Linked Life Data

15494142

Source:http://linkedlifedata.com/resource/pubmed/id/15494142

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2004-10-20
pubmed:abstractText
This report describes the development, optimization, and implementation of a cell-based assay for high-throughput screening (HTS) to identify inhibitors to hepatitis C virus (HCV) replication. The assay is based on a HCV subgenomic RNA replicon that expresses beta-lactamase as a reporter for viral replication in enhanced Huh-7 cells. The drug targets in this assay are viral and cellular enzymes required for HCV replication, which are monitored by fluorescence resonance energy transfer using cell-permeable CCF4-AM as a beta-lactamase substrate. Digital image processing was used to visualize cells that harbor viral RNA and to optimize key assay development parameters such as transfection and culturing conditions to obtain a cell line which produced a robust assay window. Formatting the assay for compound screening was problematic due to small signal-to-background ratio and reduced potency to known HCV inhibitors. These technical difficulties were solved by using clavulanic acid, an irreversible inhibitor of beta-lactamase, to eliminate residual beta-lactamase activity after HCV replication was terminated, thus resulting in an improved assay window. HTS was carried out in 384-well microplate format, and the signal-to-background ratio and Z factor for the assay plates during the screen were approximately 13-fold and 0.5, respectively.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0003-2697
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
334
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
344-55
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
A cell-based beta-lactamase reporter gene assay for the identification of inhibitors of hepatitis C virus replication.
pubmed:affiliation
Department of Automated Biotechnology, Merck and Co., 502 Louise Lane., North Wales, PA 19454, USA. paul_zuck@merck.com
pubmed:publicationType
Journal Article