Protein-ligand Interactions: We are interested in developing and applying physical models and computational algorithms to predict the specific interaction between protein and small drug-like molecules. Currently, we are investigating a series of computational models base on a polarizable atomic multipole potential energy function (AMOEBA). Our goal is to achieve chemical accuracy in the prediction and to better our understanding of the physical principles of molecular recognition and interactions. Protein targets of interest include proteases and kinases.

 

 

Biomaterials and biomimetics: Molecular modeling and simulations are utilized to understand nano surfaces and structures that mimic and interact with biomolecules. The long-term objective is to aid the design of nanomaterials with controlled molecular structure and functions for biomedical applications such as tissue scaffolds, biomolecular sensors and diagnosis devices. Polydepsipeptides and polypyrroles based materials are being investigated in conjunction with experimental labs at UT BME.

 

 

RNA is one of the most important molecules in with potentially high therapeutic values. We are working to develop computational algorithms and physical models for predicting RNA 3-D structures and potentially its interaction with other biological and synthetic molecules, on which their functions depend on. Being able to understand and predict RNA structures is a critical step in designing RNA based therapeutics. We are particularly interested in exploring coarse-grained RNA potentials based on sequence and structural statistics as well as physical principles.

 

Multiscale Physical Potential development: We are developing rigid-body physical potentials for proteins and nucleic acids. The model is based on point multipole, anisotropic vdw and implicit solvent method, and is general (easily combined with other physical models) and transferable from one environment to another.