A novel QSAR model for predicting induction of apoptosis by 4-aryl-4H-chromenes.
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.
Afantitis
Antreas
A
School of Chemical Engineering, National Technical University of Athens, Athens, Greece.
Melagraki
Georgia
G
Sarimveis
Haralambos
H
Koutentis
Panayiotis A
PA
Markopoulos
John
J
Igglessi-Markopoulou
Olga
O
D000465:Algorithms; D017209:Apoptosis / Q000187:drug effects*; D001578:Benzopyrans / Q000138:chemical synthesis* / Q000494:pharmacology*; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D003627:Data Interpretation, Statistical; D008958:Models, Molecular; D008968:Molecular Conformation; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D015203:Reproducibility of Results
D001578:Benzopyrans