Virtual Screening and Molecular Dynamics of Cytokine-Drug Complexes for Atherosclerosis Therapy

Area of Science:

• Biomedical Science
• Pharmacology
• Computational Biology

Background:

• Cardiovascular disease, primarily atherosclerosis, is a leading cause of mortality globally.
• Atherosclerosis involves chronic inflammation, lipid accumulation, and immune cell infiltration in arteries.
• Key pro-atherogenic cytokines include Tumor Necrosis Factor-alpha (TNF-α), Interferon-gamma (IFN-γ), and Interleukin-1 beta (IL-1β).

Purpose of the Study:

• To identify novel multitarget inhibitors for TNF-α, IFN-γ, and IL-1β using in silico drug repositioning.
• To explore potential therapeutic strategies for atherosclerosis beyond current treatments.
• To investigate the efficacy of both FDA-approved drugs and nutraceuticals.

Main Methods:

• Virtual screening of 2750 FDA-approved drugs against target cytokines.
• Molecular dynamics simulations to assess the stability of cytokine-ligand complexes.
• Evaluation of nutraceutical compounds, including specific fatty acids, for target interactions.

Main Results:

• Identification of potential multitarget inhibitors through computational screening.
• Molecular dynamics simulations confirmed stable interactions between selected compounds and cytokines.
• Fatty acids (oleic, linoleic, eicosapentaenoic acid) demonstrated strong, stable binding to key cytokine targets.

Conclusions:

• In silico drug repositioning and molecular dynamics offer valuable insights for identifying atherosclerosis therapeutics.
• Nutraceuticals, particularly specific fatty acids, represent promising, stable inhibitors of pro-atherogenic cytokines.
• These findings suggest novel, cost-effective therapeutic avenues for managing atherosclerosis.