Selecting and Characterizing Tyrosinase Inhibitors from Atractylodis macrocephalae Rhizoma Based on Spectrum-Activity Relationship and Molecular Docking

Atractylodis macrocephalae Rhizoma (AMR) is a famous classical Chinese traditional medicine (CTM), which has been used as a tonic for many diseases for thousands of years. In ancient China, it was used as a supplementary food for beauty in the palace. In preliminary studies, the function of whitening skin and the significant inhibiting effect on tyrosinase (TYR) which is the reactive enzyme in the composition of melanin of AMR were discovered, and the relevant research was rarely reported. In this study, high-performance liquid chromatography (HPLC) along with partial least squares regression analysis (PLS) was applied to survey the coherence between the chemical constituents and the inhibiting activity of 11 batches of AMR on TYR activity. The results of PLS showed that the chromatographic peaks 11 (atractylenolide III) and 15 could be important effective ingredients of the inhibition TYR activity as ascertained by spectrum-activity relationships. Furthermore, TYR inhibitory activity of atractylenolide III was validated by in vitro test by β-arbutin served as a positive control drug. The results of the in vitro test and the molecular docking showed that atractylenolide III has high TYR inhibitory activity and could link to the residues in TYR catalytic pocket. Therefore, bioassay, molecular docking, and spectrum-activity relationships are appropriate for linking the quality of samples with pharmaceutical-related active ingredients. And our studying would lay a theoretical foundation for applying the water extracts of AMR in whitening cosmetics.


Introduction
Tyrosinase (TYR), also nominated as polyphenol oxidase, is a polyfunctional glycosylated copper-containing enzyme which exists in the organism of animal, plant, and microorganism widely [1][2][3]. In the presence of molecular oxygen, tyrosine is firstly catalyzed by TYR to oxidize to dopa, and then further oxidized to dopaquinone, which isomerized to form dopa pigment. Dopa pigment finally formed melanin with the participation of CO 2 and TRP-2, which cause various skin diseases such as hyperpigmentation, melasma, freckles, and age spots [4,5]. TYR plays a vital role because it is the critical enzyme and restriction enzyme in the course of melanin composition [6][7][8]. Pigment spots and melanoma markedly increased by increasing TYR activity and quantity [9]. Nowadays, TYR inhibitors have received broad attention due to their latent use as hypopigmented agents [10].
Atractylodis macrocephalae rhizoma (AMR), the dry rhizoma of Atractylodes macrocephala Koidz., is one of the Chinese herbal medicines compiled in Chinese Pharmacopoeia [11][12][13][14][15]. In ancient China, AMR was optioned to form the famous classic formula for whitening designated "Seven-White Ointment" and used as supplementary food for beauty in the palace [16]. It was reported that AMR mainly contained sesquiterpenoids and triterpenoid (including atractylenolideI, atractylenolide II, and atractylenolide III), polyacetylenes, coumarins and phenylpropanoids, flavonoids and flavonoid glycosides, polysaccharides, steroids, benzoquinones, and other constituents [17,18]. However, its effects of whitening skin and active ingredients were rarely reported. e study of the spectrum-activity relationship was applied to explore their relevances. e research of the spectrum-activity relationship can not only circumvent the shortcoming of segregation between chemical ingredients and pharmacodynamics but also sufficiently associate fingerprint with pharmacodynamics by the mathematical model [19,20]. e spectrum-activity relationship explores the relevance between the fingerprint and pharmacodynamics to offer a credible method for clarifying the material base of Chinese herbal medicine [21]. e fingerprints were established by HPLC, UPLC, GC, GC-MS, and LC-MS usually [19,[22][23][24]. "Pharmacodynamics" data is acquired by the biomodels usually [25]. e methods of data processing, mainly include principal component analysis (PCA), partial least squares (PLS) regression analysis, orthogonal partial least squares-discriminant analysis (OPLS-DA), canonical correlation analysis (CCA), and grey relational analysis (GRA) usually [26][27][28][29].
To clarify the components of the AMR that contribute to the inhibition activity of TYR [30,31], the fingerprints of 11 batches of AMR were established by HPLC; pharmacodynamic of TYR inhibition activity in vitro was evaluated by the biochemical enzymatic method. e effective compounds were selected by spectrum-activity relationship model which was established by correlated fingerprint peaks with pharmacodynamic data. Furthermore, active substances would be validated by in vitro test and molecular docking experiments.
is study could lay a theoretical basis for applying AMR as the treatment medicine for pigmented skin diseases and developing it as whitening cosmetics supplementary.

Extraction.
Herbal pieces of each sample (about 10 g) were weighed precisely and then placed in a round bottom flask, adding water and refluxing to extract. Products were dried under reduced pressure to obtain the water extract of AMR. en, the water extracts of AMR (about 30.00 mg) were weighed precisely and dissolved with 50% methanol (v/v).

HPLC Analysis.
Comix C18 reversed-phase chromatography column (250 × 4.6 mm, 5 μm). e mobile phase 0.1% phosphoric was a mixture of acid water (A)-acetonitrile (B); the elution system is designed and is listed in Table 2.
e flow rate was fixed at 0.6 mL/min. e column temperature was 30°C.
e UA wavelength was 210 nm. e injection volume was 30 μL.
e detection method was verified by precision test, repeatability test, and stability test.

Chemometric Analysis.
In this study, the common peaks information of fingerprints of 11 batches of AMR were imported into software SIMCA14.1 for HCA, PCA, and OPLS-DA.

TYR Inhibition Test In Vitro.
e extracts of AMR were dissolved with phosphate (pH 6.8) buffer, stored at 4°C, and then used for the assay of the enzyme.
In this study, L-tyrosine was used as a substrate to determine the inhibition of TYR activity. e reaction solutions were prepared according to Table 3, and the inhibition rate of AMR on TYR activity was determined. Firstly, the reaction solutions were put in a 37°C water bath for 10 min. Secondly, the TYR solution was added to T2 and T4 reaction solutions immediately. irdly, the reaction solutions reacted at 37°C water bath constant temperature for 10 min after mixed fully. Finally, the reaction solutions of the absorbance values were measured at 475 nm immediately. e inhibition rates (%) were obtained from the equation: the inhibition rate

Spectrum-Activity Relationship Analysis.
e software "Chinese traditional medicine chromatographic fingerprint similarity evaluation system 2012 A Edition" was used to adjust the retention times of each peak, and the peak area (PA) was processed by equalization. en, the quantitative data were obtained. e PLS regression equation was set up with the software SIMCA14.1; the peak area was taken as the independent variable (X), and TYR inhibition rate was set as the dependent variable (Y).

Inhibitory Effect of Atractylodes III on TYR and Molecular
Docking. To testify the inhibitory effect of Atractylenolide III on TYR, in vitro enzymatic activity tests were conducted by β-arbutin serving as a positive control drug. e AutoDock4.2 program was applied in docking simulations. e crystal structure of Agaricus bisporus (PDB ID: 2Y9X) was taken as the 3D structure of TYR [32]. We performed simulations of the docking of TYR to Atractylodes III. With the purpose of docking with AutoDock Vina, the grid size was designed to (x, y, z) � (16,12,14) and the grid center was designed to (x, y, z) � (−10.348, −28.279, −45.925). In each simulation procedure, progress with default parameters operates from AutoGrid and AutoDock. Lamarckian genetic algorithm (LGA) was adopted to ascertain the most appropriate ligand binding orientations.

Results and Discussion
3.1. Methodology Validation. Precision, repeatability, and stability were validated for the analytical method. In precision testing, precision of relative retention times (RRTs) and relative peak areas (RPAs) did not exceed 0.02% and 4% in RSD, respectively; the similarity was 1. Repeatability of RRTs and RPAs was less than 0.11% and 4% in RSD, and the similarity was greater than or equal to 0.998. e stability was estimated by testing one sample solution preserved at lab environmental temperature after 0, 6, 8, 12, and 18 h. e RSDs of RRTs and RPAs of the common peaks were less than 0.1% and 4%, respectively; the similarity was more than 0.999. ese results suggested that the AMR experimental system for fingerprint analysis is steady and dependable.

HPLC Fingerprint Establishment and Similarity Analysis.
e fingerprint of Atractylodes III reference substances is exhibited in Figure 1(a). e AMR sample showed favorable segregation among its peaks (Figure 1(b)). Under the perfect conditions, the HPLC fingerprints of the 11 different batches of AMR samples were generated (Figure 1(c)), and the similarities were calculated. e results of similarities are shown in Table 4, which showed that all of the similarity values of the 11 samples were greater than 0.8, indicating that all samples were similar in the kinds of chemical compositions. Sixteen common peaks were observed by comparing their retention time of the UV spectrum. Peak 11 was identified as Atractylodes III by reference substances.
ese results indicated that the contents of the chemical substances in AMR from different production areas were obviously different.

Chemometric Analysis
3.3.1. HCA. HCA was applied to identify AMR from different production areas based on different clusters and the similarity of fingerprints. e common peak area in 11 batches of AMR was used as an indicator, and the cluster analysis was performed by software SIMCA14.1. e results are shown in Figure 2. e samples of 11 batches of AMR were divided into 3 categories when the class distances ranged between 20 and 30, of which S4, S8, S9, S1, and S3 were grouped into category I and S7 was grouped into category II, while S2, S5, S10, S6, and S11 were grouped into category III.

PCA.
In this study, the PCA of 11 batches of AMR was calculated; in 16 principal components, the cumulative contribution of the variance of the first five principal components was 91.3%. e score matrix of the first two components would be used for analysis as the cumulative variance exceeded 65.9%. erefore, in the absence of some information, construct a two-dimensional plane of the principal component that the abscissa was a principal component and the ordinate was another principal component. en, the 11 samples were projected onto the 2D plane so that their natural gathering was observed (Figure 3(a)). It was founded that S4, S8, S9, S1, and S3 had obvious classifications, S7 could be divided into one type, and S2, S5, S10, S6, and S11 could be divided into another type. e result of PCA was consistent with the HCA result.
Each dot in the load diagram represented a chromatographic peak, which represents the contribution of each chromatographic peak to the comprehensive effect of the  Sichuan 181104 S10 Zhejiang 19062502 S11 Hubei 1904005 principal components. e weight value of the variables can reflect the correlation between the chemical composition and the sample to the greatest extent. e farther away from the origin of the load diagram, the greater the variable weight. e result is shown in Figure 3(b), which suggested that the chromatographic peaks 9, 11 (atractylenolide III), and 12 had a greater impact on the first principal component. However, the chromatographic peaks 4, 5, 6, 15, and 16 had a greater impact on the second principal component. It showed that the above chromatographic peaks might have a greater impact on the classification.

OPLS-DA.
e 11 samples were divided into two groups that S1, S3, S4, S8, and S9 were the first group and S2, S5, S6, S7, S10, and S11 were the second group. e common peak information of all samples was imported into SIMCA14.1 software for OPLS-DA. R 2 X and R 2 Y characterize the explanatory rate of the model to x and y matrices, individually, and Q 2 characterizes the predictive ability of the model. e results showed that the values of R 2 X, R 2 Y, and Q 2 were 0.939, 0.992, and 0.583, respectively, all of which were greater than 0.5, indicating that the model could distinguish the two groups of samples and had a better fitting  and predictive ability in the data processing. It could be used to distinguish AMR from different production areas (Figure 4(a)).
e profile of variables important for the projection (VIP) in the OPLS-DA model can reflect the contribution of each chromatographic peak to the sample. e VIP values of  20 10 0 S4 S8 S9 S1 S3 S7 S2 S5 S10 S6 S11 Journal of Analytical Methods in Chemistry the 16 chromatographic peaks reflected the influence power on every AMR sample. Based on the selection principle that the VIP value was more than 1.0 and the error bar was less than the origin (Figure 4(b)), the 4 important chromatographic peaks were selected out, which were arranged in order: peak 1 > peak 6 > peak 16 > peak 5. e analysis results of the load diagram are shown in Figure 4(c), which showed that the positions of the above 4 important chromatographic peaks were far away from the origin. It was suggested that the 4 chromatographic peaks impacted the classification of AMR significantly, and these components represented by 4 chromatographic peaks might be the main marker components of each sample.

Assessment of Inhibitory Activity of AMR on TYR In Vitro.
e inhibitory effects of AMR from different producing areas on TYR activity were determined by the biochemical enzyme method. e effects of samples on TYR activity are listed in Table 6. Each sample with 10 mg/mL concentration could inhibit TYR activity and pharmacological activity was remarkably different, among which the inhibition rate of S5 was the highest, whereas S6 was the lowest.

Spectrum-Effect Relationships Analysis.
In this article, PLS was applied to analyze the spectrum-activity relationship. e partial regression coefficient and VIP value are shown in Figures 5(a) and 5(b), which showed that chromatographic peaks 1, 2, 5, 6, 7, 9, 10, 11, 15, and 16 were correlated positively with the inhibition of TYR activity, but the chromatographic peaks 3, 4, 8, 12, 13, and 14 were negatively correlated with them. Among the chromatographic peaks positively correlated with the inhibition of TYR activity, the VIP values of chromatographic peaks 11 (Atractylodes III) and 15 were greater than 1, which indicated that these two components influenced the inhibition of TYR activity significantly.    Journal of Analytical Methods in Chemistry 7

Inhibitory Effect of Atractylodes III on TYR and Molecular
Docking. e inhibitory effect of Atractylodes III on TYR activity was determined by biochemical enzyme method in vitro with β-arbutin as a positive control. e results showed that the inhibition rates of Atractylodes III and β-arbutin on TYR activity were 63.68 ± 2.36% and 94.85 ± 0.35%, respectively, when the samples' concentration was 1 mg/mL. Molecular docking was used to study the binding mechanism of Atractylodes III interacting with TYR (Figures 6(a)-6(c)). e binding site of mushroom tyrosinase is composed of a narrow, shallow cavity with two copper ions (Cu 2+ ) each stabilised by three histidine residues (e.g., His 61) at the enzyme's active center. In this study, Atractylodes III is a small molecule compound located in the active center of the enzyme and interacts with the surrounding residues (His 244, Phe 264, Ala 286, His 263, Val 283, His259, His 85, Asn 260). Remarkably, Atractylodes III formed a stable hydrogen bond to Asn 260 with a bond length of 1.9Å.

Conclusions
In this study, a systematic method was established connecting the HPLC fingerprints with chemometric analysis to distinguish AMR samples from different origins, and the whitening effect of AMR was proved by the biochemical enzyme method. Spectrum-effect relationships indicated that the chromatographic peaks 1, 2, 5, 6, 9, 10, 11, 15, and 16 were positively correlated with AMR inhibition effect on TYR activity, among which peaks 11 (atractylenolide III) and 15 might be important active constituents. Meanwhile, atractylenolide III has high TYR inhibitory activity in vitro test, and the result of molecular docking showed that its mechanism might be related to the binding of amino acid residues in TYR catalytic capsule. erefore, these results proved that bioassay, molecular docking, and spectrumactivity relationships are appropriate for linking the quality of samples with pharmaceutical-related active ingredients.

Data Availability
e data used to support the fndings of this study are available from the corresponding author upon request.

Disclosure
Yong-Qin Liu and Chang-Yan Xu are regarded as the cofirst authors.