A novel QSAR model for predicting induction of apoptosis by 4-aryl-4H-chromenes

Afantitis, A; Melagraki, G; Sarimveis, H; Koutentis, PA; Markopoulos, J; Igglessi-Markopoulou, O

dc.contributor.author	Afantitis, A	en
dc.contributor.author	Melagraki, G	en
dc.contributor.author	Sarimveis, H	en
dc.contributor.author	Koutentis, PA	en
dc.contributor.author	Markopoulos, J	en
dc.contributor.author	Igglessi-Markopoulou, O	en
dc.date.accessioned	2014-03-01T01:23:26Z
dc.date.available	2014-03-01T01:23:26Z
dc.date.issued	2006	en
dc.identifier.issn	0968-0896	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16974
dc.subject	Apoptosis	en
dc.subject	Chromenes	en
dc.subject	Molecular modeling	en
dc.subject	QSAR	en
dc.subject.classification	Biochemistry & Molecular Biology	en
dc.subject.classification	Chemistry, Medicinal	en
dc.subject.classification	Chemistry, Organic	en
dc.subject.other	chromene derivative	en
dc.subject.other	apoptosis	en
dc.subject.other	article	en
dc.subject.other	data base	en
dc.subject.other	diagnostic accuracy	en
dc.subject.other	linear regression analysis	en
dc.subject.other	multiple linear regression analysis	en
dc.subject.other	physical chemistry	en
dc.subject.other	quantitative structure activity relation	en
dc.subject.other	randomization	en
dc.subject.other	validation process	en
dc.subject.other	Algorithms	en
dc.subject.other	Apoptosis	en
dc.subject.other	Benzopyrans	en
dc.subject.other	Chemistry, Physical	en
dc.subject.other	Data Interpretation, Statistical	en
dc.subject.other	Models, Molecular	en
dc.subject.other	Molecular Conformation	en
dc.subject.other	Predictive Value of Tests	en
dc.subject.other	Quantitative Structure-Activity Relationship	en
dc.subject.other	Regression Analysis	en
dc.subject.other	Reproducibility of Results	en
dc.title	A novel QSAR model for predicting induction of apoptosis by 4-aryl-4H-chromenes	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.bmc.2006.05.061	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.bmc.2006.05.061	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	A linear quantitative structure-activity relationship (QSAR) model is presented for modeling and predicting induction of apoptosis by 4-aryl-4H-chromenes. The model was produced by using the multiple linear regression (MLR) technique on a database that consists of 43 recently discovered 4-aryl-4H-chromenes. Among the 61 different physicochemical, topological, and structural descriptors that were considered as inputs to the model, seven variables were selected using the elimination selection-stepwise regression method (ES-SWR). The physical meaning of each descriptor is discussed. The accuracy of the proposed MLR model is illustrated using the following evaluation techniques: cross-validation, validation through an external test set, and Y-randomization. Furthermore, the domain of applicability which indicates the area of reliable predictions is defined. (c) 2006 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Bioorganic and Medicinal Chemistry	en
dc.identifier.doi	10.1016/j.bmc.2006.05.061	en
dc.identifier.isi	ISI:000240650500024	en
dc.identifier.volume	14	en
dc.identifier.issue	19	en
dc.identifier.spage	6686	en
dc.identifier.epage	6694	en