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Identification of Potential TMPRSS2 Inhibitors for COVID-19 Treatment in Chinese Medicine by Computational Approaches and Surface Plasmon Resonance Technology.
Yang, Rong; Liu, Linhua; Jiang, Dansheng; Liu, Lei; Yang, Huili; Xu, Hongling; Qin, Meirong; Wang, Ping; Gu, Jiangyong; Xing, Yufeng.
  • Yang R; Department of Hepatology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
  • Liu L; Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau 999078, China.
  • Jiang D; Department of Hepatology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
  • Liu L; Department of Hepatology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
  • Yang H; Department of Infectious Diseases, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
  • Xu H; Department of Hepatology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
  • Qin M; Department of Hepatology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
  • Wang P; National Medical Products Administration, Shenzhen Institute for Drug Control, Shenzhen 518057, China.
  • Gu J; National Medical Products Administration, Shenzhen Institute for Drug Control, Shenzhen 518057, China.
  • Xing Y; Research Centre for Integrative Medicine, School of Basic Medical Science, Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
J Chem Inf Model ; 63(10): 3005-3017, 2023 05 22.
Article in English | MEDLINE | ID: covidwho-2320623
ABSTRACT

BACKGROUND:

Coronavirus disease-19 (COVID-19) pneumonia continues to spread in the entire globe with limited medication available. In this study, the active compounds in Chinese medicine (CM) recipes targeting the transmembrane serine protease 2 (TMPRSS2) protein for the treatment of COVID-19 were explored.

METHODS:

The conformational structure of TMPRSS2 protein (TMPS2) was built through homology modeling. A training set covering TMPS2 inhibitors and decoy molecules was docked to TMPS2, and their docking poses were re-scored with scoring schemes. A receiver operating characteristic (ROC) curve was applied to select the best scoring function. Virtual screening of the candidate compounds (CCDs) in the six highly effective CM recipes against TMPS2 was conducted based on the validated docking protocol. The potential CCDs after docking were subject to molecular dynamics (MD) simulations and surface plasmon resonance (SPR) experiment.

RESULTS:

A training set of 65 molecules were docked with modeled TMPS2 and LigScore2 with the highest area under the curve, AUC, value (0.886) after ROC analysis selected to best differentiate inhibitors from decoys. A total of 421 CCDs in the six recipes were successfully docked into TMPS2, and the top 16 CCDs with LigScore2 higher than the cutoff (4.995) were screened out. MD simulations revealed a stable binding between these CCDs and TMPS2 due to the negative binding free energy. Lastly, SPR experiments validated the direct combination of narirutin, saikosaponin B1, and rutin with TMPS2.

CONCLUSIONS:

Specific active compounds including narirutin, saikosaponin B1, and rutin in CM recipes potentially target and inhibit TMPS2, probably exerting a therapeutic effect on COVID-19.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Serine Proteinase Inhibitors / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Traditional medicine Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2023 Document Type: Article Affiliation country: Acs.jcim.2c01643

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Serine Proteinase Inhibitors / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Traditional medicine Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2023 Document Type: Article Affiliation country: Acs.jcim.2c01643