Predictive Modeling of Antioxidant Coumarin Derivatives Using Multiple Approaches: Descriptor-Based QSAR, 3D-Pharmacophore Mapping, and HQSAR

利用多种方法对香豆素类抗氧化剂衍生物进行预测建模:基于描述符的QSAR、3D药效团映射和HQSAR

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Abstract

The inability of the systemic antioxidants to alleviate the exacerbation of free radical formation from metabolic outputs and environmental pollutants claims an urgent demand for the identification and design of new chemical entities with potent antioxidant activity. In the present work, different QSAR approaches have been utilized for identifying the essential structural attributes imparting a potential antioxidant activity profile of the coumarin derivatives. The descriptor-based QSAR model provides a quantitative outline regarding the structural prerequisites of the molecules, while 3D pharmacophore and HQSAR models emphasize the favourable spatial arrangement of the various chemical features and the crucial molecular fragments, respectively. All the models infer that the fused benzene ring and the oxygen atom of the pyran ring constituting the parent coumarin nucleus capture the prime pharmacophoric features, imparting superior antioxidant activity to the molecules. The developed models may serve as indispensable query tools for screening untested molecules belonging to the class of coumarin derivatives.

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