Comparative QSAR modeling of 2‐phenylindol derivatives for predicting the anticancer activity using genetic algorithm multiple linear regression and back‐propagation‐artificial neural network techniques

Abstract

Quantitative structure-activity relationship (QSAR) studies on a series of 2-phenylindole derivatives as anticancer drugs were performed to choice the important descriptor, which is responsible for their anticancer activity (expressed as pIC 50 ). The geometry optimizations were performed on the structures using Gaussian software with the density functional B3LYP and 6-311G(d,p) basis sets.Dragon software was used to calculate molecular descriptors, and the genetic algorithm (GA) procedure and backward regression were used to proper selection of the most relevant descriptors. The backward multiple linear regression (BW-MLR) and backpropagation-artificial artificial neural network (BP-ANN) were carried out to design QSAR models. The squared correlation coefficient (R 2 ) and the root mean squared error (RMSE) values of the GA-MLR model were calculated to be 0.2843 and 0.7001, respectively. The BP-ANN model was the most powerful, with the square of predictive correlation coefficient R 2 pred , root mean square error (RMSE), and absolute average deviation (AAD) which was equal to 0.9416, 0.0238, and 0.0099, respectively.

QSPR analysis to predict some quantum chemical properties of 2‐phenylindol derivatives as anticancer drugs using molecular descriptor and genetic algorithm multiple linear regression

“…Several studies have been conducted on the correlation between the chemical structure and anticancer activity of 2‐phenylindole derivatives using different methods such as the comparative molecular field analysis (CoMFA) [30] the Index of Ideality of Correlation (IIC) [31], factor analysis‐multiple linear regression (FA‐MLR) [32], and the Genetic algorithm‐multiple linear regression (GA‐MLR) and backpropagation artificial neural network (BP‐ANN) [33], but a few studies have been purposed of the connection between the chemical structure and thermodynamic properties of 2‐phenylindole derivatives.…”