Areas of Interest
G protein-coupled receptors (GPCR's) are a superfamily of transmembrane proteins that bind a multitude of ligands, relaying a signal that will ultimately manifest in a cellular response. Aberration of function oftentimes leads to different diseases, most importantly cancer. In fact, about 40% of drugs on the market today target GPCR's, lending credence to its importance in drug discovery. However, few GPCR structures have been solved to date, most of them being in Family A, and structures are needed now more than ever for structure-based drug design. In order to overcome this problem, homology modeling of GPCR's can provide an expedited solution, providing the structures required for /in silico/ screening of compounds.
My project involves constructing a database that mines for ligand-GPCR interaction data from multiple databases, as well as from the literature. Based on the assumption that homologous GPCR's may utilize chemically-similar substrates, ligand profiles will be developed for each GPCR from known associations, aiming to predict ligands for unknown targets. All human GPCR homology models will be employed in high-throughput docking screens with ligands best matching the respective ligand profile, followed with high-throughput experimental validation of cancer-related targets.
Jul 19-24, 2015, Gordon Research Conference - Computer Aided Drug Deisgn, West Dover, VT. Poster Presentation: "GLASS: a comprehensive database for experimentally-validated GPCR-ligand associations"
Honors & Awards
Proteome Informatics in Cancer Training Program - 2013 - 2015
Rackham Travel Grant (2015)
Wallace K. B. Chan, Hongjiu Zhang, Jianyi Yang, Jeffrey R. Brender, Junguk Hur, Arzucan Özgür and Yang Zhang (2015) GLASS: a comprehensive database for experimentally validated GPCR-ligand associations. Bioinformatics, Online ISSN 1460-2059 - Print ISSN 1367-4803