title: Identification of active molecular sites using quantum-self-similarity measures.
abstract: A novel approach to construct theoretical QSAR models is proposed. This technique, based on the systematic use of quantum similarity measures as theoretical molecular descriptors, opens the possibility to localize and to identify the position of the bioactive part of drug molecules in situations, where the nature of the pharmacophore is not known. To test the reliability of this new approach, the method has been applied to the study of steroids binding to corticosteroid-binding human globulin. The studied molecules involved the set of 31 Cramer's steroids, often used as a benchmark set in QSAR studies. It has been shown that theoretical QSAR models based on the present procedure are superior to those derived from alternative existing approaches. In addition, a new method to measure the statistical significance of multiparameter QSAR models is also proposed.
authors.affiliation: Institute of Computational Chemistry, University of Girona, Catalonia, Spain.
authors.forename: L
authors.initials: L
authors.lastname: Amat
authors.forename: E
authors.initials: E
authors.lastname: Besalú
authors.forename: R
authors.initials: R
authors.lastname: Carbó-Dorca
authors.forename: R
authors.initials: R
authors.lastname: Ponec
mesh_terms: D001565:Benzoates / Q000737:chemistry; D001665:Binding Sites; D006801:Humans; D008956:Models, Chemical; D015394:Molecular Structure; D021281:Quantitative Structure-Activity Relationship; D013256:Steroids / Q000737:chemistry*; D014156:Transcortin / Q000737:chemistry*
chemical_list: D001565:Benzoates; D013256:Steroids; D014156:Transcortin