title: Variable selection and model validation of 2D and 3D molecular descriptors.
abstract: We have found that molecular shape and electrostatics, in conjunction with 2D structural fingerprints, are important variables in discriminating classes of active and inactive compounds. The subject of this paper is how to explore the selection of these variables and identify their relative importance in quantitative structure-activity relationships (QSAR) analysis. We show the use of these variables in a form of similarity searching with respect to a crystal structure of a known bound ligand. This analysis is then validated through k-fold cross-validation of enrichments via several common classifiers. Additionally, we show an effective methodology using the variables in hypothesis generation; namely, when the crystal structure of a bound ligand is not known.
authors.affiliation: OpenEye Scientific Software, Inc., Santa Fe, NM 87507, USA. anthony@www.eyesopen.com
authors.forename: Anthony
authors.initials: A
authors.lastname: Nicholls
authors.forename: Norah E
authors.initials: NE
authors.lastname: MacCuish
authors.forename: John D
authors.initials: JD
authors.lastname: MacCuish
mesh_terms: D015220:Calcium Channels / Q000737:chemistry; D016000:Cluster Analysis; D051546:Cyclooxygenase 2; D004298:Dopamine / Q000737:chemistry; D008958:Models, Molecular; D011374:Progesterone / Q000737:chemistry; D011451:Prostaglandin-Endoperoxide Synthases / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D055672:Static Electricity
chemical_list: D015220:Calcium Channels; D011374:Progesterone; D051546:Cyclooxygenase 2; D011451:Prostaglandin-Endoperoxide Synthases; D004298:Dopamine
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