Computational analysis of De Novo evolution of Hepatitis C virus NS5B polymerase inhibitors

P. O.Yuan Chen, Wei Tse Hsu, Mien D.E. Jhuo, Che Yen Ou, Tzu-Hurng Cheng, Tzu Ching Shih, Chieh Hsi Wu, Rick Sai Chuan Wu, T. E.Chun Hsia, Jing Gung Chung

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

HCV (Hepatitis C virus) that causes chronic liver disease. HCV NS5B RNA-dependent RNA polymerase (RbRp) and NS3 protease are able to affect virtual replication of genes. Computer-aided drug design (CADD) aims at designing new molecules with pharmacological activity. In this study, we used the Discovery Studio 2.0 program and the scoring function to estimate the Dock Score, piecewise linear potential 1 (PLP1), piecewise linear potential 2 (PLP2), and potential of mean force (PMF) score of novel compounds. In this way, novel compounds with "de novo evolution" can be found. Using the the pharmacophore features that are near the receptor pocket and the score functions to calculate scores for the ligand-receptor interaction, the new ligands were selected, developed and virtually placed in the binding site of the receptor. A new compound, EVO12, gave the best score, indicating that it may be an efficient polymerase inhibitor of HCV NS5B.

Original languageEnglish
Pages (from-to)219-228
Number of pages10
JournalIn Vivo
Volume25
Issue number2
Publication statusPublished - 2011
Externally publishedYes

Keywords

  • Aromatic substituents
  • Computational analysis
  • HCV NS5B polymerase inhibitors

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology
  • Pharmacology

Fingerprint

Dive into the research topics of 'Computational analysis of De Novo evolution of Hepatitis C virus NS5B polymerase inhibitors'. Together they form a unique fingerprint.

Cite this