Linked Life Data

20870313

Source:http://linkedlifedata.com/resource/pubmed/id/20870313

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2010-10-11
pubmed:abstractText
N-formyl peptide receptors (FPRs) are important in host defense. Because of the potential for FPRs as therapeutic targets, recent efforts have focused on identification of non-peptide agonists for two FPR subtypes, FPR1 and FPR2. Given that a number of specific small-molecule agonists have recently been identified, we hypothesized that computational structure-activity relationship (SAR) analysis of these molecules could provide new information regarding molecular features required for activity. We used a training set of 71 compounds, including 10 FPR1-specific agonists, 36 FPR2-specific agonists, and 25 non-active analogs. A sequence of (1) one-way analysis of variance selection, (2) cluster analysis, (3) linear discriminant analysis, and (4) classification tree analysis led to the derivation of SAR rules with high (95.8%) accuracy for correct classification of compounds. These SAR rules revealed key features distinguishing FPR1 versus FPR2 agonists. To verify predictive ability, we evaluated a test set of 17 additional FPR agonists, and found that the majority of these agonists (>94%) were classified correctly as agonists. This study represents the first successful application of classification tree methodology based on atom pairs to SAR analysis of FPR agonists. Importantly, these SAR rules represent a relatively simple classification approach for virtual screening of FPR1/FPR2 agonists.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1768-3254
pubmed:author
pubmed:copyrightInfo
Copyright © 2010 Elsevier Masson SAS. All rights reserved.
pubmed:issnType
Electronic
pubmed:volume
45
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5406-19
pubmed:dateRevised
2011-11-1
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Computational structure-activity relationship analysis of small-molecule agonists for human formyl peptide receptors.
pubmed:affiliation
Department of Chemistry, Altai State Technical University, Barnaul 656038, Russia. aikhl@chem.org.ru
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural