Computational Biology, Bioinformatics, and Systems Biology; Cancer Metabolomics; development of tools for the prediction of protein structure and function; functional genomics; metabolic pathways, prediction of small molecule ligands for drug discovery, prediction of druggable protein targets, drug design, prediction of DNA binding proteins, drug discovery. evolutionary biology, molecule based cell simulations.

The long term goal of my research is to be able to simulate at molecular detail a single cell. In doing so, one would understand the basic principles of life.

We have developed a very promising ligand homology modeling approach for the computational prioritization of small molecules that are likely to bind a given protein target. The power of the approach is that predicted as well as experimental structures can be used. Thus, the methodology has been applied to the human proteome and where we find that we can identify off target proteins. In other work, we are in the early stages of simulating a  molecular model of E. coli. Finally, we have developed new approaches to the prediction of DNA binding proteins that have low false positive rates.

With the outstanding support of the Georgia Research Alliance, the Georgia Institute of Technology is embarking on building a world class program in Systems Biology. The excitement of helping contribute to this goal as well as the quality of life in Georgia is what drew me to Georgia.