@article{f159050092c34193b7ef855455768d8d,
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.}",
note = "Funding Information: This work was supported by the National Natural Science Foundation of China (Grants nos. 21433004 , 21303057 , 21403068 and 31571786 ), Ministry of Science and Technology of China (Grant no. 2016YFA0501700 ), and Shanghai Putuo District (Grant 2014-A-02 ). X.H. is also supported by the Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20130076120019 ) and the Fundamental Research Funds for the Central Universities . L.Z. acknowledges the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase). We thank the Supercomputer Center of East China Normal University for providing us with computational time. Publisher Copyright: {\textcopyright} 2016 Elsevier B.V.",
year = "2016",
month = aug,
day = "16",
doi = "10.1016/j.cplett.2016.07.059",
language = "English (US)",
volume = "659",
pages = "295--303",
journal = "Chemical Physics Letters",
issn = "0009-2614",
publisher = "Elsevier B.V.",
}