Comprehensive investigation of network pharmacology, computational modeling, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in rheumatoid arthritis.

Abstract

Rheumatoid arthritis is a chronic autoimmune disease characterized by inflammation and joint damage, imposing a significant burden on affected individuals worldwide. Flavonoids, a class of natural compounds abundant in various plant-based foods, have shown promising anti-inflammatory and immunomodulatory effects, suggesting their potential as therapeutic agents for RA. In this study, we conducted a comprehensive investigation of identified LCMS compounds utilizing network pharmacology, computational modeling, in silico approaches, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in RA treatment. The study identified 5 flavonoid structures with common targets via LCMS and Integration of network pharmacology approaches enabled a comprehensive evaluation of the pharmacological profile of flavonoids in the context of RA treatment, guiding the selection of promising candidates for further experimental validation and clinical development. The top 10 targets were AKT1, PI3KR1, CDK2, EGFR, CDK6, NOS2, FLT3, ALOX5, CCNB1, and PTPRS via PPI network. The investigation emphasized several pathways, including the AGE-RAGE signaling pathway, resistance to EGFR tyrosine kinase inhibitors, the PI3K-AKT signaling network, and the Rap 1 signaling pathway. In silico studies estimated binding affinities that ranged from - 7.0 to - 10.0 kcal/mol. Schaftoside and Vitexin showed no toxicity in computational approach and found suitable for further investigations. Overall, our study underscores the potential of flavonoids as therapeutic agents for RA and highlights the utility of integrative approaches combining network pharmacology, computational modeling, in silico methods, and pharmacokinetic assessment in drug discovery and development processes.