We develop computational tools on high-performance systems to model protein structure and function, understand bimolecular interactions, develop new drugs, and help analyze, in the long run, the molecular machinery of the cell. We integrate sequence information with three-dimensional structural information to capture, represent and exploit relevant molecular motion. Of particular interest are the identification of three-dimensional functional motifs in protein databases, metabolic pathways, docking of flexible molecules to flexible receptors, computer-assisted drug discovery, the characterization and analysis of protein motion, protein folding, and the compact representation and understanding of structural changes in large biomolecular machines.
Functional Annotation of Proteins
Computational Cancer-Drug Design
Metabolic Networks
Nonlinear Dimensionality Reduction for the Analysis of Protein Motion
Sampling-Based Modeling of Equilibrium Fluctuations in Proteins
Exploring the Dynamics and Energetics of Protein Complexes
Multiscale Representation of Proteins
Molecular Representations, Kinematics and Related Problems
Biomolecular Interactions
We have also developed courses and educational material on the above topics. Courses (COMP470: Bioinformatics: from Sequence to Structure and COMP650: Topics in Physical Computing) can be found under Rice's OWLSPACE.
An online course has been developed using Connexions: Geometric Methods in Structural Computational Biology. The material can be used freely under the license information specified in the same page.