Predicted PAR1 inhibitors from multiple computational methods

Ying Wang; Jinfeng Liu; Tong Zhu; Lujia Zhang; Xiao He; John Z.H. Zhang

doi:10.1016/j.cplett.2016.07.059

Predicted PAR1 inhibitors from multiple computational methods

Ying Wang, Jinfeng Liu, Tong Zhu, Lujia Zhang, Xiao He, John Z.H. Zhang

Chemistry

Research output: Contribution to journal › Article › peer-review

Abstract

Multiple computational approaches are employed in order to find potentially strong binders of PAR1 from the two molecular databases: the Specs database containing more than 200,000 commercially available molecules and the traditional Chinese medicine (TCM) database. By combining the use of popular docking scoring functions together with detailed molecular dynamics simulation and protein-ligand free energy calculations, a total of fourteen molecules are found to be potentially strong binders of PAR1. The atomic details in protein-ligand interactions of these molecules with PAR1 are analyzed to help understand the binding mechanism which should be very useful in design of new drugs.

Original language	English (US)
Pages (from-to)	295-303
Number of pages	9
Journal	Chemical Physics Letters
Volume	659
DOIs	https://doi.org/10.1016/j.cplett.2016.07.059
State	Published - Aug 16 2016

ASJC Scopus subject areas

Physics and Astronomy(all)
Physical and Theoretical Chemistry

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title = "Predicted PAR1 inhibitors from multiple computational methods",

abstract = "Multiple computational approaches are employed in order to find potentially strong binders of PAR1 from the two molecular databases: the Specs database containing more than 200,000 commercially available molecules and the traditional Chinese medicine (TCM) database. By combining the use of popular docking scoring functions together with detailed molecular dynamics simulation and protein-ligand free energy calculations, a total of fourteen molecules are found to be potentially strong binders of PAR1. The atomic details in protein-ligand interactions of these molecules with PAR1 are analyzed to help understand the binding mechanism which should be very useful in design of new drugs.",

author = "Ying Wang and Jinfeng Liu and Tong Zhu and Lujia Zhang and Xiao He and Zhang, {John Z.H.}",

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AU - Wang, Ying

AU - Liu, Jinfeng

AU - Zhu, Tong

AU - Zhang, Lujia

AU - He, Xiao

AU - Zhang, John Z.H.

PY - 2016/8/16

Y1 - 2016/8/16

N2 - Multiple computational approaches are employed in order to find potentially strong binders of PAR1 from the two molecular databases: the Specs database containing more than 200,000 commercially available molecules and the traditional Chinese medicine (TCM) database. By combining the use of popular docking scoring functions together with detailed molecular dynamics simulation and protein-ligand free energy calculations, a total of fourteen molecules are found to be potentially strong binders of PAR1. The atomic details in protein-ligand interactions of these molecules with PAR1 are analyzed to help understand the binding mechanism which should be very useful in design of new drugs.

AB - Multiple computational approaches are employed in order to find potentially strong binders of PAR1 from the two molecular databases: the Specs database containing more than 200,000 commercially available molecules and the traditional Chinese medicine (TCM) database. By combining the use of popular docking scoring functions together with detailed molecular dynamics simulation and protein-ligand free energy calculations, a total of fourteen molecules are found to be potentially strong binders of PAR1. The atomic details in protein-ligand interactions of these molecules with PAR1 are analyzed to help understand the binding mechanism which should be very useful in design of new drugs.

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