Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

A high-throughput cell-based screening method for Zika virus protease inhibitor discovery

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • Contributors:
      Lee Kong Chian School of Medicine (LKCMedicine); National Centre for Infectious Diseases, Singapore; NTU Institute of Structural Biology
    • الموضوع:
      2024
    • Collection:
      DR-NTU (Digital Repository at Nanyang Technological University, Singapore)
    • نبذة مختصرة :
      Zika virus (ZIKV) continues to pose a significant global public health threat, with recurring regional outbreaks and potential for pandemic spread. Despite often being asymptomatic, ZIKV infections can have severe consequences, including neurological disorders and congenital abnormalities. Unfortunately, there are currently no approved vaccines or antiviral drugs for the prevention or treatment of ZIKV. One promising target for drug development is the ZIKV NS2B-NS3 protease due to its crucial role in the virus life cycle. In this study, we established a cell-based ZIKV protease inhibition assay designed for high-throughput screening (HTS). Our assay relies on the ZIKV protease's ability to cleave a cyclised firefly luciferase fused to a natural cleavage sequence between NS2B and NS3 protease within living cells. We evaluated the performance of our assay in HTS setting using the pharmacologic controls (JNJ-40418677 and MK-591) and by screening a Library of Pharmacologically Active Compounds (LOPAC). The results confirmed the feasibility of our assay for compound library screening to identify potential ZIKV protease inhibitors. ; Ministry of Education (MOE) ; Published version ; This work was supported by National Institute of Allergy and Infectious Disease grant U19-AI171954 and by the Singapore Ministry of Education Academic Research Fund Tier 2 [MOE-T2EP30220–0009].
    • File Description:
      application/pdf
    • ISSN:
      38796112
    • Relation:
      MOE-T2EP30220–0009; SLAS Discovery; https://hdl.handle.net/10356/179981; 29; 100164
    • الرقم المعرف:
      10.1016/j.slasd.2024.100164
    • الدخول الالكتروني :
      https://doi.org/10.1016/j.slasd.2024.100164
      https://hdl.handle.net/10356/179981
    • Rights:
      © 2024 The Authors. Published by Elsevier Inc. on behalf of Society for Laboratory Automation and Screening. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
    • الرقم المعرف:
      edsbas.AF79F00E