Journal of Biomolecular Research & Therapeutics

Vamsi Boyapati

Vamsi Boyapati
Postdoctoral Researcher    
Louisiana State University
USA

Biography

Ph.D. Biochemistry, Louisiana State University, Baton Rouge, LA-USA (2011) Advisor: Dr. Fareed Aboul-Ela.

M.Sc. Biochemistry, Acharya Nagarjuna University, India (2005).

B.Sc. Osmania University, India (2003).

Research Interest

Structural biology and drug design: The determination of the atomic structure of proteins and RNA, the study of their interaction with small molecule drugs and metabolites and the use of this information to design lead molecules for the discovery of new therapeutic drugs.

Ph.D. focus: Designed and put-together an Ribonucleic acid (RNA) targeted small molecule library with the aid of computational tools. Implemented Nuclear magnetic resonance (NMR) spectroscopy experiments to screen the library small molecules against RNA drug targets in a high-throughput setup.

Investigated the mechanistic contributions of SAM-I riboswitch RNA with its effector metabolite S-adenosyl methionine in gene regulation mechanism in bacteria. Multi dimensional NMR, inline probing and other biophysical experiments along with computational and molecular dynamic simulations were used to delineate the structural features of the SAM-I riboswitch.

Current research: As a post doctoral researcher, currently investigating protein protein interactions between Ras GTPase-activating-like protein (IQGAP) in association with GTPase proteins. The IQGAPS are multi domain scaffold proteins. Each domain interacts with a host of other proteins to control cell division, cell adhesion, cancer metastasis, cytoskeleton rearrangement. The interaction of GAP related domain (GRD) of the IQGAP with GTPase is believed to sequester or open the other domains of IQGAP protein to control the above cellular processes. High resolution structural information is necessary to understand the functional role of the IQGAP proteins. Crystals of the IQGAP-GRD in complex with GTPase are made to collect high resolution X-ray diffraction data. The diffraction data is used to build models of physiological relevance.