In silico identification of phytoconstituents from Capparis sepiaria as interleukin-1 inhibitors for rheumatoid arthritis: molecular docking, ADMET profiling, and molecular dynamics simulation.

Abstract

In this study computational methods were used to explore the anti-inflammatory properties of Capparis (C.) sepiaria extracts; focusing on their activity against pro-inflammatory cytokine, interleukin-1 (IL-1). Molecular docking was performed on 18 C. sepiaria phytoconstituents using AutoDock VinaXB. The study identified five compounds (CIDs 8122, 33934, 605626, 638072, 5363269) with high affinity for IL-1. Notably, CID 638072 demonstrated superior binding affinity compared to standard controls such as thalidomide. Pharmacokinetic and toxicity profiles were assessed using SwissADME and pkCSM which showed that all these compounds met acceptable criteria as promising anti-inflammatory agents. Molecular dynamics simulations with GROMACS (version 2019) confirmed the stability and interaction dynamics of these compounds, which support the docking results. The findings validate the traditional medicinal use of C. sepiaria for the treatment of inflammation, suggesting that CID 638072 holds significant potential for further development into a natural anti-inflammatory therapeutic. This research provides clues for the therapeutic applications of C. sepiaria, advancing the search for effective natural remedies for the treatment of inflammation. Further experimental validation is necessary to transition this study from computational predictions to clinical applications.