Spectrum-effect relationship study to reveal the pharmacodynamic substances in Flos Puerariae-Semen Hoveniae medicine pair for the treatment of alcohol-induced liver damage

Zhang, Haotian; Wei, Ziyun; Tong, Yichen; Song, Xiaofeng; Li, Siyue; Sun, Yi; Lei, Chun; Han, Fei; Yu, Jia

doi:10.1016/j.jep.2023.116628

Cited by 8 publications

(5 citation statements)

References 31 publications

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“…In the comprehensive analysis, 10 common peaks satisfied the following criteria: negative correlation and a VIP value greater than one in the PLS-DA, negative correlation and a correlation coefficient greater than 0.4 in the BCA, and a correlation degree greater than 0.6 in the GCA. Based on this, peaks 6, 9 (glycitin), 11 (genistin), 12 (4 ′ -methoxypuerarin), 25,34,35,36,53, and 59 were preliminarily identified as candidates with PTP1B inhibitory activity.…”

Section: Integration Of Analytical Resultsmentioning

confidence: 99%

“…; That is, with an increase in peak area, the inhibitory activity of the extracts on PTP1B increased. The absolute values of correlation coefficients of peaks 5 (puerarin 6 ′′ -O-xyloside), 6, 8, 9 (glycitin), 11 (genistin), 12 (4 ′ -methoxypuerarin), 23,25,34,35,36,45,53,54,55,58, and 59 were all greater than 0.4, indicating a good correlation. As shown in Table S3, peaks 5 and 6 showed a significant negative correlation (p ≤ 0.05).…”

Section: Bivariate Correlation Analysis (Bca)mentioning

confidence: 94%

“…Spectrum–effect relationship analysis uses powerful mathematical and statistical methods, such as grey relational analysis (GRA), correlation analysis (CA), and partial least squares discrimination analysis (PLS-DA), to study the relationship between fingerprint data and pharmacodynamic indicators, to clarify the material basis of the pharmacological action of TCM, and to analyze the bioactive substances in fingerprints [ 35 ]. However, there is a lack of reports regarding the spectrum–effect relationship analysis between P. lobata and its inhibition of PTP1B.…”

Section: Introductionmentioning

confidence: 99%

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Protein Tyrosine Phosphatase 1B Inhibitors of Pueraria lobata Based on the Spectrum–Effect Relationship by Q-Marker Selection

Zhang,

Liu,

et al. 2024

Molecules

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Pueraria lobata (P. lobata), a traditional anti-diabetic medicine mainly composed of flavonoids and isoflavones, has a long history in diabetes treatment in China. However, the anti-diabetic active component is still unclear. Recently, protein tyrosine phosphatase 1B (PTP1B) has been a hot therapeutic target by negatively regulating insulin signaling pathways. In this study, the spectrum–effect relationship analysis method was first used to identify the active components of P. lobata that inhibit PTP1B. The fingerprints of 12 batches of samples were established using high-performance liquid chromatography (HPLC), and sixty common peaks were identified. Meanwhile, twelve components were identified by a comparison with the standards. The inhibition of PTP1B activity was studied in vitro by using the p-nitrophenol method, and the partial least squares discriminant analysis, grey relational analysis, bivariate correlation analysis, and cluster analysis were used to analyze the bioactive compounds in P. lobata. Peaks 6, 9 (glycitin), 11 (genistin), 12 (4′-methoxypuerarin), 25, 34, 35, 36, 53, and 59 were considered as potentially active substances that inhibit PTP1B. The in vitro PTP1B inhibitory activity was confirmed by glycitin, genistin, and 4′-methoxypuerarin. The IC50s of the three compounds were 10.56 ± 0.42 μg/mL, 16.46 ± 0.29 μg/mL, and 9.336 ± 0.56 μg/mL, respectively, indicating the obvious PTP1B inhibitory activity. In brief, we established an effective method to identify PTP1B enzyme inhibitors in P. lobata, which is helpful in clarifying the material basis of P. lobata on diabetes. Additionally, it is evident that the spectrum–effect relationship method serves as an efficient approach for identifying active compounds, and this study can also serve as a reference for screening bioactive constituents in traditional Chinese medicine.

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Section: Integration Of Analytical Resultsmentioning

confidence: 99%

Section: Bivariate Correlation Analysis (Bca)mentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

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Protein Tyrosine Phosphatase 1B Inhibitors of Pueraria lobata Based on the Spectrum–Effect Relationship by Q-Marker Selection

Zhang,

Liu,

et al. 2024

Molecules

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“…Currently, the statistical analysis methods used in the spectrum-effect correlation method include correlation analysis, regression analysis, principal component analysis, gray correlation analysis, and artificial neural network analysis. Each statistical method has its advantages and disadvantages, so the most reasonable and effective prediction can be obtained by combining multiple results in practical application [ 30 , 31 , 32 ]. In order to screen the active ingredients, we used the spectrum-effect relationship method, combining 11 common peaks and pharmacological parameters of PC extract using Pearson’s correlation analysis, GRA and OPLSR.…”

Section: Discussionmentioning

confidence: 99%

Screening of Key Components for Melanogenesis Inhibition of Polygonum cuspidatum Extract Based on the Spectrum–Effect Relationship and Molecular Docking

Du,

Ye,

Chen

et al. 2024

Molecules

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Polygonum cuspidatum (PC) extract has been listed in the “Catalog of Used Cosmetic Ingredients (2021 Edition)”, which can inhibit melanogenesis, thus exerting a whitening effect, and has been widely used in cosmetics. However, there are currently no quality standards for PC extract used in cosmetics, and the bioactive components associated with anti-melanogenesis remain unclear. In view of this, the present study was the first to investigate the spectrum-effect relationship between fingerprints of PC extract and melanogenesis inhibition. Ten batches of PC extract fingerprints were established by HPLC. Pearson’s correlation analysis, gray correlation analysis (GRA) and orthogonal partial least squares regression analysis (OPLSR) were used to screen out resveratrol, emodin and physcion as the main whitening active ingredients using the inhibition of tyrosinase in B16F10 cells as the pharmacological index. Then, the melanogenesis inhibitory effects of the above three components were verified by tyrosinase inhibition and a melanin content assay in B16F10 cells. The interaction between small molecules and proteins was investigated by the molecular docking method, and it was confirmed by quantitative real-time PCR (qRT-PCR) that resveratrol, emodin and physcion significantly down-regulated the transcript levels of melanogenesis-related factors. In conclusion, this study established a general model combining HPLC fingerprinting and melanogenesis inhibition and also analyzed the spectrum–effect relationship of PC extract, which provided theoretical support for the quality control of PC extract in whitening cosmetics.

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“…By combining them with pharmacological indicators, a rational spectrumeffect model and analysis method can be established, which can systematically reveal the relationship between the components and the pharmacological effects, further elucidating pharmacologically active components and composition compatibility. Based on the establishment of the spectrum-effect correlation between pharmacodynamic indexes (the cell viability, ALT, AST activity, and TNF-α, IL-1β production) and HPLC chromatograms, Zhang H et al [17] revealed that daidzin, 6 ′′ -O-xylosylglycitin, 6 ′′ -O-xylosyl-tectorid in a Flos Puerariae-Semen Hoveniae medicine pair made a great contribution to treating alcoholinduced liver damage by modulating the PI3K/AKT/mTOR signaling pathways. Hanting Yang and Qian Li [18] found that isoimperatorin and byakangelicol exerted antioxidant activity in Angelica dahurica by establishing spectrum-effect relationships between antioxidant indexes and GC-MS chromatograms.…”

Section: Introductionmentioning

confidence: 99%

Quality Evaluation and Identification of Phyllanthi fructus (Yuganzi) Based on the Spectrum-Effect Relationship

Zhou,

Wu,

Liu

et al. 2024

Separations

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To establish a quality evaluation and identification method for Phyllanthi fructus (Yuganzi), the spectrum-effect relationship was explored. A high-performance liquid chromatography (HPLC) fingerprint was established using ultraviolet spectrophotometry, and the in vitro antioxidant activity was determined using a total antioxidant capacity assay kit. Similarity analysis, hierarchical cluster analysis (HCA), and partial least squares regression (PLSR) were performed to establish the spectrum-effect relationships. Thirteen batches of Yuganzi were collected for testing. The results revealed that the optimal chromatographic conditions for the HPLC fingerprint were as follows: the mobile phase consisted of 0.1% phosphoric acid solution (A) and acetonitrile (B), the detection wavelength was 214 nm, the column temperature was 30 °C, and the flow rate was 0.8 mL/min. Among the batches of samples, the similarity values of 10 samples (S1–S10) from Yunnan were larger than 0.995; the similarity values of 3 samples (S11–S13) from India, Gaoligong Mountain, and Fujian were less than or equal to 0.986. Furthermore, nineteen characteristic peaks of Yuganzi were calibrated using fingerprint evaluation software. The study on the spectrum-effect relationship further revealed that compounds corresponding to peaks 5 and 8 were potentially key ingredients for the quality evaluation and identification of Yuganzi, closely related to the stable antioxidant activities of Yuganzi. The spectrum-effect relationship is an agile and efficient approach that can ensure the intra-assay stability of Yuganzi from same region and identify Yuganzi from different regions. Compounds with antioxidant activity can be identified as quality markers for Yuganzi.

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Spectrum-effect relationship study to reveal the pharmacodynamic substances in Flos Puerariae-Semen Hoveniae medicine pair for the treatment of alcohol-induced liver damage

Cited by 8 publications

References 31 publications

Protein Tyrosine Phosphatase 1B Inhibitors of Pueraria lobata Based on the Spectrum–Effect Relationship by Q-Marker Selection

Protein Tyrosine Phosphatase 1B Inhibitors of Pueraria lobata Based on the Spectrum–Effect Relationship by Q-Marker Selection

Screening of Key Components for Melanogenesis Inhibition of Polygonum cuspidatum Extract Based on the Spectrum–Effect Relationship and Molecular Docking

Quality Evaluation and Identification of Phyllanthi fructus (Yuganzi) Based on the Spectrum-Effect Relationship

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