Paper Info
Title
Homology Model-Based Virtual Screening for GPCR Ligands Using Docking and Target-Biased Scoring
Abstract
The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS). Our approach was evaluated in retrospective virtual screening experiments for antagonists of the metabotropic glutamate receptor (mGluR) subtype 5. The results of our approach were compared to the results obtained by conventional scoring functions (Dock-Score, PMF-Score, Gold-Score, ChemScore, and FlexX-Score). The IFS lead to significantly higher enrichment rates, relative to the competing scoring functions. Though using a target-biased scoring approach, the results were not biased toward the chemical classes of the reference structures. Our results indicate that the presented approach has the potential to serve as a general setup for successful structure-based GPCR virtual screening.
Year
DOI
Venue
2008
10.1021/ci8000265
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Keywords
DocType
Volume
virtual screening,homology modeling
Journal
48
Issue
ISSN
Citations 
5
1549-9596
3
PageRank 
References 
Authors
0.52
0
2
Name
Order
Citations
PageRank
Tanja Weil171.63
Steffen Renner2645.18