The Discovery of Tyrosinase Enzyme Inhibitors Activity from Polyphenolic Compounds in Red Grape Seeds through In Silico Study
Mentari Luthfika Dewi, Taufik Muhammad Fakih, Resty Imfyani Sofyan
J. Pure App. Chem. Res. Vol 10, No 2 (2021), pp.
Submitted: July 09, 2020     Accepted: July 20, 2021     Published: July 20, 2021


Tyrosinases are essential metal-containing enzymes in the biosynthesis of melanin, therefore responsible for pigmentation of the skin. The upregulation of tyrosinase enzyme activities leads to hyperpigmentation that will become a health problems and interfere psychosocially. Inhibition of tyrosinase enzyme activity, both competitive and non-competitive become widely developed for most anti hyperpigmentation agent. Natural antioxidants are one of the potential compounds for this purpose. Red grape seeds contain high levels of antioxidant compounds, such as procyanidin, prodelphinidin, and propelargonidin. In this research in silico studies, including molecular docking, molecular dynamics simulations, and toxicity predictions, were used to assess the activity of the three molecules of polyphenolic compounds on macromolecules of the tyrosinase enzyme. Molecular docking studies show that the compound propelargonidin has the highest affinity against the macromolecule of the tyrosinase enzyme, with a binding free energy value of −32.87 kJ/mol. These results were confirmed in molecular dynamics simulations that show strong interactions at the macromolecular active site of the tyrosinase enzyme. Toxicity prediction results show that the three polyphenolic compound molecules were classified in the High-Class Category, which shows that safety is not guaranteed, but is likely, not carcinogenic and nongenotoxic. Therefore, the compound propelargonidin is predicted to be able to interact strongly with the tyrosinase enzyme. The results in this research are useful for further study in the development of tyrosinase enzyme inhibitors.

Keywords : tyrosinase enzyme, red grape seeds, polyphenolic compounds, inhibitory pattern, in silico study


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