Exploring Secondary Metabolites Database of Apocynaceae, Menispermaceae, and Annonaceae to Select Potential Anti-HCV Compounds.
Alkaloids
Hepatitis C virus
Ligand-based virtual screening
Molecular
dynamics
Structure-based virtual screening
Terpenes.
Journal
Current topics in medicinal chemistry
ISSN: 1873-4294
Titre abrégé: Curr Top Med Chem
Pays: United Arab Emirates
ID NLM: 101119673
Informations de publication
Date de publication:
2019
2019
Historique:
received:
14
11
2018
revised:
27
03
2019
accepted:
27
03
2019
pubmed:
11
5
2019
medline:
10
9
2019
entrez:
11
5
2019
Statut:
ppublish
Résumé
Hepatitis C is a disease that constitutes a serious global health problem, is often asymptomatic and difficult to diagnose and 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 to combine structure-based and ligand-based virtual screening (VS) techniques to select potentially active molecules against four HCV target proteins from in-house secondary metabolite dataset (SistematX). From the ChEMBL database, we selected four sets of 1199, 355, 290 and 237chemical structures with inhibitory activity against different targets of HCV to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, a ligandbased 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 analyses approach combining ligand-based and structure-based VS, three alkaloids were selected as potential anti-HCV compounds. The selected structures are a starting point for further studies in order to develop new anti- HCV compounds based on natural products.
Sections du résumé
BACKGROUND
BACKGROUND
Hepatitis C is a disease that constitutes a serious global health problem, is often asymptomatic and difficult to diagnose and 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.
OBJECTIVE
OBJECTIVE
The search for new drugs from natural products has been outstanding in recent years. The aim of this study was to combine structure-based and ligand-based virtual screening (VS) techniques to select potentially active molecules against four HCV target proteins from in-house secondary metabolite dataset (SistematX).
MATERIALS AND METHODS
METHODS
From the ChEMBL database, we selected four sets of 1199, 355, 290 and 237chemical structures with inhibitory activity against different targets of HCV to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, a ligandbased 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.
RESULTS
RESULTS
Finally, using consensus analyses approach combining ligand-based and structure-based VS, three alkaloids were selected as potential anti-HCV compounds.
CONCLUSION
CONCLUSIONS
The selected structures are a starting point for further studies in order to develop new anti- HCV compounds based on natural products.
Identifiants
pubmed: 31074368
pii: CTMC-EPUB-98435
doi: 10.2174/1568026619666190510094228
doi:
Substances chimiques
Antiviral Agents
0
Enzyme Inhibitors
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
900-913Informations de copyright
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