QSAR Analysis, Molecular Docking and ADME Studies of Thiobarbituric Acid Derivatives as Thymidine Phosphorylase Inhibitors: A Rational Approach to Anticancer Drug Design by in silico Modelling

Abstract

Background: Thymidine Phosphorylase (TP) is an imperative target for cancer researchers. In the current research, quantitative structure-activity relationship (QSAR) models were demonstrated to identify new TP inhibitors. Objective: The main objective is to perform a QSAR study on a series of 19 derivatives of thiobarbituric acid and new molecules designed and dock to check potency and efficacy for anticancer activity. Methods: Multiple linear regression analysis (MLR) was used to establish a two-dimensional quantitative structure-activity relationship (2D-QSAR) with regression coefficient values of 0.9781, 0.9513, and 0.9819 for the training set (r2), leave-one-out (LOO) dependent internal regression (q2), and external test set regression (r2 _pred), respectively. Three-dimensional quantitative structure-activity relationship (3DQSAR) model, obtained by using the simulated annealing k nearest neighbour (SA-KNN) method (q2 = 0.7880). Newly designed molecules were subjected to docking studies with 7-deazaxanthine taken as standard. Results: Molecular modelling, structure-based drug design and docking study analysis were performed. The new chemical entities (NCE’s) designed, docked towards targeted receptor and show good results as compared to the standard 7-deazaxanthine. It was found that these molecules bind similar amino acid pocket regions as that of standard. Molecules bind at the active site of TP enzyme involving H bond interactions with shorter distances showed greater affinity. At last, the oral bioavailability and toxic effect were evaluated as absorption, distribution, metabolism, and elimination (ADME) studies by computational means of the Qikprop tool of Schrodinger. Conclusion: One of the most successful and fast-increasing methodologies is molecular modelling. It not only aids in the prediction of specific target compounds but also aids in the cost reduction of valuable substances. QSAR and docking study was performed, and most of the molecules have shown good dock scores. Based on these results, NCE’s for anticancer activity were successfully designed and analysed in this research work which will be helpful for effective drug synthesis with less toxicity in the future. Others: 2D QSAR model was generated by three methods, and the best one was selected for further study. NCEs were planned based on descriptors such as topological, electrostatic, steric, and hydrophobic substitutions around the core.