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Study of the structure‐activity relationship for theoretical molecular descriptors using density functional theory and chemometric methods in cannabinoid metabolites
Author(s) -
e Silva Tânia B.,
Pereira Mariano A.,
Malta Valéria S.,
Bento Edson S.,
SanMiguel Miguel A.,
Ziolli Roberta L.,
Martins João B. L.,
Sih Andre,
Taft Carlton A.
Publication year - 2008
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/qua.21696
Subject(s) - principal component analysis , chemistry , density functional theory , steric effects , cannabinoid , quantum chemical , computational chemistry , cluster (spacecraft) , molecular descriptor , k nearest neighbors algorithm , quantitative structure–activity relationship , molecule , stereochemistry , artificial intelligence , computer science , organic chemistry , biochemistry , receptor , programming language
A set of 30 cannabinoid metabolites has been investigated from a combination of electronic and chemometric methods. Density functional calculations have been carried out to obtain optimized geometries, energies, and selected molecular properties. These molecular descriptors take into account steric effects, electronic properties, and chemical reactivity. The use of statistical methods including principal component analysis (PCA), hierarchical cluster analysis (HCA) and nonhierarchical cluster analysis (K‐means), nearest neighbor (KNN) and artificial neural networks (ANN) has enabled to classify the compounds into psychoactive, moderately psychoactive and psychoinactive groups in good agreement with experimental evidences. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2008