Flavones as tyrosinase inhibitors: kinetic studies in vitro and in silico


Arroo R. R. J. , SARI S. , Barut B., ÖZEL A., Ruparelia K. C. , ŞÖHRETOĞLU D.

PHYTOCHEMICAL ANALYSIS, cilt.31, ss.314-321, 2020 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 31 Konu: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1002/pca.2897
  • Dergi Adı: PHYTOCHEMICAL ANALYSIS
  • Sayfa Sayıları: ss.314-321

Özet

Introduction Tyrosinase is a multifunctional copper-containing oxidase enzyme that catalyses the first steps in the formation of melanin pigments. Identification of tyrosinase inhibitors is of value for applications in cosmetics, medicine and agriculture. Objective To develop an analytical method that allows identification of drug-like natural products that can be further developed as tyrosinase inhibitors. Results of in vitro and in silico studies will be compared in order to gain a deeper insight into the mechanism of action of enzyme inhibition. Method Using an in vitro assay we tested tyrosinase inhibitor effects of five structurally related flavones, i.e. luteolin (1), eupafolin (2), genkwanin (3), nobiletin (4), and chrysosplenetin (5). The strongest inhibitors were further investigated in silico, using enzyme docking simulations. Results All compounds tested showed modest tyrosinase inhibitory effect compared to the positive control, kojic acid. The polymethoxy flavones 4 and 5 exhibited the strongest tyrosinase inhibitory effect with the half maximal inhibitory concentration (IC50) values of 131.92 +/- 1.75 mu M and 99.87 +/- 2.38 mu M respectively. According to kinetic analysis 2, 4 and 5 were competitive inhibitors, whereas 1 and 3 were non-competitive inhibitors of tyrosinase. Docking studies indicated that methoxy groups on 4 and 5 caused steric hindrance which prevented alternative binding modes in the tyrosinase; the methoxy groups on the B-ring of these flavones faced the catalytic site in the enzyme. Conclusions The docking simulations nicely complemented the in vitro kinetic studies, opening the way for the development of predictive models for use in drug design.