Ligand-Based and Structure-Based virtual screening for the discovery of natural inhibitor the Hepatitis C Virus

Marcus Scotti,Renata Priscila Costa Barros

doi:10.3390/mol2net-04-05873

Abstract

Hepatitis C is a disease that constitutes a serious global health problem, is often asymptomatic and difficult to diagnose, about 60-80% of infected patients develop chronic diseases over time. As there is no vaccine against hepatitis C virus (HCV), developing new cheap treatments is a big challenge. The search for new drugs from natural products has been outstanding in recent years. The aim of this study was combining structure-based and ligand-based virtual screening (VS) techniques to select potentially active molecules against two HCV target proteins from in-house secondary metabolite dataset (SistematX). From the ChEMBL database, we selected two sets of 1199 and 237chemical structures with inhibitory activity against different targets of HCV to create random forest models with an accuracy value higher than 72% for cross-validation and test sets. Afterward, a ligand-based virtual screen of the entire 1848 secondary metabolites database stored in SistematX was performed. In addition, a structure-based virtual screening was also performed for the same set of secondary metabolites using molecular docking. Finally, using consensus analyzes approach combining ligand-based and structure-based VS, two alkaloids and one triterpene were selected as potential anti-HCV compounds.

Highlights

Hepatitis C is a disease that constituted a serious public health problem worldwide, is a liver disease and makes patients affected by this disease vulnerable to cirrhosis, hepatic insufficiency, hepatocellular carcinoma, etc
Several studies have shown that patients with hepatic cirrhosis tend to have early hepatitis C virus (HCV) RNA recurrence in weeks and recur after cessation of treatment with AADs
The area under the curve was greater than 81% for the cross-validation sets, and greater than 85% for the test sets, revealing that the models are capable of performing a good classification and prediction rate

Summary

Introduction

Hepatitis C is a disease that constituted a serious public health problem worldwide, is a liver disease and makes patients affected by this disease vulnerable to cirrhosis, hepatic insufficiency, hepatocellular carcinoma, etc. [1]. Hepatitis C is a disease that constituted a serious public health problem worldwide, is a liver disease and makes patients affected by this disease vulnerable to cirrhosis, hepatic insufficiency, hepatocellular carcinoma, etc. A new era in the treatment of hepatitis C was started in 2011 from the approval of first generation direct acting antiviral agents (AADs) [3]. In 2014, more potent and better new AADs became available by achieving a sustained immune response (SVR). Several studies have shown that patients with hepatic cirrhosis tend to have early HCV RNA recurrence in weeks and recur after cessation of treatment with AADs. A major problem in this new era of HCV treatment is the extremely high cost of medications [3, 4]

Objectives

Methods

Results

Conclusion