<i>In Silico</i> Identification of Natural Product-Based Inhibitors Targeting IL-1β/IL-1R Protein–Protein Interface

Abstract

IL-1β mediates inflammation and regulates immune responses, cell proliferation, and differentiation. Dysregulation of IL-1β is linked to inflammatory and autoimmune diseases. Elevated IL-1β levels are found in patients with severe COVID-19, indicating its excessive production may worsen the disease. Also, dry eye disease patients show high IL-1β levels in tears and conjunctival epithelium. Therefore, IL-1β signaling is a potential therapeutic targeting for COVID-19 and aforementioned diseases. No small-molecule IL-1β inhibitor is clinically approved despite efforts. Developing such inhibitors is highly desirable. Herein, a docking-based strategy was used to screen the TCM (Traditional Chinese Medicine) database to identify possible IL-1β inhibitors with desirable pharmacological characteristics by targeting the IL-1β/IL-1R interface. Primarily, the docking-based screening was performed by selecting the crucial residues of IL-1β interface to retrieve the potential compounds. Afterwards, the compounds were shortlisted on the basis of binding scores and significant interactions with the crucial residues of IL-1β. Further, to gain insights into the dynamic behavior of the protein–ligand interactions, MD simulations were performed. The analysis suggests that four selected compounds were stabilized in an IL-1β pocket, possibly blocking the formation of an IL-1β/IL-1R complex. This indicates their potential to interfere with the immune response, making them potential therapeutic agents to investigate further.

Keywords

• IL-1β
• virtual screening
• molecular docking
• MD simulation
• natural products