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个人简介
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), the third generation of the general-AMBER force field (GAFF3), 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 using both the endpoint and pathway methods.
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, Tachykinin receptor 1, Mechanosensitive channel of large conductance(MscL). 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 on pharmacometrics and systems pharmacology (PSP). He is interested in studying drug-drug interactions from the perspectives of both pharmacokinetics and pharmacodynamics.
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), the third generation of the general-AMBER force field (GAFF3), 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 using both the endpoint and pathway methods.
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, Tachykinin receptor 1, Mechanosensitive channel of large conductance(MscL). 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 on pharmacometrics and systems pharmacology (PSP). He is interested in studying drug-drug interactions from the perspectives of both pharmacokinetics and pharmacodynamics.
研究兴趣
论文共 344 篇作者统计合作学者相似作者
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CoRR (2025)
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Sihan Li, Zehua Wang, Xiaofei Wang, Yifei Wang,Dhamotharan Pattarayan,Yu Zhang, Phuong Nguyen,Avishek Bhuniya, Yuang Chen, Haozhe Huang,Yixian Huang, Luxuan Wang,Junmei Wang,Song Li,Min Zhang,Yang Liu,Nara Lee,Da Yang
Cell genomicspp.100878-100878, (2025)
Research square (2025)
JOURNAL OF CHEMICAL INFORMATION AND MODELINGno. 3 (2025): 1428-1440
Journal of chemical theory and computationno. 6 (2025): 3032-3043
Briefings in bioinformaticsno. 3 (2025)
Journal of computational chemistryno. 14 (2025): e70137-e70137
CPT pharmacometrics & systems pharmacologyno. 3 (2025): 435-447
Briefings in bioinformaticsno. 3 (2025)
Frontiers in Molecular Biosciences (2025)
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作者统计
#Papers: 344
#Citation: 53882
H-Index: 73
G-Index: 231
Sociability: 7
Diversity: 4
Activity: 80
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