H
Hailei Zhang
Researcher at Harvard University
Publications - 4
Citations - 704
Hailei Zhang is an academic researcher from Harvard University. The author has contributed to research in topics: Virtual screening & Docking (molecular). The author has an hindex of 4, co-authored 4 publications receiving 646 citations. Previous affiliations of Hailei Zhang include Dalian University of Technology & East China University of Science and Technology.
Papers
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Journal ArticleDOI
TarFisDock: a web server for identifying drug targets with docking approach
Honglin Li,Zhenting Gao,Ling Kang,Hailei Zhang,Kun Yang,Kunqian Yu,Xiaomin Luo,Weiliang Zhu,Kaixian Chen,Jianhua Shen,Xicheng Wang,Hualiang Jiang +11 more
TL;DR: TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products, and a reverse ligand–protein docking program for seeking potential protein targets by screening an appropriate protein database.
Journal ArticleDOI
PDTD: a web-accessible protein database for drug target identification
Zhenting Gao,Zhenting Gao,Honglin Li,Honglin Li,Hailei Zhang,Xiaofeng Liu,Ling Kang,Xiaomin Luo,Weiliang Zhu,Kaixian Chen,Xicheng Wang,Hualiang Jiang,Hualiang Jiang +12 more
TL;DR: PDTD serves as a comprehensive and unique repository of drug targets and in conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules and may be a valuable platform for the pharmaceutical researchers.
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An improved PMF scoring function for universally predicting the interactions of a ligand with protein, DNA, and RNA.
Xiaoyu Zhao,Xiaofeng Liu,Yuanyuan Wang,Zhi Chen,Ling Kang,Hailei Zhang,Xiaomin Luo,Weiliang Zhu,Kaixian Chen,Honglin Li,Xicheng Wang,Hualiang Jiang +11 more
TL;DR: An improved potential mean force scoring function, named KScore, has been developed by using 23 redefined ligand atom types and 17 protein atom types, as well as 28 newly introduced atom types for nucleic acids (DNA and RNA).
Journal ArticleDOI
An effective docking strategy for virtual screening based on multi-objective optimization algorithm
Honglin Li,Honglin Li,Honglin Li,Hailei Zhang,Mingyue Zheng,Jie Luo,Ling Kang,Xiaofeng Liu,Xicheng Wang,Hualiang Jiang,Hualiang Jiang +10 more
TL;DR: The multi-objective optimization method was successfully applied in virtual screening with two different scoring functions that can yield reasonable binding poses and can furthermore, be ranked with the potentially compromised conformations of each compound, abandoning those conformations that can not satisfy overall objective functions.