In silico assessment of cannabinoids and related compounds as multi-target modulators of IL-2, TNF-α, HSP70/HSP90, EGF signaling, and MMP-2/MMP-9 in ovarian cancer

Abstract

Ovarian cancer is one of the most lethal gynecological diseases and remains a formidable challenge because of its high mortality and intrinsic resistance to conventional treatment approaches. Recent advances in molecular biology and drug discovery have identified several proteins, such as interleukin-2 (IL-2), tumor necrosis factor-alpha (TNF-α), heat shock proteins (HSPs), epidermal growth factor (EGF), and matrix metalloproteinases (MMPs), as potential therapeutic targets. Tetrahydrocannabinol (THC), cannabinol, elasterol, and 2-methylenecholestan-3-ol are among the substances that have shown promise in modulating these targets. This study aims to evaluate, in silico, the potential of 2-methylenecholestan-3-ol, elastrol, THC, and cannabinol to modulate IL-2, TNF-α, HSPs, EGF signaling, and MMPs in ovarian cancer. Bioinformatics databases were used to identify potential therapeutic agents for ovarian cancer. Molecular docking, protein-ligand complex analysis, SwissADME, admetSAR, and toxicity prediction were performed as key components of the workflow. Overall, the in silico analyses suggest that these compounds may interact with key proteins implicated in ovarian cancer progression. Particularly, elasterol and 2-methylenecholestan-3-ol showed good therapeutic properties against OC targeting HSP70 and HSP90, whereas THC and cannabinol show adequate interactions with MMPs and TNF-α. These findings suggest potential therapeutic relevance, opening up a promising avenue for improving ovarian cancer treatment.

Keywords

Ovarian cancer / Phytocompounds / HSP-70 / MMPs / Molecular docking / admetSAR

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

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