The research in our group specializes in G Protein Coupled receptors (GPCR).

GPCRs form one of the largest gene families of membrane bound proteins. They play a critical role in the physiology and pathology of many diseases including cancer. As a result, more than 50% of the drugs in the market target GPCRs.

In our lab, we use computational techniques to understand the structure and function of the G-Protein Coupled receptors.

BX471 drug bound to human  CCR1 chemokine receptor

Research Projects

Structure Prediction of GPCRs
In our laboratory, we focus on developing computational methods for predicting the three dimensional structure of GPCRs using minimal experimental data. GPCRs are implicated in many diseases including cancer and are therefore seen as potential targets for new drugs. However, the lack of crystal structures is a major hindrance to the understanding of the physiological functions of GPCRs. Using our methods, we show how the differences in sequence identity lead to variations in the structures of the various GPCR subtypes.

Computational Drug Design
Once the structure of a GPCR is available, we predict the binding sites of agonists and antagonists to these receptors using docking algorithms. The predicted binding site and calculated binding energies are then compared with the available experimental data on mutagenesis and ligand binding affinities. These computational predictions greatly aid the experimental screening and discovery of new ligands that could be used either as drugs, or as probes for understanding the physiology of the receptors. We specialize particularly on GPCRs that are cancer targets. The predictions made in our lab are experimentally verified by our collaborators, which include both academic research groups and pharmaceutical companies.

Long Timescale Simulation - Protein Dynamics
Another focus of our research is developing hierarchical molecular dynamics algorithms for performing long time scale (microseconds) simulations to study the conformational changes that lead to activation of GPCRs. These constrained dynamics algorithms scale linearly with the number of degrees of freedom and hence would be useful is pushing towards microsecond level simulations. We also apply these long time scale dynamics methods to study the stability of DNA crossover nanostructures. These algorithms are developed in collaboration with scientists at Jet Propulsion Laboratory/Caltech.

Epinephrine bound to the transmembrane domain of B2-Adrenergic Receptor