4.4 Article

Development of multiple QSAR models for consensus predictions and unified mechanistic interpretations of the free-radical scavenging activities of chromone derivatives

Journal

JOURNAL OF MOLECULAR MODELING
Volume 18, Issue 5, Pages 1819-1840

Publisher

SPRINGER
DOI: 10.1007/s00894-011-1198-x

Keywords

Antioxidant; Hologram quantitative structure-activity relationship; Group-based quantitative structure-activity relationship; 3D pharmacophore; Comparative molecular similarity indices

Funding

  1. Indian Council of Medical Research (ICMR), New Delhi

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Antioxidants are important defenders of the human body against nocive free radicals, which are the causative agents of most life-threatening diseases. The immense biomedicinal utility of antioxidants necessitates the development and design of new synthetic antioxidant molecules. The present report deals with the modeling of a series of chromone derivatives, which was done to provide detailed insight into the main structural fragments that impart antioxidant activity to these molecules. Four different quantitative structure-property relationship (QSAR) techniques, namely 3D pharmacophore mapping, comparative molecular similarity indices analysis (CoMSIA 3D-QSAR), hologram QSAR (HQSAR), and group-based QSAR (G-QSAR) techniques, were employed to obtain statistically significant models with encouraging external predictive potentials. Moreover, the visual contribution maps obtained for the different models signify the importance of different structural features in specific regions of the chromone nucleus. Additionally, the G-QSAR models determine the composite influence of pairs of substituent fragments on the overall antioxidant activity profiles of the molecules. Multiple models with different strategies for assessing structure-activity relationships were applied to reach a unified conclusion regarding the antioxidant mechanism and to provide consensus predictions, which are more reliable than values derived from a single model. The structural information obtained from the various QSAR models developed in the present work can thus be effectively utilized to design and predict the activities of new molecules belonging to the class of chromone derivatives.

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