Flavonoids are a group of naturally occurring phytochemicals abundantly present in fruits, vegetables, and beverages such as wine and tea. In the past two decades, flavonoids have gained enormous interest because of their beneficial health effects such as anti-inflammatory, cardio-protective and anticancer activities. These findings have contributed to the dramatic increase in the consumption and use of dietary supplements containing high concentrations of plant flavonoids. The pharmacological effect of flavonoids is mainly due to their antioxidant activity and their inhibition of certain enzymes. In spite of abundant data, structural requirements and mechanisms underlying these effects have not been fully understood. This review presents the current knowledge about structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs) of the antioxidant activity of flavonoids. SAR and QSAR can provide useful tools for revealing the nature of flavonoid antioxidant action. They may also help in the design of new and efficient flavonoids, which could be used as potential therapeutic agents.
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The relationship between molecular descriptors and the inhibitory activity of aldose reductase (AR) for a series of coumarin and flavonoid derivatives has been investigated using a novel multivariate linear regression based on the ordered orthogonalized descriptor set. First, starting from the set of 31 descriptors we produced absolutely the best nonorthogonalized QSAR models with I descriptors (I ) 1-7). These models are always better than the models that the most authors achieve by the use of the stepwise inclusion-exclusion procedure.In the next step we realized all possible orthogonalization orderings of a given set of N descriptors (there are N! of these). The key result is that some orthogonalization orderings lead to QSAR models with I ordered orthogonalized descriptors that have higher values of both the correlation coefficient R and crossvalidated correlation coefficient R cv than the corresponding models with the same number of nonorthogonalized descriptors. In order to achieve the highest possible reliability in predicting the inhibition we produced several models that were obtained applying the ordered orthogonalization procedure on one set with five (N ) 5) and on two sets with seven (N ) 7) descriptors. Then the inhibitory activity for 34 coumarins and 30 flavonoids was predicted, and several compounds were detected with a very high inhibitory activity.
The HPLC retention times (RT) of 12 anthocyanidin malonylglucosides, which appear in flowers of Hibiscus syriacus, were calculated using several structure-property models based on three different types of orthogonalized topological indices, that is, the path numbers, the connectivity indices, and the Harary indices.The best agreement between the experimental and calculated values is achieved with a model with path numbers. This model is recommended to experimental researchers which are interested in quick assessment of the retention times of their newly found anthocyanin derivatives.
This indicates that the QSAR model, based on the consideration of all possible orthogonalization orderings, can predict inhibition of cAMP phosphodiesterase with considerable accuracy.
Simple QSAR/QSPR models have been developed which enable the prediction of the pK values and halflives of flavylium salts as a function of their molecular descriptors. On the basis of these results, as well as calculated UV-vis spectra, flavylium salt model structures are proposed, which are expected to be useful as potential food dyes.
A simple QSAR model of xanthine oxidase (XO) inhibitory flavylium salts, which enables prediction of the inhibitory potency of anthocyanidins as a function of their molecular properties, has been developed. The results obtained in the present work help to understand which of the several tautomeric anhydrobase species present in nearly neutral solution are mainly responsible for the inhibition of XO.
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