A practical overview of quantitative structure-activity relationship

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dc.contributor.authorIsarankura-Na-Ayudhya, Chartchalerm
dc.contributor.authorNaenna, Thanakorn
dc.contributor.authorNantasenamat, Chanin
dc.contributor.authorPrachayasittikul, Virapong
dc.date.accessioned2009-07-08T08:22:46Z
dc.date.available2009-07-08T08:22:46Z
dc.date.issued2009-07-08T08:22:46Z
dc.description.abstractQuantitative structure-activity relationship (QSAR) modeling pertains to the construction of predictive models of biological activities as a function of structural and molecular information of a compound library. The concept of QSAR has typically been used for drug discovery and development and has gained wide applicability for correlating molecular information with not only biological activities but also with other physicochemical properties, which has therefore been termed quantitative structure-property relationship (QSPR). Typical molecular parameters that are used to account for electronic properties, hydrophobicity, steric effects, and topology can be determined empirically through experimentation or theoretically via computational chemistry. A given compilation of data sets is then subjected to data preprocessing and data modeling through the use of statistical and/or machine learning techniques. This review aims to cover the essential concepts and techniques that are relevant for performing QSAR/QSPR studies through the use of selected examples from our previous work.en
dc.identifier.urihttp://hdl.handle.net/2003/26225
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-690
dc.language.isoen
dc.relation.ispartofseriesEXCLI Journal ; Vol. 8, 2009en
dc.subjectmultivariate analysisen
dc.subjectQSARen
dc.subjectquantitative structure-activity relationshipen
dc.subjectquantitative structure-property relationshipen
dc.subject.ddc610
dc.titleA practical overview of quantitative structure-activity relationshipen
dc.typeText
dc.type.publicationtypearticleen
dcterms.accessRightsopen access
eldorado.dnb.zdberstkatid2132560-1

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