QSAR Model Generation of Phthalazinones as Poly (ADP-Ribose) Polymerase Inhibitors by the Genetic Algorithm and Multiple Linear Regression (GA-MLR) Method: A Ligand-Based Approach for Cancer Drug Design

Abstract

Poly (ADP-ribose) polymerase-1 (PARP-1), an enzyme known for catalyzing the attachment (covalently) of polymers of ADP-ribose moieties on itself and its target proteins, has been reported in recent study to regulate gene expression in prostate cancer. BRCA mutations are associated in the sensitivity of PARP inhibitors. The present study aimed to develop a Quantitative Structure-Activity Relationship (QSAR) model with Phthalazinones, inhibitors of PARP-1. Phthalazinones were divided into training and test sets to build the QSAR model. Among the several topological, constitutional, geometrical, electronic and hybrid descriptors generated as inputs to the model, three variables were selected by adopting the genetic algorithm subset selection method (GA). The correctness of the proposed model was accounted for by using the following evaluation techniques: Y-randomization, Validation of the external data test set and cross-validation. The model was found to have a good predictive ability and could be used for designing similar group of compounds.