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. 2022 Dec;37(1):421-430.
doi: 10.1080/14756366.2021.2014832.

Flavonoids as tyrosinase inhibitors in in silico and in vitro models: basic framework of SAR using a statistical modelling approach

Affiliations

Flavonoids as tyrosinase inhibitors in in silico and in vitro models: basic framework of SAR using a statistical modelling approach

Katarzyna Jakimiuk et al. J Enzyme Inhib Med Chem. 2022 Dec.

Erratum in

  • Correction.
    [No authors listed] [No authors listed] J Enzyme Inhib Med Chem. 2022 Dec;37(1):514. doi: 10.1080/14756366.2022.2024999. J Enzyme Inhib Med Chem. 2022. PMID: 34986713 Free PMC article. No abstract available.

Abstract

Flavonoids are widely distributed in plants and constitute the most common polyphenolic phytoconstituents in the human diet. In this study, the in vitro inhibitory activity of 44 different flavonoids (1-44) against mushroom tyrosinase was studied, and an in silico study and type of inhibition for the most active compounds were evaluated too. Tyrosinase inhibitors block melanogenesis and take part in melanin production or distribution leading to pigmentation diseases. The in vitro study showed that quercetin was a competitive inhibitor (IC50=44.38 ± 0.13 µM) and achieved higher antityrosinase activity than the control inhibitor kojic acid. The in silico results highlight the importance of the flavonoid core with a hydroxyl at C7 as a strong contributor of interference with tyrosinase activity. According to the developed statistical model, the activity of molecules depends on hydroxylation at C3 and methylation at C8, C7, and C3 in the benzo-γ-pyrane ring of the flavonoids.

Keywords: Flavonoid; molecular docking; statistical analysis; structure-activity relationship; tyrosinase.

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Conflict of interest statement

No potential conflict of interest was reported by the authors. CT Supuran is Editor-in-Chief of Journal of Enzyme Inhibition and Medicinal Chemistry and he was not involved in the assessment, peer review or decision making process of this paper. The authors have no relevant affiliations of financial involvement with any organisation or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Figures

Figure 1.
Figure 1.
Molecular structures of the tested compounds.
Figure 2.
Figure 2.
Lineweaver–Burk plots for inhibition of tyrosinase in the presence of compounds: 4 (A), 17 (B), 26 (C), 32 (D), 35 (E), and 41 (F). The concentrations of the compounds were 0.00, 25, and 50 µM. The substrate L-DOPA concentrations were 0.25, 0.50, 1, and 2 mM.
Figure 3.
Figure 3.
Dixon plots for inhibition of tyrosinase in the presence of compounds: 4 (A), 17 (B), 26 (C), 32 (D), 35 (E), and 41 (F). The concentrations of the compounds were 0.00, 25, and 50 µM. The substrate L-DOPA concentrations were 0.25, 0.50, 1, and 2 mM.
Figure 4.
Figure 4.
Predicted binding mode of compounds 4 (A), 17 (B), 26 (C), 32 (D), 35 (E), and 41 (F) in the tyrosinase active site. Compounds are represented as colour stick balls, interacting tyrosinase residues as grey sticks, Cu2+ as orange spheres, their histidine ligands as wireframes, and binding interactions as colour dashed lines. The distances between Cu2+ and interacting atoms are shown in Å.
Figure 5.
Figure 5.
Binding interactions of compounds 4 (A), 17 (B), 26 (C), 32 (D), 35 (E), and 41 (F) with the tyrosinase active site residues. Binding interactions are shown as coloured lines, and compound moieties exposed to solvent are highlighted with grey shades.

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