Linked Life Data

7120279

Source:http://linkedlifedata.com/resource/pubmed/id/7120279

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
1982-12-2
pubmed:abstractText
A pattern-recognition analysis using the ADAPT system was performed on a set of 9-anilinoacridine antitumor agents, to determine whether computer-generated descriptors could be used to separate active from inactive compounds. A training set of 213 compounds was chosen by random computer selection from a list of 776 structures. Maximal increase in life span at the LD10 dosage, a response which is difficult to model using traditional Hansch analysis, was used as the measure of biological activity. A set of 18 molecular descriptors, including fragment, substructure environment, and physicochemical property descriptors (molar refraction, partial electronic charge) was identified which could correctly classify 94% of the compounds in the training set (97% of active and 85% of inactive compounds). Eight of the inactive compounds that were misclassified contained amino substituents, suggesting a role for ionization. The weight vector that was obtained from the training set was applied to a prediction set of 50 compounds that were not included in the original analysis and to a set of 69 structures drawn from the recent literature. The prediction set results, ranging from 73 to 86% correct, were lower than those of the training set, but they clearly indicate that pattern-recognition techniques can be useful in the screening of proposed or already existing agents and especially useful for the identification of active compounds.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0022-2623
pubmed:author
pubmed:issnType
Print
pubmed:volume
25
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
899-908
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
1982
pubmed:articleTitle
Structure-antitumor activity relationships of 9-anilinoacridines using pattern recognition.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.