Our main research interests are development and application of computational methods to study the structure and dynamics of bio-molecular systems. We focus on protein folding and aggregation and protein structure prediction, simulation method development, structure and dynamics of G-protein coupled receptors, DNA-protein interactions, and computer aided drug design.
Proteins need to “fold” to their native productive states to become biologically active. A number of proteins can also misfold and have been linked to a number of human diseases, including cystic fibrosis, Alzheimer’s disease and other amyloidoses, and prion spongiform encephalopathies such as Creutzfeldt-Jacob disease. An understanding of the mechanism differentiating productive protein folding from misfolding and aggregation is critical to preventing misfolding and misassembly of proteins and would enable us to predict protein structures more accurately and to design new proteins. We are conducting simulation studies to elucidate the process of protein folding and aggregation.
G-protein coupled receptors (GPCR) are membrane proteins that can be activated/deactivated by external stimuli and initiate signal transduction. GPCR have been the premier targets of drug development effort and about 50% of the existing drugs on the market are designed to interact with GPCRs. GPCRs are believed to share a common 7 transmembrane architecture with relatively flexible extra-cellular and cytoplasmic domains. Therefore, computational modeling can play important role to provide detailed and accurate information on the structure and dynamics of GPCRs.
The interactions between proteins and DNA play a central role in molecular biology and genomics. These interactions include both sequence-specific and sequence-non-specific types. In the sequence-specific interactions, proteins recognize a specific DNA sequence (e.g., restriction enzymes and transcription factors). In the non-specific type, proteins interact with DNA regardless of the sequence. These interactions are crucial for gene expression, gene activation/repression. Thus, understanding these interactions is considered a key step toward functional interpretation of genetic sequences in the post-genomic era.
