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Future medicinal chemistry

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


PMID 23464517

Abstract

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. 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. 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.