The main objective of the project is to model in detail the process of how beta amyloids can bind G-protein coupled receptors (GPCRs) and to do so in silico. Detailed modeling of protein-ligand binding is traditionally conducted via Molecular Dynamics (MD) simulations. Simulating MD simulations in silico is expensive and not feasible, practically. Our approach is not based on running expensive MD simulations but is just as accurate and reliable. The approach relies on dense sampling of the ligand conformer space.
The first 1-2 weeks in my research I read many journal articles to understand the interaction between beta amyloids and Nicotinic Receptors, and to find out what are other protein docking software used in the field. Throughout the research I used a molecular modeling software called PyRosetta, a Python-based interface to the Rosetta molecular modeling software. It allows users to create custom docking algorithms using Python scripting. This week I ran several docking simulations to reveal possible differences between the native and aggregation-prone (diseased) form of the amyloid-beta peptide when binding to alpha-7 Nicotinic Acetylcholine Receptor (a7 nAchR). Once I get all docking simulation results I am going to analyze total energies and corresponding binding poses using a linear dimensionality reduction technique known as Principal Component Analysis (PCA).
During the whole process, the guidance from my mentor was great. The experiences that I gained while working on my research project helped me to improve my research skills and will help me to be a successful researcher in the future. The USRP program is a great opportunity for undergraduates at Mason to enhance their research skills.