Chung F. Wong
Chung
F. Wong received his B.Sc. (Hons.) degree from the Chinese
University of Hong Kong and his Ph.D. degree from the University
of Chicago. He did his postdoctoral work at the University
of Houston. He held academic and industrial positions at the
University of Houston, Mount Sinai School of Medicine, SUGEN,
Inc., University of California-San Diego, and the Howard Hughes
Medical Institute before joining the faculty of UM-St. Louis
in 2004.
wongch@msx.umsl.edu
Office: N203
Phone:(314) 516-5318
Fax: (314) 516-5342
Chung Wong Laboratory Homepage
Research
Interests
Our
research involves the development and applications of computational
methods to study biomolecular structure, dynamics, and function and
to aid the design of bioactive compounds. Methods that we have been
developing/using include molecular dynamics that simulates biomolecular
motion by solving Newtons equation of motion, Brownian dynamics that
simulates molecular motion and the diffusional encounter among biomolecules,
Feynmann path integral method that accounts for quantum nuclear tunneling
effects in simulating conformational fluctuations, sensitivity analysis
that helps to identify the determinants of biomolecular properties
and to aid molecular design, continuum-electrostatics models that
predict the electrostatic properties of biomolecules, and quantum
chemical methods that calculate the energetic, conformational and
spectroscopic properties of molecules of biological interests. In
addition, we have developed a helix-coil transition theory using
database-derived potentials to predict the helical forming propensity
of amino acid sequences. Recently, we are also interested in developing
a full quantum-mechanical treatment of protein-ligand interactions.
The biological systems that we recently focus on are protein kinases and phosphatases. We are interested in using the above techniques to decipher the enzymatic mechanisms of these proteins. In addition, we have been using a combination of computational tools to aid the design of drugs targeting these proteins to treat diseases such as cancer and diabetes. With the rapid advance of computer hardware and new developments in molecular modeling and simulation software, computational tools are becoming increasingly powerful in computer-aided drug design. Although there is still substantial room for further improving these techniques, the use of a combination of methods that are based upon different approximations can already yield useful predictions. For example, when several methods point to the same conclusion, there is a good chance that the conclusion is valid. Also, it is a useful strategy to employ a hierarchical approach to computer-aided drug design in which simpler but faster methods are first used to examine a large number of real or virtual compounds and more sophisticated but slower methods are then used to further evaluate a smaller number of compounds that warrant further exploration. We have been constructing components of such a hierarchical approach by using existing methodologies as well as methods developed in our own laboratory. In addition, as whole genome data are becoming available, we are also performing large scale comparative analyses to take selectivity into account in designing drugs that have fewer side effects.
Selected Publications
Z. Huang, C.F. Wong and R. Wheeler, "Flexible Protein-Flexible Ligand Docking with Disrupted Velocity Simulated Annealing", Proteins: Structure, Function, Bioinformatics, 2008, 71, 440.
"Flexible ligand-flexible protein docking in protein kinase systems", C. F. Wong, Biochimica et Biophysica Acta, Proteins and Proteomics, 2008, 1784, 244
"A Mining-Minima Approach to Exploring the Docking Pathways of p-Nitrocatechol Sulfate to YopH", Z. Huang and C.F. Wong, Biophys. J., 2007, 93, 4141
"Efficient Quantum Mechanical Calculation of Solvation Free Energies Based on Density Functional Theory, Numerical Atomic Orbitals and Poisson-Boltzmann Equation", M. Wang, C. F. Wong, J. Liu and P. Zhang, Chem. Phys. Lett., 2007, 442, 464.
"Rank-ordering Protein-Ligand Binding Affinity by a QM/MM/PBSA Model", M. Wang and C. F. Wong, J. Chem. Phys., 2007, 126, 026101.
"Calculation of Solvation Free Energy from Quantum Mechanical Charge Density and Continuum Dielectric Theory", M. Wang and C. F. Wong, J. Phys. Chem. A 2006, 110, 4873
"Molecular Dynamics Simulation of Laser Desorption of a Fragment of Protein Kinase A from Two MALDI Matrices", C. Wang and C. F. Wong, J. Phys. Chem. A 2006, 110, 5355
"Molecular docking of balanol to dynamics snapshots of protein kinase A", C. F. Wong, J. Kua, Y. Zhang, T. P. Straatsma and A. J. McCammon, Proteins: Structure, Function and Bioinformatics 2005, 61, 850 .
"Direct estimation of entropy loss due to reduced translational and rotational motions upon molecular binding", B. Lu and C. F. Wong, Biopolymers 2005, 79, 277
"Relative contributions of desolvation, inter- and intramolecular interactions to binding affinity in protein kinase systems", P. A. Sims, C. F. Wong, D. Vuga, A. J. McCammon and B. M Sefton, J. Comput. Chem. 2005, 26, 668.
"Release of ADP from the catalytic subunit of protein kinase A: A molecular dynamics simulation study", B. Lu, C. F. Wong and A. J. McCammon, Protrein Science 2005, 14, 159
"Finite Concentration Effects on Diffusion-controlled Reactions", S. Senapati, C.F. Wong and J.A. McCammon, J. Chem. Phys. 2004, 121 7896
"Release of ADP from the Catalytic Subunit of Protein Kinase A: A Molecular Dynamics Simulation Study", B.Z. Lu, C.F. Wong & J.A. McCammon, Protein Sci. 2004, 14, 159
"Charge Optimization of the Interface between Protein Kinases and their Ligands", P. Sims, C.F. Wong and J.A. McCammon, J. Comput. Chem., 2004. 25, 1416
"Computational analysis of the interactions between the angiogenesis inhibitor PD173074 and fibroblast growth factor receptor ", K. Tondel, C. F. Wong and J. A. Mccammon, Journal of Theoretical & Computational Chemistry, 2003, 2, 43