@article{dab7a93541d34e9ea0cf8580e3eee8e3,
title = "Inhibition of striatal-enriched protein tyrosine phosphatase by targeting computationally revealed cryptic pockets",
abstract = "Cryptic pockets, which are not apparent in crystallographic structures, provide promising alternatives to traditional binding sites for drug development. However, identifying cryptic pockets is extremely challenging and the therapeutic potential of cryptic pockets remains unclear. Here, we reported the discovery of novel inhibitors for striatal-enriched protein tyrosine phosphatase (STEP), a potential drug target for multiple neuropsychiatric disorders, based on cryptic pocket detection. By combining the use of molecular dynamics simulations and fragment-centric topographical mapping, we identified transiently open cryptic pockets and identified 12 new STEP inhibition scaffolds through structure-based virtual screening. Site-directed mutagenesis verified the binding of ST3 with the predicted cryptic pockets. Moreover, the most potent and selective inhibitors could modulate the phosphorylation of both ERK1/2 and Pyk2 in PC12 cells.",
keywords = "Cryptic pocket, Inhibitor, Striatal-enriched protein tyrosine phosphatase, Virtual screening",
author = "Xuben Hou and Sun, {Jin peng} and Lin Ge and Xiao Liang and Kangshuai Li and Yingkai Zhang and Hao Fang",
note = "Funding Information: This work was supported by grants from National Natural Science Foundation of China (Grant 21672127 and 81874288 to H.F. and Grant 31470789 and 81773704 to J.P.S.), US National Institute of Health (R35-GM127040) to Y.Z. Key Research and Development Project of Shandong Province (Grant No. 2017CXGC1401), Fundamental Research Funds of Shandong University (Grant No. 2019GN045) and The Joint Research Funds for Shandong University and Karolinska Institute (SDU-KI-2019-06). The authors gratefully acknowledge NYU-ITS and NYUAD for providing computational resources. Funding Information: This work was supported by grants from National Natural Science Foundation of China (Grant 21672127 and 81874288 to H.F. and Grant 31470789 and 81773704 to J.P.S.), US National Institute of Health ( R35-GM127040 ) to Y.Z., Key Research and Development Project of Shandong Province (Grant No. 2017CXGC1401 ), Fundamental Research Funds of Shandong University (Grant No. 2019GN045 ) and The Joint Research Funds for Shandong University and Karolinska Institute ( SDU-KI-2019-06 ). The authors gratefully acknowledge NYU-ITS and NYUAD for providing computational resources. Publisher Copyright: {\textcopyright} 2020 Elsevier Masson SAS",
year = "2020",
month = mar,
day = "15",
doi = "10.1016/j.ejmech.2020.112131",
language = "English (US)",
volume = "190",
journal = "CHIM.THER.",
issn = "0223-5234",
publisher = "Elsevier Masson SAS",
}