Identification of potential Zika virus NS2B-NS3 protease inhibitors via docking, molecular dynamics and consensus scoring-based virtual screening

J Mol Model. 2019 Jun 17;25(7):194. doi: 10.1007/s00894-019-4076-6.

Abstract

The Zika virus has recently become a subject of acute interest after the discovery of the link between viral infection and microcephaly in infants. Though a number of treatments are under active investigation, there are currently no approved treatments for the disease. To address this critical need, we screened more than 7 million compounds targeting the NS2B-NS3 protease in an attempt to identify promising inhibitor candidates. Starting with commercially and freely available compounds, we identified six hits utilizing an exhaustive consensus screening protocol, followed by molecular dynamics simulation and binding energy estimation using MM/GBSA and MM/PBSA methods. These compounds feature a variety of cores and functionalities, and all are predicted to have good pharmacokinetic profiles, making them promising candidates for screening assays. Graphical abstract Virtual screen of potential Zika virus NS2B-NS3 protease inhibitors.

Keywords: Consensus scoring; Docking; Molecular dynamics; Virtual screen; Zika.

MeSH terms

  • Antiviral Agents / chemistry*
  • Antiviral Agents / pharmacology
  • Drug Evaluation, Preclinical
  • Humans
  • Molecular Conformation
  • Molecular Docking Simulation*
  • Molecular Dynamics Simulation*
  • Molecular Structure
  • Peptide Hydrolases / chemistry*
  • Protease Inhibitors / chemistry*
  • Protease Inhibitors / pharmacology
  • Protein Binding
  • Viral Nonstructural Proteins / antagonists & inhibitors
  • Viral Nonstructural Proteins / chemistry*
  • Zika Virus / drug effects
  • Zika Virus / metabolism*

Substances

  • Antiviral Agents
  • Protease Inhibitors
  • Viral Nonstructural Proteins
  • Peptide Hydrolases