Identification of potential inhibitors against the Zika virus using consensus scoring

J Mol Graph Model. 2017 May:73:54-61. doi: 10.1016/j.jmgm.2017.01.018. Epub 2017 Feb 9.

Abstract

The Zika virus (ZIKV) is a life threatening pathogen of zoonotic importance with prevalence in some parts of Africa and America. Unfortunately, there is yet to be a single approved vaccine or antiviral drug to treat the diseases and deformations being caused by the Zika virus infection. In this study, about 36 million compounds from MCULE database were virtually screened against a real matured ZIKV protein using a consensus scoring method to get improved hit rates. The consensus scoring method combined the result from the 25 top ranked molecules from both MCULE and Drug Score eXtended (DSX) docking programs which led to the selection of two hit compounds. The inhibition constant (Ki) values of 0.08 and 0.30μm were obtained for the two selected compounds MCULE-8830369631-0-1 and MCULE-9236850811-0-1 respectively, to remark them as hit compounds. The molecular interactions of the two selected hit compounds with the amino acids (ALA 48, ILE 49, ILE 468 and LEU 472) present in the ZIKV protein indicated that they both have similar binding modes. The result of the computationally predicted physicochemical properties including ADMET for the selected compounds showed their great potential in becoming lead compounds upon optimization and thus could be used in treating the Zika virus diseases.

Keywords: Consensus scoring; Molecular docking; Virtual screening; Zika virus; Zoonotic disease.

MeSH terms

  • Antiviral Agents / chemistry
  • Antiviral Agents / pharmacology*
  • Binding Sites
  • Ligands
  • Molecular Docking Simulation
  • Research Design*
  • Zika Virus / drug effects*

Substances

  • Antiviral Agents
  • Ligands