central molecule in pathogenesis. Two mutations of the second residue in the N-terminus of AÎ² have opposite effects in developing the disease. A2T is a neuroprotective variant and A2V is a causative mutation. Another protein of interest, when studying Alzheimerâs pathology, is the NMDA receptor (NMDAR), a post-synaptic receptor family critical to neuroplasticity and consequently learning and memory. The NMDAR protein is composed of four subunits and is activated by the coincidence of glutamate and glycine together with a membrane depolarization. Several treatments for AD focus on regulating the activity of NMDAR through inhibition, e.g., memantine. While there is evidence that suggests a link between Alzheimerâs via direct or indirect interactions between the NMDA receptor with AÎ², the structural details and binding modes remains largely unknown. The goal of this study is to use in silico methods (molecular docking and simulations), to provide insight into NMDA - AÎ² interactions and guide experiments that can elucidate their role in Alzheimerâs pathogenesis. Our methodology includes an ab-initio rigid body docking step, to generate unbiased interaction models of the NMDAR- AÎ² complex and discover preferred AÎ² binding regions on NMDAR. This is then followed by a flexible docking step to predict a more representative structure of the AÎ² peptide:NMDAR complex, and a molecular dynamics simulation step to study the strength and stability of the complexes in an environment that closely represents in vivo conditions. We find that a single amino acid substitution with known changes to developing AD results in distinct interaction profiles in our rigid body docking experiments. We also find overlaps between active molecule binding locations and predicted docking models with all AÎ² isoforms.