Dr. Junmei Wang is an Associate Professor of Pharmaceutical Sciences and a member of the Computational Chemical Genomics Screening Center (www.CBLigand.org/CCGS), University of Pittsburgh School of Pharmacy.
Dr. Wang received his PhD from Peking University in China, and he was trained as a postdoctoral associate with Dr. Peter Kollman at University of California San Francisco. Before joining University of Pittsburgh, Dr. Wang was an associate professor at University of Texas Southwestern Medical Center. He has a rich background in pharmaceutical industry due to his working experience in Encysive Pharmaceuticals as a Senior Scientist.
Dr. Wang is also a long-term Developer of the Amber Software (www.ambermd.org). He and other collaborators developed a set of popular AMBER force fields, such as FF99, GAFF and polarizable FF based on Thole’s dipole-interaction models as well as the Antechamber module implemented in AMBER software packages.
Dr. Wang’s research interests fall into three directions. First, he is dedicated to develop high quality physical scoring functions to study protein-ligand interactions. Ongoing projects include the second generation of the general-AMBER force field (GAFF2), polarizable force fields based on atomic dipole interaction, solvation models, efficient methods for calculating entropies, and toolkits that facilitate users to study protein-ligand interactions.
A chief application of the developed molecular mechanics force fields and toolkits is to elucidate the molecular mechanisms of how small molecule inhibitors mediate protein and nucleic acid targets using molecular dynamics simulations, and then to rationally design high potent agonists or antagonists to enhance or eradicate the functions of the protein or nucleic acid targets. Dr. Wang’s research group is involved in many drug discovery projects, including Toll-like receptors, Cannabinoid receptors and Orexin receptors. During this procedure, his force field models and toolkits are rigorously scrutinized and critically assessed through direct comparisons with experiments.
The third research direction in Dr. Wang’s lab is pharmacometric modeling. He is interested in constructing pharmacokinetic, pharmacodynamic and disease-state models using technologies popular in other fields, but uncommon in pharmacometric research.
1. Shao, Z. H.; Yin, J.; Chapman, K.; Grzemska, M.; Clark, L.; Wang, J.; Rosenbaum, D. "High-resolution crystal structure of the human CB1 cannabinoid receptor", Nature, 540, 602-606, 2016.
2. Lee, J.-Y. ; Kinch, L. N.; Borek, D. M.; , Wang, J.; Wang, J.; Urbatsch, I. L.; Xie, X.-S.; Grishin, N. V.; Cohen, J. C.; Otwinowski, Z.; Hobbs, H. H.; Rosenbaum, D. M., Crystal structure of the human sterol transporter ABCG5/ABCG8, Nature, 533, 561-564, 2016.
3. Wray, R.; Iscla, I.; Wang, J.*; Blount P*. Dihydrostreptomycin directly binds to, modulates, and passes through the MscL channel pore. PLOS Biology, 14, e1002473, 2016. (* corresponding authors)
4. Wang, J.; Cieplak, P.; Li, J.; Cai, Q.; Hsieh, M. J.; Luo, R.; Duan, Y. Development of polarizable models for molecular mechanical calculations IV: van der Waals parameterization. J. Phys. Chem. B, 116, 7088-7101, 2012.
5. Wang, J.; Hou, T. Develop and Test a Solvent Accessible Surface Area-Based Model in Conformational Entropy Calculations. J. Chem. Info. Model., 52, 1199-1212, 2012.
6. Wang, J.; Cieplak, P.; Li, J.; Hou, T.; Luo, R.; Duan, Y. Development of polarizable models for molecular mechanical calculations I: Parameterization of atomic polarizability. J. Phys. Chem. B, 115, 3091-3099, 2011.
7. Wang, J.; Cieplak, P.; Li, J.; Wang, J.; Cai, Q.; Hsieh, M. J.; Lei, H.; Luo, R.; Duan, Y. Development of polarizable models for molecular mechanical calculations II: Induced dipole models significantly improve accuracy of intermolecular interaction energies. J. Phys. Chem. B, 115, 3100-3111, 2011.
8. Wang, J.*; Hou, T. Application of molecular dynamics simulations in molecular property prediction II: Diffusion coefficients. J. Comput. Chem., 32, 3505-3519, 2011.
9. Wang, J.*; Hou, T. Application of molecular dynamics simulations in molecular property prediction I: Density and heat of vaporization. J. Chem. Theory Comput., 7, 2151-2165, 2011.
10. Hou, T.; Wang, J.; Li, Y.; Wang, W. Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. J. Chem. Info. Model., 51:69-82, 2011. [cited 451 times]
11. Hou, T.; Wang, J.; Li, Y.; Wang, W. Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking. J. Comput. Chem., 32, 866-877, 2011. [cited 138 times]
12. Wang, J.*; Hou, T. Drug and drug candidate building block analysis. J. Chem. Info. Model., 50, 55-67, 2010.
13. Wang, J.*; Hou, T.; Xu, X. Aqueous solubility prediction based on weighted atom type counts and solvent accessible surface areas. J. Chem. Info. Model., 49, 571-581, 2009.
14. Wang, J.*; Krudy, G.; Hou, T.; Holland, G.; Xu, X. Development of reliable aqueous solubility models and their application in drug-like analysis. J. Chemical Information and Modeling, 47, 1395-1404, 2007.
15. Wang, J.*; Wang, W.; Kollman, P. A.; Case, D. A. Automatic atom type and bond type perception in molecular mechanical calculations, J. Mol. Grap. Mod., 25, 247-260, 2006. [cited 1,247 times]
16. Wang, J.*; Krudy, G.; Xie, X.-Q.; Wu, C.; Holland, G. Genetic algorithm-optimized QSPR models for bioavailability, protein binding, and urinary excretion, J. Chem. Info. Model., 46, 2674-2683, 2006.
17. Wang, J.*; Hou, T.; Xu, X. Recent advances in free energy calculations with a combination of molecular mechanics and continuum models, Current Computer-Aided Drug Design, 2, 95-103, 2006.
18. Wang, J.*; Kang, X.; Kollman, P. A.; Kuntz, I. D. Hieratical database screening for HIV-1 reverse transcriptase using pharmacophore model, rigid docking, solvation docking and MM-PB/SA, J. Med. Chem. . 48, 2432-2444, 2005.
19. Wang, J.; Wolf, R.; Caldwell, J.; Kollman, P. A.; Case, D. A. Development and test of a general AMBER force field for organic molecules and bio-molecules, J. Comput. Chem. 25, 1157-1174, 2004. [cited 4,468 times]
20. Huo, S.; Wang, J.; Cieplak, P.; Kollman, P. A.; Kuntz, I. D. Molecular dynamics and free energy analyses of cathepsin D-inhibitor interactions: insight into structure-based ligand design, J. Med. Chem., 45, 1412-1419, 2002. [cited 143 times]
21. Wang, J.;, Morin, P.; Wang, W.; Kollman, P. A. Use of MM-PBSA in reproducing the binding free energies to HIV-1 RT of TIBO derivatives and predicting the binding mode to HIV-1 RT of efavirenz by docking and MM-PBSA, J. Am. Chem. Soc., 123, 5221-5230, 2001. [cited 441 times]
22. Wang, J.;, Wang, W.; Huo, S.; Lee M.; Kollman, P. A. A solvation model based on weighted solvent accessible surface area, J. Phys. Chem. B., 105, 5055-5067, 2001.
23. Wang, J.;, Cieplak, P.; Kollman, P. A. How well does a restrained electrostatic potential (RESP) mode perform in calculating conformational energies of organic and biological molecules? J. Comput. Chem., 21, 1049-1074, 2000. [cited 2,579 times]
2R01GM079383-05 01/01/2014 – 12/31/2018
AMBER force field consortium: a coherent biomolecular simulation platform
The major goals of the project are to develop polarizable force fields for proteins, nucleic acids and organic molecules
Role: one of multi-PIs