ABSTRACT

Rheumatoid Arthritis (RA) is a disease that has caused a serious issue in our society with a whooping increase in its percentage of prevalence from 1990 to 2021. Morning stiffness, rise in temperature and pain during any activity are few symptoms that are prevalent among the RA patients. As the prevalence increases there is a need for drug discovery with more safety and efficacy. Lashuna (Allium sativum L) is a drug of choice in case of RA as it is mentioned in several classical texts of Ayurveda. Though the drug is used and mentioned for treatment, exact mechanism of the drug will give us further more understanding in its usage. For this computational method was used to recover phytochemicals related to the drug was obtained from plant databases and targets related to disease were collected form disease databases. After recovering the overlapping targets and generating PPI network, the KEGG pathway analysis done. With this topological analysis of ‘Target – Compound – Pathway’ was done. Followed by this molecular docking and visualization of the targets and phytochemicals was done. A total of 53 overlapping targets, 10 pathways and 25 phytochemicals were derived. Among this based on the degree in topological analysis 3 targets and phytochemicals were chosen and docking results showed that Quercetin has highest binding affinity towards FABP4 and PDGFRA targets of the disease. Further in-vivo and Clinical studies are required to find out its dosage and efficacy in huge volunteers. Keywords: Rheumatoid arthritis, Lashuna, In-silico analysis, Molecular docking
Publication date: 01/08/2026

https://www.ijbpas.com/pdf/2026/August/MS_IJBPAS_2026_10288.pdf

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https://doi.org/10.31032/IJBPAS/2026/15.8.10288