Inhibitory effects of cupferron on the monophenolase and diphenolase activity of mushroom tyrosinase

Xie, Li; Chen, Qing Xi; Huang, Huang; Liu, Xiao Dan; Chen, Hong Tao; Zhang, Rong Qing

doi:10.1016/s1357-2725(03)00006-2

Cited by 89 publications

(78 citation statements)

References 22 publications

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“…apigenin so far, but its bad solubilization in the water-based assay medium might distort the tests' results [43,44]. To confirm our results, the whitening activities of apigenin and luteolin were assessed in vitro following the same protocol as the one used previously to evaluate the activity of the R. luteola extracts and resulting fractions.…”

Section: Final Purification and Identification Of Active Compoundssupporting

confidence: 65%

“…UPLC-HRMS also facilitated the identification of the two bioactive principles as luteolin and apigenin. If luteolin was already known as a skin-lightening agent [37], apigenin was only reported to be a weak tyrosinase inhibitor, an observation that might be biased by its low solubility in water-based medium [43,44]. Their whitening potencies were hence further confirmed by tyrosinase inhibitory assays that were performed on analytical standards in the same experimental conditions as the ones that were used to assess the activities of the R. luteola extracts and fractions: both luteolin and apigenin appear to be potent tyrosinase inhibitors.…”

Section: Discussionmentioning

confidence: 99%

“…Their whitening potencies were hence further confirmed by tyrosinase inhibitory assays that were performed on analytical standards in the same experimental conditions as the ones that were used to assess the activities of the R. luteola extracts and fractions: both luteolin and apigenin appear to be potent tyrosinase inhibitors. Flavonoids have previously been identified as competitive tyrosinase inhibitors thanks to their ability to chelate the copper from the enzyme's active site, leading to the enzyme's irreversible inactivation [1,44].…”

Section: Discussionmentioning

confidence: 99%

“…Apigenin, particularly promising for cancer prevention [41], also displays a variety of engaging activities and notably anti-inflammatory and anti-oxidant properties [39,42]. Only weak whitening activity was reported for apigenin so far, but its bad solubilization in the water-based assay medium might distort the tests' results [43,44]. To confirm our results, the whitening activities of apigenin and luteolin were assessed in vitro following the same protocol as the one used previously to evaluate the activity of the R. luteola extracts and resulting fractions.…”

Section: Final Purification and Identification Of Active Compoundsmentioning

confidence: 99%

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Whitening Agents from Reseda luteola L. and Their Chemical Characterization Using Combination of CPC, UPLC-HRMS and NMR

et al. 2017

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Skin whitening agents occupy an important part of the dermo-cosmetic market nowadays. They are used to treat various skin pigmentation disorders, or simply to obtain a lighter skin tone. The use of traditional skin bleachers (e.g., hydroquinone, corticoids) is now strictly regulated due to their side effects. When considering this and the growing consumers' interest for more natural ingredients, plant extracts can be seen as safe and natural alternatives. In this perspective, in vitro bioassays were undertaken to assess cosmetic potential of Reseda luteola, and particularly its promising whitening activities. A bioguided purification procedure employing centrifugal partition chromatography, Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-HRMS) and NMR was developed to isolate and identify the whitening agents (i.e., luteolin and apigenin) from aerial parts of R. luteola. UPLC-HRMS also enabled the characterization of acetylated luteolin-and apigenin-O-glycosides, which occurrence is reported for the first time in R. luteola.

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Section: Final Purification and Identification Of Active Compoundssupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Final Purification and Identification Of Active Compoundsmentioning

confidence: 99%

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Whitening Agents from Reseda luteola L. and Their Chemical Characterization Using Combination of CPC, UPLC-HRMS and NMR

et al. 2017

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“…Studies have shown that the absence of flavonoid in mushrooms may be of biological advantage in their various ecological niches. [31] Ginger and the mushroom, T. nudum, showed very high contents of total phenolics, followed by garlic, possibly making them better antioxidants than garlic and the other species of mushrooms. The low and varied concentrations of these phytochemicals among the tested mushrooms may be attributed to mycelia wet and wet weights.…”

Section: Discussionmentioning

confidence: 97%

Phytochemical and Antioxidant Analyses of Selected Edible Mushrooms, Ginger and Garlic from Ebonyi State, Nigeria

Udu-Ibiam¹,

Ogbu²,

Agah³

2014

IOSRJPBS

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Prediction of Tyrosinase Inhibition Activity Using Atom‐Based Bilinear Indices

et al. 2007

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A set of novel atom-based molecular fingerprints is proposed based on a bilinear map similar to that defined in linear algebra. These molecular descriptors (MDs) are proposed as a new means of molecular parametrization easily calculated from 2D molecular information. The nonstochastic and stochastic molecular indices match molecular structure provided by molecular topology by using the kth nonstochastic and stochastic graph-theoretical electronic-density matrices, M(k) and S(k), respectively. Thus, the kth nonstochastic and stochastic bilinear indices are calculated using M(k) and S(k) as matrix operators of bilinear transformations. Chemical information is coded by using different pair combinations of atomic weightings (mass, polarizability, vdW volume, and electronegativity). The results of QSAR studies of tyrosinase inhibitors using the new MDs and linear discriminant analysis (LDA) demonstrate the ability of the bilinear indices in testing biological properties. A database of 246 structurally diverse tyrosinase inhibitors was assembled. An inactive set of 412 drugs with other clinical uses was used; both active and inactive sets were processed by hierarchical and partitional cluster analyses to design training and predicting sets. Twelve LDA-based QSAR models were obtained, the first six using the nonstochastic total and local bilinear indices and the last six with the stochastic MDs. The discriminant models were applied; globally good classifications of 99.58 and 89.96 % were observed for the best nonstochastic and stochastic bilinear indices models in the training set along with high Matthews correlation coefficients (C) of 0.99 and 0.79, respectively, in the learning set. External prediction sets used to validate the models obtained were correctly classified, with accuracies of 100 and 87.78 %, respectively, yielding C values of 1.00 and 0.73. This subset contains 180 active and inactive compounds not considered to fit the models. A simulated virtual screen demonstrated this approach in searching tyrosinase inhibitors from compounds never considered in either training or predicting series. These fitted models permitted the selection of new cycloartane compounds isolated from herbal plants as new tyrosinase inhibitors. A good correspondence between theoretical and experimental inhibitory effects on tyrosinase was observed; compound CA6 (IC(50)=1.32 microM) showed higher activity than the reference compounds kojic acid (IC(50)=16.67 microM) and L-mimosine (IC(50)=3.68 microM).

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Inhibitory effects of cupferron on the monophenolase and diphenolase activity of mushroom tyrosinase

Cited by 89 publications

References 22 publications

Whitening Agents from Reseda luteola L. and Their Chemical Characterization Using Combination of CPC, UPLC-HRMS and NMR

Whitening Agents from Reseda luteola L. and Their Chemical Characterization Using Combination of CPC, UPLC-HRMS and NMR

Phytochemical and Antioxidant Analyses of Selected Edible Mushrooms, Ginger and Garlic from Ebonyi State, Nigeria

Prediction of Tyrosinase Inhibition Activity Using Atom‐Based Bilinear Indices

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