Chalcones are 1,3-diphenyl-2-propene-1-one, in which two aromatic rings are linked by a three carbon α,β- unsaturated carbonyl system. These are abundant in edible plants and are considered to be precursors of flavonoids and isoflavonoids. Our objective is to study the relationship between the activities and structure, a 3D-QSAR study is applied to a set of 20 molecules for biological activity prediction derivatives. This study was conducted using the principal component analysis PCA method; the multiple linear regression method MLR and the artificial neural network ANN;The leave-one out cross-validation procedure was used to validate the ANN model for use it to predict the activity of others new compounds. The relevant descriptors obtained from the ANN showed a correlation coefficient of 0.949 models which is a good result. As a result of quantitative structure–activity relationships, we found that the model proposed in this study is constituted of major descriptors used to describe these molecules. The obtained results suggested that the proposed combination of several calculated parameters could be useful to predict the biological activity of derivatives of 1,3-diphenyl-2-propene-1-one.
