Integrating bioinformatics, protein modeling and computational chemical genomics approaches in predicting protein kinases structure and binding with ligands and interacting proteins: Towards understanding the molecular basis of human disease and in silico drug discovery
Feb 20, Mon, 2006
3:30pm - 4:30pm, 6031 Haworth
This presentation will focus on the quantitative characterization of molecular recognition and analysis of protein kinases structure and binding function at the molecular level by employing an array of bioinformatics, protein modeling and chemical genomics approaches to understand structure, dynamics and evolution of ligand-protein and protein-protein interactions involved in signal transduction. The ultimate goal of this research is to provide a molecular level insight into protein kinases structure and binding function with ligands and interacting proteins to facilitate the molecular analysis of human disease and in silico drug discovery.
I will also discuss computational approaches for molecular fingerprinting the effects of genetic variations in protein kinases on protein function and ligand-protein interactions. These studies integrate information about the influence of naturally occurring sequence variations, somatic and drug- resistant mutations in protein kinases from genotype to disease phenotypes via in silico modeling of the impact of genetic variation on protein structure, dynamics and binding function. The bioinformatics component of this program aims in developing a dynamic repository of computational and experimental information integrating genetic polymorphism data, structural, dynamics and interaction profiles of protein kinases with biological and chemical data.