Docking Descriptor-Based QSAR Model for Prediction of Pyrimidine Series Activities as Novel Phosphodiesterase10A Inhibitors

Schizophrenia is a mental disorder that represents a vital unmet medical need [1]. Recently inhibition of phosphodiesterase (PDE10A) enzyme as an alternative approach is shown to have potential in treatment of schizophrenia [2, 3]. Objective of this study is investigating inhibition activity of 87 structurally diverse pyrimidine-based derivatives as a novel therapeutic drug candidate for PDE10A inhibition. A combination of docking and quantitative structure-activity relationship (QSAR) approaches were performed to characterize the relation between the structural features and the PDE10A inhibition activity. Molecular docking computation was performed by AutoDock 4.2 using the Lamarckian genetic algorithm. Conformations of pyrimidine inhibitors originating from docking with the lowest binding free energy were used to calculate molecular descriptors in a structure-based QSAR model. Molecular structural descriptors were calculated by BINding ANAlyzer (BINANA) Dragon, CODESSA and Accelrys Materials Studio software from docked conformers. The data set was divided into 69 training and 18 test sets based on hierarchical clustering method. The stepwise multiple linear regression as a variable selection method was carried out on the training set for selecting the most relevant descriptors. Among selected descriptors the most important ones, encoded topological features of molecules (e.g. the more branches, the more complex molecule) which can affect on steric interactions of ligand and the protein. Then support vector machine (SVM) was used to derive model based on obtained descriptors. The statistical parameters of R2 and standard error for training set of SVM model were; 0.95 and 0.14, respectively, and were 0.93 and 0.18 for the test set. Leave one out cross validation test was used for assessment of the predictive power and validity of models which led to cross-validation correlation coefficient ) of 0.82.