The global population is ageing rapidly, with the number of people aged 60 and above expected to reach 2.1 billion by 2050. This shift is driving a rise in chronic diseases, including diabetes, which is projected to affect 592 million people by 2035. These trends highlight the urgent need for novel therapeutic strategies and better understanding of disease mechanisms. Resveratrol and quercetin, two widely recognized polyphenols, are highly valued for their potent antioxidant and anti-inflammatory properties, demonstrating significant promise in mitigating and improving diabetic conditions by addressing core pathological features such as oxidative stress and insulin resistance. This study leverages computational chemistry techniques to elucidate the putative mechanisms of action of resveratrol and quercetin within the context of diabetic pathogenesis. To achieve this, a target prediction analysis was performed for both molecules using SwissTargetPrediction and EpigeneticTargetProfiler, followed by a structure-based target fishing utilizing TargetFisher. From the list of the predicted targets, we selected three key enzymes: monoamine oxidase A (MAO-A) and monoamine oxidase B (MAO-B), mitochondrial enzymes linked to oxidative stress and inflammation in diabetic conditions, and insulin-like growth factor 1 receptor (IGF-1R), which activates signalling pathways essential for insulin sensitivity and beta-cell function. These targets were chosen due to their established roles in metabolic signalling and oxidative pathways relevant to diabetes progression. Molecular docking analyses indicated the potential of quercetin and resveratrol to modulate the function of these enzymes and to confirm their viability for continued exploration of the therapeutic potential of these natural products in both combating metabolic ageing and managing diabetic disease.

Introduction: Natural polyphenolics are frequently inefficient in metabolic disorders due to multi-target promiscuity and restrictive in vivo bioavailability. This study proposes a chemoinformatics framework utilizing human bioactivity data to map micro-structural variations of privileged scaffolds to macro-systemic network perturbations, establishing a baseline for biomarker-guided supplement formulation. Methods: Human screening assays for quercetin, resveratrol, and five elite analogues (kaempferol, myricetin, fisetin, piceatannol, and pterostilbene) were extracted from the ChEMBL database. Over 1400 entries were filtered through an in silico pharmacokinetic constraint (pChEMBL = 6.0) to construct empirical Structure–Activity Relationship (SAR) matrices and a bipartite compound-target-extended disease network resolving an additional 190 unique protein nodes. Results: Flavonoid B-ring hydroxylation strictly governed target selectivity: monohydroxylation (kaempferol) optimized dipeptidyl peptidase 4 binding (DPP-4, Max pChEMBL = 6.31), whereas a di-hydroxylated catechol motif (quercetin) maximized aldo-keto reductase 1B1 potency (Max pChEMBL = 7.83). Transitions to methoxylated stilbenes (pterostilbene) maximized target occupancy within the hydrophobic catalytic domain of protein deacetylase HDAC6 (Max pChEMBL = 6.26), while low-steric, reduced-hydroxylation patterns (kaempferol) favoured casein kinase 2 (Max pChEMBL = 6.68). Conclusions: These findings reconcile previous monoamine oxidase (MAO-A/B) molecular docking leads by contextualizing lower-affinity hubs within a broader polypharmacological network. These empirical SAR observations provide a systems-level knowledge base suitable for adaptive decision-support systems designed to personalize phytochemical combinations dynamically based on metabolic markers like glycated hemoglobin (HbA1c).

Aging is a complex biological process defined by a series of molecular and cellular changes known as the hallmarks of aging. Polyphenols, particularly quercetin, are increasingly being studied for their potential anti-aging effects. This analysis considered two studies. The first, conducted on the organism S. vetulus, demonstrated that quercetin extends both average and maximum lifespan, and improves glycolytic and energy metabolism through the regulation of key enzymes and signaling pathways. The second, a clinical study involving patients with type 2 diabetes, showed a beneficial impact of quercetin on bio-clinical parameters, including a reduction in body mass index and anxiety levels. The efficacy of quercetin depends largely on its biotransformation via the gut microbiota, while its metabolites further contribute to its therapeutic effects. It is concluded that quercetin holds promise as a natural geroprotector; however, further research is needed to determine the optimal dosage and duration of treatment.