13C NMR spectral data and molecular descriptors to predict the antioxidant activity of flavonoids / Dados espectrais de RMN 13C e descritores moleculares para prever a atividade antioxidante dos flavonóides

Tissue damage due to oxidative stress is directly linked to development of many, if not all, human morbidity factors and chronic diseases. In this context, the search for dietary natural occurring molecules with antioxidant activity, such as flavonoids, has become essential. In this study, we investigated a set of 41 flavonoids (23 flavones and 18 flavonols) analyzing their structures and biological antioxidant activity. The experimental data were submitted to a QSAR (quantitative structure-activity relationships) study. NMR 13C data were used to perform a Kohonen self-organizing map study, analyzing the weight that each carbon has in the activity. Additionally, we performed MLR (multilinear regression) using GA (genetic algorithms) and molecular descriptors to analyze the role that specific carbons and substitutions play in the activity.

Danos aos tecidos devido ao estresse oxidativo estão diretamente ligados ao desenvolvimento de muitos, senão todos, os fatores de sedentarismo e de doenças crônicas. Neste contexto, a busca de moléculas naturais, que participam da nossa dieta e que possuam atividade antioxidante, flavonóides, torna-se de grande interesse. Neste estudo, nós investigamos um conjunto de 41 flavonóides (23 flavonas e 18 flavonóis), relacionando suas estruturas e atividade antioxidante. Os dados experimentais foram submetidos à análise de QSAR (relações quantitativas estrutura-atividade). Dados de RMN 13C foram utilizados para realizar um estudo do mapa auto-organizável de Kohonen, analisando o peso que cada carbono tem na atividade. Além disso, realizamos uma MLR (regressão múltipla) usando GA (algoritmos genéticos) e descritores moleculares para avaliar a influência de carbonos e substituições na atividade.

Self-organizing maps and VolSurf approach to predict aldose reductase inhibition by flavonoid compounds

Aldose Reductase (AR) is the polyol pathway key enzyme which converts glucose to sorbitol. High glucose availability in insulin resistant tissues in diabetes leads into an accumulation of sorbitol, which has been associated with typical chronic complications of this disease, such as neuropathy, nephropathy and retinopathy. In this study, 71 flavonoids AR inhibitors were subjected to two methods of SAR to verify crucial substituents. The first method used the PCA (Principal Component Analysis) to elucidate physical and chemical characteristics in the molecules that would be essential for the activity, employing VolSurf descriptors. The rate obtained explained 53 percent of the system total variance and revealed that a hydrophobic-hydrophilic balance in the molecules is required, since very polar or nonpolar substituents decrease the activity. Artificial Neural Networks (ANNs) was also employed to determine key substituents by evaluating substitution patterns, using NMR data. This study had a high success rate (85 percent accuracy in the training set and 88 percent accuracy in the test set) and showed polihydroxilations are essential for high activity and methoxylations and glicosilations primarily at positions C7, C3' and C4' decrease the activity.