4.7 Article

Structure-based discovery of clinically approved drugs as Zika virus NS2B-NS3 protease inhibitors that potently inhibit Zika virus infection in vitro and in vivo

期刊

ANTIVIRAL RESEARCH
卷 145, 期 -, 页码 33-43

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.antiviral.2017.07.007

关键词

Zika; Flavivirus; Novobiocin; Protease; Treatment; Molecular modelling

资金

  1. Centro de Alto Rendimiento de la Region de Murcia [CFE-CAR-23/15]
  2. Consultancy Service for Enhancing Laboratory Surveillance of Emerging Infectious Diseases of the Department of Health, Hong Kong Special Administrative Region
  3. Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases
  4. Ministry of Education of China
  5. Fundacion Seneca del Centro de Coordinacion de la Investigation de la Region de Murcia [18946/JLI/13, 19419/PI/14-1]

向作者/读者索取更多资源

Zika virus (ZIKV) infection may be associated with severe complications in fetuses and adults, but treatment options are limited. We performed an in silico structure-based screening of a large chemical library to identify potential ZIKV NS2B-NS3 protease inhibitors. Clinically approved drugs belonging to different drug classes were selected among the 100 primary hit compounds with the highest predicted binding affinities to ZIKV NS2B-NS3-protease for validation studies. ZIKV NS2B-NS3 protease inhibitory activity was validated in most of the selected drugs and in vitro anti-ZIKV activity was identified in two of them (novobiocin and lopinavir-ritonavir). Molecular docking and molecular dynamics simulations predicted that novobiocin bound to ZIKV NS2B-NS3-protease with high stability. Dexamethasone-immunosuppressed mice with disseminated ZIKV infection and novobiocin treatment had significantly (P < 0.05) higher survival rate (100% vs 0%), lower mean blood and tissue viral loads, and less severe histopathological changes than untreated controls. This structure-based drug discovery platform should facilitate the identification of additional enzyme inhibitors of ZIKV. (C) 2017 Elsevier B.V. All rights reserved.

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