Computational study of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ binding sites identification on cytokines to predict dental metal allergy: An in silico study

Abstract

Context: Metal allergy is a general term to describe allergic diseases due to the release of metal ion reactions in the body which are mediated by T cells and involve inflammatory cytokines that can cause morbidity and mortality. Molecular docking is an analysis that can be used to assess the interaction of ligand bonds with target proteins that are used to predict metal allergies caused by metal ions that stimulate cytokines. Aims: To analyze the binding sites of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ ions on cytokines to predict dental metal allergy through a bioinformatics approach, in silico. Methods: Metal ion particles consisting of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ were predicted to bind tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukin (IL) IL-1b, IL-2, IL-4, IL-10, IL-13, IL-17, IL-23, and IL-33 act as target proteins were examined. Results: The blind docking simulation succeeded in identifying the comparison of the binding activity of metal ion particles on cytokines target proteins. The docking simulation results show that the metal ion with the most negative binding affinity value binds to the IL-17 protein. Conclusions: Metal ion particles consisting of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ have the most negative binding affinity values for binding to IL-17 protein, which can cause allergic reactions predicted by molecular docking, in silico.