A Quantitative Structure-Antioxidant Relationship (QSAR) model for 1,3,4-oxadiazole derivatives using PLS regression

Abstract

Antioxidants can control the generation of free radical by terminating the reaction chain. 1,3,4-oxadizol derivatives are the most important heterocyclic compounds which exhibit antioxidant activity. This study aims to build a reliable quantitative structure antioxidant relationship (QSAR) model of 1,3,4-oxadiazol derivatives using IPLS as a variable selection method, and PLS as a regression method. The QSAR model was developed based on the correlation between the antioxidant activities in DPPH (2, 2diphenyl-1-picrayl hydrazyl) assay of 52 oxadiazol derivatives and their molecular descriptors. Only three descriptors that contribute to the antioxidant property are identified and selected to build QSAR model. The performance of QSAR model is reported as r2cal (0.92) and the model is validated by leave-one-out cross-validation technique r2cv (0.91), and predicted correlation coefficient r2pre (0.91). Based on the findings, the iPLS-PLS model can explain 91% variance of antioxidant activity. The result shows that the GATS2m and E3s descriptors are positively correlated with DPPH values, while the R7s+ has negative correlations with DPPH values. This finding proves that the increasing atomic mass and central symmetric atoms of 1,3,4oxadiazol cause to increase the antioxidant activity. The final QSAR model can be used as a guide to predict free radical scavenger activities of new synthesized 1,3,4-oxadiazol compounds.