Research: Proteins are allosteric nano-machines whose conformational dynamics controls their functional versatility. Conformational dynamics is important in understanding the allosteric nature of proteins, in identifying allosteric druggable sites as well as in designing drugs with functional specificity.
Biophysical experimental methods provide fragmented information on the structure and dynamics and the X-ray crystallography provides a static picture of one of the low energy conformations in an ensemble of states. Therefore computational methods are essential in integrating the experimental information and provide an atomic level detail of the dynamics of proteins. One of the major bottlenecks in using the existing computational methods to study dynamics of proteins is the limitation in time scale and the narrow conformational search afforded by these methods. Thus we need multi-scale computational methods that span a larger range in time and length scale to extend the use of computational methods to large protein complexes. Our laboratory is focused on developing state of the art multi-scale computational methods to study the conformational dynamics of proteins. We are developing coarse grain computational methods to sample the various kinetic states of the protein dynamics, followed by fine grain computational methods to capture the detailed atomic level structural changes and to calculate the thermodynamic properties.
Our research projects include:
- Development of constrained molecular dynamics methods – GNEIMO
- Development of coarse grained conformational sampling method for G-protein coupled receptors (GPCRs) – GPCRSimKit
- Development of computational method for designing thermostable mutants for GPCRs – LITiConDesign
- Development and application of computational methods to identify allosteric sites for drug design in protein-protein complexes – AlloBindSite
- Application of these methods to design drugs with functional specificity for GPCRs targeting pancreatic cancer and other cancers – Chemokine
