Quantitative Structure-Activity Relationship Study of Amino Acid Derivatives as Histone Deacetylase Inhibitors using the Genetic Algorithm – Multiple Linear Regression

Abstract

The quantitative structure-activity relationship (QSAR) of the amino acid derivatives for prediction of histone deacetylase inhibitors activity was studied. Semi-empirical quantum chemical calculations at the AM1 level were used to find the 3D geometry of the studied molecules. The suitable set of the molecular descriptors was calculated, and the important descriptors were selected by the genetic algorithm (GA). The predictive quality of the QSAR model was tested for an external set of eight compounds, randomly chosen out of 38 compounds. The genetic algorithm-multiple linear regression (GA-MLR) model with six selected descriptors was obtained. The accuracy of the proposed GA-MLR model was illustrated using to following evaluation techniques: cross-validation, validation through an external test set, and Y-randomization. This model, demonstrating high statistical qualities .The predictive ability of the model was found to be satisfactory and could be used for predicting the histone deacetylase inhibitors activity of the molecules with low prediction error.