Quantitative structure-activity studies on aldehyde oxidase inhibitors

Abstract

Aldehyde oxidase (AOX) (EC1.2.3.1) is a cytosolic enzyme belongs to molybdo-flavoenzyme family. This enzyme is responsible for metabolism of nitrogen-containing drugs as well as oxidation products of CYP450 and monoamine oxidase. Several drugs can inhibit AOX and co-administration with drugs metabolized by this enzyme can induce drug-drug interactions. Therefore, prediction of biological activity of AOX inhibitors via computational approaches is of importance in the field of drug toxicity and drug-drug interaction. Objective:The purpose of this study was prediction of biological activity of AOX inhibitors using quantitative structure-activity relationship. Materials and methods:Following the data collection, the structures of AOX inhibitors were generated and energy minimized using Hyperchem software. For 2D-QSAR, genetic algorithm was employed for model development. For developing model using 3D-QSAR study, Pentacle program and PLS method were applied. In the case of model using 6D-QSAR method, Quasar software and genetic algorithm were utilized. Finally, cross validation was performed for each of generated QSAR models. Results:Analysis the results demonstrated that the 2D-QSAR and 6D-QSAR models were capable of predicting biological activity of AOX inhibitors. By inspection of statistical metrics, 6D-QSAR model provides better prediction of endpoint values. However, the 3D-QSAR based model was not successful in prediction of AOX inhibitory activity based on externally validated values. Conclusion: The results of the current investigation can be used for prediction of AO inhibitors in the field of drug toxicity and drug-drug interaction studies.