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Chung F. Wong, B.Sc. (Hons.), Chinese University of Hong Kong, Ph.D. the University of Chicago, did 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 UMSL in 2004. |
wongch@msx.umsl.edu |
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. For details please go to the link above to the laboratory homepage.
Selected Publications
″Milestoning simulation of ligand dissociation from the glycogen synthase kinase 3β″, S. Rathnayake, B. Narayan, R. Elber and C. F. Wong, Proteins: Structure, Function, and Bioinformatics 2023, 91, 209.
″15 Years of molecular simulation of drug-binding kinetics″, C. F. Wong, Exp. Opin. on Drug Disc.2023, 18, 1333.
″Simulation of ligand dissociation kinetics from the protein kinase PYK2,″ J. Spiriti, F. Noe, and C. F. Wong, J. Computat. Chem. 2022, 43, 1911
"Why 2,6-di-methyl-β-cyclodextrin can encapsulate OH-substituted naphthalenes better than β-cyclodextrin: Binding pose, non-covalent interaction and solvent effect," K. Chen, R. X. Liu, C. F. Wong, S. Xu, J. Luo, X. Gong and B. Zhou, Comp. & Theoret. Chem., 2021, 1206, 113496
"Why heptakis(2,3-di-O-acetyl)-β-cyclodextrin can separate terbutaline enantiomers better than β-cyclodextrin: nonbonding and hydrophobic interactions" R. Dou, K. Chen, G. Chi, J. Luo, C. F. Wong and B. Zhou. J. Incluson Phen. & Macrocyclic Chem, 2021 100, 189
″Qualitative Prediction of Ligand Dissociation Kinetics from Focal Adhesion Kinase Using Steered Molecular Dynamics,″ J. Spiriti and C. F. Wong, Life 2021, 11, 74.
EDock-ML: A web server for using ensemble docking with machine learning to aid drug discovery , T. Chandak and C. F. Wong, Protein Sci. 2021, 30, 1087
″Using machine learning to improve ensemble docking for drug discovery,″ T. Chandak, J. P. Mayginnes, H. Mayes and C. F. Wong, Prot. Struct. Func. & Bioinf. 2020; 88, 1263.
″Improving ensemble docking for drug discovery by machine learning,″ C. F. Wong, J. Theoret. Comp. Chem. 2019, 18, 1920001.
"Steered molecular dynamics simulations for uncovering the molecular mechanisms of drug dissociation and for drug screening: A test on the focal adhesion kinase," C. F. Wong, J. Computational Chem. 2018, 39, 1307.
″Program for Simulating Gel Electrophoresis of Enzyme-Digested Proteins, ″ H. Mayes and C. F. Wong, J Chem. Ed. 2018, 95, 2064.
″Variable van der Waals Radii Derived From a Hybrid Gaussian Charge Distribution Model for Continuum-Solvent Electrostatic Calculations,″ R. Ye, X. Nie, C. F. Wong, X. Gong, Y. A. Wang, T. Heine and B. Zhou, Baojing, Z. Phys. Chem. 2016, 230, 681
″Incorporating binding kinetics in drug design, ″ C. F. Wong, In: Silico Drug Discovery and Design, C. N. Cavasotto, Ed, 2016, 483-503
″Exploring host-guest complexation mechanisms by a molecular dynamics/quantum mechanics/continuum solvent model approach,″ R. Ye, X. Nie, Y. Zhou, C. F. Wong, X. Gong, W. Jiang, W. Tang, Y. A. Wang,T. Heine and B. Zhou, Chem. Phys. Lett. 2016, 648, 170
″Inexpensive Method for Selecting Receptor Structures for Virtual Screening,″ Z. Huang and C. F. Wong, J. Chem. Inf. & Modeling 2016, 56, 21.