Predicted PAR1 inhibitors from multiple computational methods

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

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)295-303
Number of pages9
JournalChemical Physics Letters
Volume659
DOIs
StatePublished - Aug 16 2016

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Computational methods
inhibitors
Molecules
Binders
Ligands
proteins
molecules
ligands
scoring
medicine
Free energy
Medicine
Molecular dynamics
Proteins
drugs
free energy
molecular dynamics
Computer simulation
Pharmaceutical Preparations
simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

Cite this

Predicted PAR1 inhibitors from multiple computational methods. / Wang, Ying; Liu, Jinfeng; Zhu, Tong; Zhang, Lujia; He, Xiao; Zhang, John.

In: Chemical Physics Letters, Vol. 659, 16.08.2016, p. 295-303.

Research output: Contribution to journalArticle

Wang, Ying ; Liu, Jinfeng ; Zhu, Tong ; Zhang, Lujia ; He, Xiao ; Zhang, John. / Predicted PAR1 inhibitors from multiple computational methods. In: Chemical Physics Letters. 2016 ; Vol. 659. pp. 295-303.
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