Linked Life Data

19051151

Source:http://linkedlifedata.com/resource/pubmed/id/19051151

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2008-12-3
pubmed:abstractText
The concept of quantitative SAR (QSAR) is inherently imbued with an expectation of predictivity, novel insights and the generation of useful hypotheses, particularly as applied to the drug discovery process. However, even recently developed QSAR models often appear to be flawed, characterized by mediocre predictive power and undecipherable descriptors. As a result, users may be able to derive only a vague notion of which molecular features are correlated to activity. Consideration of several precautions is necessary to attempt to circumvent the misuse and misunderstanding of the QSAR technique. Issues related with QSAR include an erroneous association of correlation with causation, the close relationship between large numbers of descriptors and the effect of chance factor, the misuse of the 'leave-one-out' paradigm, and finally, the QSAR enigma, wherein the predictivity of a model is not necessarily a measure of a model's utility.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1369-7056
pubmed:author
pubmed:issnType
Print
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
894-9
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Is QSAR relevant to drug discovery?
pubmed:affiliation
Bristol-Myers Squibb Co, Research and Development, Computer-Aided Drug Design, PO Box 4000, Princeton, NJ 08543, USA. arthur.doweyko@bms.com
pubmed:publicationType
Congresses