Thursday, September 11, 2014

URSP Student Herath Pilapitiya Understands Alzheimer’s by Modeling beta-amyloids that Bind to GPCRs

Computer Science is one of the fastest growing fields in the modern world. Research experience in the field of computer science is very important to be successful as a computer scientist. With the hope of pursuing graduate studies in a computer science related field and be a computer scientist in the future, I was interested in doing research as an undergraduate student. When I was searching for a faculty mentor at the computer science department who offers research opportunities for undergraduates, I came to know that some undergraduate students doing research under Dr. Amarda Shehu. After going over her website and personally talking to her, I was really interested in her projects in the field of bioinformatics. She informed me she had just the right project for me and asked me to join her lab in the summer. The project was a collaboration with a neuroscientist, which had me even more enthusiastic about the possibility of acquiring interdisciplinary skills.

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.