Predictive chemometric modeling of DPPH free radical-scavenging activity of azole derivatives using 2D- and 3D-quantitative structure-activity relationship tools.

Background: The endogenous antioxidants often fail to manage the systemic free radical overload resulting from extensive exposure to environmental pollutants and improper diet. Such free-radical burden over a prolonged period leads to oxidative stress, which in turn, promotes an array of fatal diseases.

Results: Five different in silico methodologies have been employed here for a series of azole derivatives, which identify the essential structural attributes of the molecules and quantify the contributions of the prime molecular prerequisites for designing compounds with improved antioxidant activity.

Conclusion: The importance of the different constituents is quantitatively analyzed using the descriptor-based quantitative structure-activity relationship and group-based quantitative structure-activity relationship models while the pharmacophore, comparative molecular similarity index analysis and hologram quantitative structure-activity relationship models serve as essential query tools for screening of azole compounds in order to select potent antioxidant molecules.