Discovery of quality control markers from traditional Chinese medicines by fingerprint-efficacy modeling: Current status and future perspectives

Research on the hemostasis and coagulation effects of Callicarpa nudiflora based on the spectrum-effect relationship

Callicarpa nudiflora (C. nudiflora) is widely used in the treatment of bleeding related diseases. However, its main material basis has not been fully defined which limits the in-depth study of screening out the material basis of hemostasis and coagulation from C. nudiflor. In this study, the method of spectrum-effect relationship was used to quickly screen the material basis of hemostasis and coagulation. The five compounds related to hemostasis and coagulation were screened as Alyssonoside (P24), Luteolin (P25), Quercetin (P26), Apigenin (P28), Isorhamnetin (P29). And the contribution of these five peaks to hemostasis and coagulation efficacy was P24 > P25 > P28 > P26 > P29.

Combination ATR-FTIR with Multiple Classification Algorithms for Authentication of the Four Medicinal Plants from Curcuma L. in Rhizomes and Tuberous Roots

Curcumae Longae Rhizoma (CLRh), Curcumae Radix (CRa), and Curcumae Rhizoma (CRh), derived from the different medicinal parts of the Curcuma species, are blood-activating analgesics commonly used for promoting blood circulation and relieving pain. Due to their certain similarities in chemical composition and pharmacological effects, these three herbs exhibit a high risk associated with mixing and indiscriminate use. The diverse methods used for distinguishing the medicinal origins are complex, time-consuming, and limited to intraspecific differentiation, which are not suitable for rapid and systematic identification. We developed a rapid analysis method for identification of affinis and different medicinal materials using attenuated total reflection-Fourier-transform infrared spectroscopy (ATR-FTIR) combined with machine learning algorithms. The original spectroscopic data were pretreated using derivatives, standard normal variate (SNV), multiplicative scatter correction (MSC), and smoothing (S) methods. Among them, 1D + MSC + 13S emerged as the best pretreatment method. Then, t-distributed stochastic neighbor embedding (t-SNE) was applied to visualize the results, and seven kinds of classification models were constructed. The results showed that support vector machine (SVM) modeling was superior to other models and the accuracy of validation and prediction was preferable, with a modeling time of 127.76 s. The established method could be employed to rapidly and effectively distinguish the different origins and parts of Curcuma species and thus provides a technique for rapid quality evaluation of affinis species.

Comprehensive Investigation of Homology and Heterogeneity Between Aurantii Fructus and Aurantii Fructus Immaturus Using Chemometrics Combined with Network Pharmacology

Aurantii Fructus (AF) and Aurantii Fructus Immaturus (AFI) are distinct herbs outlined by the Chinese Pharmacopoeia. They are sourced from the same plant but harvested at different times, resulting in differences in efficacy. It is important to avoid mixing them clinically and to distinguish between the two. Furthermore, dissimilar cultivation conditions may cause variability in the quality of herbs, so it is vital to differentiate drugs from dissimilar origins. In this study, two plants, AF and AFI from different provinces, were comparatively analyzed based on High Performance Liquid Chromatography (HPLC) fingerprints and classified using chemometric methods. The results indicate that the two medicines can be clearly distinguished. Also, AF and AFI grown in different locations can be distinguished. Ten chemical markers were screened, and their variations were determined, including eriocitrin, narirutin, naringin, meranzin hydrate, naringenin, hesperidin, nobiletin, tangeretin, neohesperidin, and poncirin. Subsequent network pharmacology correlated the screened chemical components with the biological network of the organism. The material basis of the difference in efficacy of the two homologous herbs was explored from the perspective of changes in chemical composition. This study provides a reference for formulating quality evaluation standards for AF and AFI and lays a foundation for the efficacy-related quality research of the two.

Comparative Study on Morphological Features and Chemical Components of Wild and Cultivated Angelica sinensis Based on Bionic Technologies and Chemometrics

As a traditional Chinese medicine, Angelica sinensis is primarily sourced from cultivated plants due to the significant decline in wild resources. This shift raises concerns about potential differences in efficacy resulting from variations in morphological features and chemical composition between wild (WA) and cultivated (CA) A. sinensis. In this study, a suite of advanced analytical techniques including electronic nose, electronic tongue, and electronic eye, alongside headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and high-performance liquid chromatography, was applied to compare the morphological features and chemical components of WA and CA. Furthermore, principal component analysis and partial least-squares discriminant were employed for data analysis. The morphological features and chemical components of WA and CA were compared and analyzed. The results showed that three bionic technologies can distinguish WA from CA well and that fusion signals can distinguish better. There were differences between WA and CA in odor, taste, color, and content of the indicator components. There were correlations between the morphological features and the content of indicator components.

AI-driven determination of active compounds and investigation of multi-pharmacological effects of Chrysanthemi Flos

BACKGROUND

Chrysanthemi Flos as a medicine food homology species is widely used in the prevention and treatment of diseases, whereas comprehensive research of its active compounds related to multi-pharmacological effects remains limited. This study aimed to systematically explore the active compounds through artificial intelligence-based target prediction and activity evaluation.

METHODS

The information on compounds in Chrysanthemi Flos was obtained from six cultivars containing Gongju, Chuju, Huaiju, Boju, Hangbaiju, and Fubaiju, using UPLC-Q-TOF/MS. The main differential metabolites in six cultivars were also screened through the PLS-DA model. Then the potential targets of differential compounds were predicted via the DrugBAN model. Enrichment and topological analysis of compound-target networks were performed to identify key pharmaceutical compounds. Subsequently, the pharmacological effects of predictively active compounds were confirmed in vitro. Based on the active compounds, the pharmacological activities of Chrysanthemi Flos from the six origins were also investigated and compared for the further evaluation of medicinal quality.

RESULTS

A total of 155 secondary metabolites were obtained from Chrysanthemi Flos. Among them, 26 differential components were screened, and 9 key pharmacological compounds with 1141 targets were identified. Enrichment analysis indicated the main pharmacological effects of Chrysanthemi Flos related to inflammation, oxidative stress, and lipid metabolism. In addition, 9 key pharmaceutical compounds were evaluated in vitro experiments, indicating the significant therapeutic effect in regulating inflammation, oxidative stress, and lipid metabolism.

CONCLUSION

This study successfully identified 9 key pharmaceutical compounds in Chrysanthemi Flos and predicted the pharmacodynamic advantages of six origins. The findings would provide improved guidance for the discovery of active constituents and the assessment of pharmacodynamic advantages of different geographical origins.

Quantitative analysis of the quality constituents of Lonicera japonica Thunberg based on Raman spectroscopy

Quantitative analysis of the quality constituents of Lonicera japonica (Jinyinhua [JYH]) using a feasible method provides important information on its evaluation and applications. Limitations of sample pretreatment, experimental site, and analysis time should be considered when identifying new methods. In response to these considerations, Raman spectroscopy combined with deep learning was used to establish a quantitative analysis model to determine the quality of JYH. Chlorogenic acid and total flavonoids were identified as analysis targets via network pharmacology. High performance liquid chromatograph and ultraviolet spectroscopy were used to construct standard curves for quantitative analysis. Raman spectra of JYH extracts (1200) were collected. Subsequently, models were built using partial least squares regression, Support Vector Machine, Back Propagation Neural Network, and One-dimensional Convolutional Neural Network (1D-CNN). Among these, the 1D-CNN model showed superior prediction capability and had higher accuracy (R2 = 0.971), and lower root mean square error, indicating its suitability for rapid quantitative analysis.

Strategies for the quality control of Chrysanthemi Flos: Rapid quantification and end-to-end fingerprint conversion based on FT-NIR spectroscopy

INTRODUCTION

Chrysanthemi Flos (CF) is widely used as a natural medicine or tea. Due to its diverse cultivation regions, CF exhibits varying quality. Therefore, the quality and swiftness in evaluation holds paramount significance for CF.

OBJECTIVE

The aim of the study was to construct a comprehensive evaluation strategy for assessing CF quality using HPLC, near-infrared (NIR) spectroscopy, and chemometrics, which included the rapid quantification analyses of chemical components and the Fourier transform (FT)-NIR to HPLC conversion of fingerprints.

MATERIALS AND METHODS

A total of 145 CF samples were utilised for data collection via NIR spectroscopy and HPLC. The partial least squares regression (PLSR) models were optimised using various spectral preprocessing and variable selection methods to predict the chemical composition content in CF. Both direct standardisation (DS) and PLSR algorithms were employed to establish the fingerprint conversion model from the FT-NIR spectrum to HPLC, and the model's performance was assessed through similarity and cluster analysis.

RESULTS

The optimised PLSR quantitative models can effectively predict the content of eight chemical components in CF. Both DS and PLSR algorithms achieve the calibration conversion of CF fingerprints from FT-NIR to HPLC, and the predicted and measured HPLC fingerprints are highly similar. Notably, the best model relies on CF powder FT-NIR spectra and DS algorithm [root mean square error of prediction (RMSEP) = 2.7590, R2 = 0.8558]. A high average similarity (0.9184) prevails between predicted and measured fingerprints of test set samples, and the results of the clustering analysis exhibit a high level of consistency.

CONCLUSION

This comprehensive strategy provides a novel and dependable approach for the rapid quality evaluation of CF.

Separation, identification, and fingerprinting of antioxidant components in persimmon (Diospyros kaki) leaves by offline two-dimensional liquid chromatography with electrochemical detection and tandem mass spectrometry

In this work, the antioxidant components in persimmon (Diospyros kaki) leaves were separated by offline two-dimensional liquid chromatography-electrochemical detection (LC×LC-ECD) and identified by LC-tandem mass spectrometry (LC-MS/MS). A total of 33 antioxidants, mainly proanthocyanidins, and glycosides of kaempferol and quercetin, were identified. The antioxidant assays demonstrated that the fractions collected from the first-dimension LC (1D-LC) possessed considerable radical scavenging capabilities, with correlation coefficients of peak area versus radical scavenging capability of 1,1-diphenyl-2-picrylhydrazyl and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) being 0.9335 and 0.9116, respectively. The fingerprinting showed that 37 peaks were present in all samples. The major antioxidant components of persimmon leaves were the glycosides of kaempferol and quercetin. Finally, fourteen antioxidants were quantitatively assessed. Offline LC×LC provided high peak capacity and separation; ECD enabled specific screening and detection of antioxidant components; and MS/MS provided excellent identification capability. In this study, the combination of the three approaches was utilized to screen for antioxidant components in persimmon leaves, with satisfactory findings. In conclusion, this technique is an effective means for rapid analysis of antioxidant components and quality control of medicinal plants, achieving rapid separation of congeners and facilitating more accurate qualitative and quantitative analyses.

An innovative processing driven efficient transformation of rare ginsenosides enhances anti-platelet aggregation potency of notoginseng by integrated analyses of processing-(chemical) profiling-pharmacodynamics

ETHNOPHARMACOLOGICAL RELEVANCE

Panax notoginseng (Burk.) F. H. Chen, a valuable Chinese herb medicine, shows a characteristic bi-directional regulation of hemostasis and activating blood circulation with ginsenosides as the predominant bioactive compounds and is a typical representative of "processing triggered heteropotency".

AIM OF THE STUDY

Processing triggered heteropotency, one of the unique theories and practices in traditional Chinese medicine, refers to that the processing will lead to change in physical and chemical properties, and eventually disparate efficacy of the crude drugs, yet the optimum process and underlying mechanism remains unclear. In this study, using Panax notoginseng (PN) as a representative sample, a processing-(chemical) profiling-pharmacodynamics (3-P) relationship was proposed to investigate the processing mechanism of PN.

MATERIALS AND METHODS

Firstly, a temperature programmed steaming process was designed to evaluate the steaming triggered chemical transformation of triterpene saponins and the corresponding enhancement in anti-platelet aggregation activity. The steaming process was programed from the conventional 100 °C-150 °C in a time course of 0-12 h, aiming to achieve the maximized conversion of rare ginsenosides (RGs), and dynamic profile of ginsenosides were constructed by a UPLC-Q-TOF-MS/MS analysis. Then, a processing-(chemical) profiling-pharmacodynamics (3-P) relationship was assessed by using the grey relational analysis (GRA) and orthogonal projections to latent structures (OPLS), and validated by bioactive fraction of 140 °C steamed PN. Subsequently, the P2Y12-ligand binding affinity of potential candidates was analyzed by molecular docking. Finally, the dynamic changes of ginsenosides during steaming of SPN were quantitatively detected by UPLC-QQQ-MS/MS.

RESULTS

A total of 48 differential ginsenosides were characterized and monitored including the primary and secondarily transformed saponins. The higher temperature steaming especially at 140 °C induces not only the predominant production of the RGs, but also the stronger anti-platelet aggregation activity. The 3-P relationship showed the fraction (3) of 140 °C steamed PN rich in RGs exhibits the most predominant efficacy, in which, a series of RGs including ginsenosides Rg5, Rk1, 20(S/R)-Rg3 were proven to be potent components. Molecular docking analysis suggested that ginsenosides Rg5 and Rk1 showed more strong interaction with the platelet P2Y12 receptor. Quantitative analysis found 140 °C-2h PN possessed highest contents of Rk1 and Rg5 and total RGs.

CONCLUSIONS

The integrated 3-P strategy uncovered the promising ginsenosides with anti-platelet effect, thereby revealing the material basis of PN steaming, which could provide a new enlightenment for the investigation of processing mechanism of traditional Chinese medicines.

Quality Consistency Evaluation of Traditional Chinese Medicines: Current Status and Future Perspectives

Quality consistency evaluation of traditional Chinese medicines (TCMs) is a crucial factor that determines the safe and effective application in clinical settings. However, TCMs exhibit diverse, heterogeneous, complex, and flexible chemical compositions, as well as variability in preparation processes. These characteristics pose greater challenges in researching the consistency of TCMs compared to chemically synthesized and biological drugs. Therefore, it is paramount to develop effective strategies for evaluating the quality consistency of TCMs. From the starting point of quality properties, this review explores the strategy used to evaluate quality consistency in terms of chemistry-based strategy (chemical consistency) and the biology-based strategy (bioequivalence). Among them, the chemistry-based strategy is the mainstream, and biology-based strategy complements the chemistry-based strategy each other. Furthermore, the emerging chemistry-biology strategies (overall evaluation) is discussed, including individually combining strategy and integration strategy. Finally, this review provides insights into the challenges and future perspectives in this field. By highlighting current status and trends in TCMs quality consistency, this review aims to contribute to establishment of generally applicable chemistry-biology integrated evaluation strategy for TCMs. This will facilitate the advancement toward a higher stage of overall quality evaluation.

Identification of key phenolic compounds for alleviating gouty inflammation in edible chrysanthemums based on spectrum-effect relationship analyses

Edible chrysanthemum is a common food resource for tea and functional foods with potential benefits for human health. Studies have indicated that chrysanthemum has the potential effect on inflammatory diseases, while the effects on gouty inflammation remain underexplored. The present study aimed to investigate the anti-gout activity and characterize the active ingredients of chrysanthemums by using metabolite profiles, in vitro experiments, and spectrum-effect analysis. Results showed that 'Boju' (BJ), 'Hangbaiju' (HBJ), and 'Huaiju' (HJ) exhibited regulatory effects on monosodium urate (MSU)-induced inflammation. At the dose of 50 µg/mL, the inhibitory rates of IL-1β secretion were 24.53 %, 14.36 %, and 38.10 %, respectively. A total of 32 phenolic compounds were identified or preliminarily assigned in UPLC-Q/TOF-MS analysis. And seven phenolics related to anti-gout activity were identified by spectrum-effect relationships. According to ADME (absorption, distribution, metabolism, excretion) evaluation and experiments verification, luteolin, acacetin-7-O-glucoside, and apigenin-7-O-glucoside were critical constituents potentially associated with the reduction of inflammation in gout. Additionally, these phenolics might be suitable as quality control indicators. This study clarified the anti-gout properties of different cultivars of chrysanthemums and active compounds, providing a theoretical basis for its scientific utilization in functional foods.

Spectrum-Effect Relationship in Chinese Herbal Medicine: Current Status and Future Perspectives

The quality of Chinese herbal medicine (CHM) directly impacts clinical efficacy and safety. Fingerprint technology is an internationally recognized method for evaluating the quality of CHM. However, the existing quality evaluation models based on fingerprint technology have blocked the ability to assess the internal quality of CHM and cannot comprehensively reflect the correlation between pharmacodynamic information and active constituents. Through mathematical methods, a connection between the "Spectrum" (fingerprint) and the "Effect" (pharmacodynamic data) was established to conduct a spectrum-effect relationship (SER) of CHM to unravel the active component information associated with the pharmacodynamic activity. Consequently, SER can efficiently address the limitations of the segmentation of chemical components and pharmacodynamic effect in CHM and further improve the quality evaluation of CHM. This review focuses on the recent research progress of SER in the field of CHM, including the establishment of fingerprint, the selection of data analysis methods, and their recent applications in the field of CHM. Various advanced fingerprint techniques are introduced, followed by the data analysis methods used in recent years are summarized. Finally, the applications of SER based on different research subjects are described in detail. In addition, the advantages of combining SER with other data are discussed through practical applications, and the research on SER is summarized and prospected. This review proves the validity and development potential of the SER and provides a reference for the development and application of quality evaluation methods for CHM.

Quality evaluation of Keteling capsules based on fingerprinting, multicomponent quantification, and quantitative prediction

The Keteling capsule (KC) is a traditional Chinese medicine (TCM) made from the dried extract of Ficus microphylla and an appropriate amount of chlorpheniramine maleate. It is widely used to treat cough and relieve asthma. Despite its extensive usage, a rapid and comprehensive quality evaluation strategy for KC remains a challenge. This study introduces an electrochemical fingerprint analysis technique, in addition to the commonly employed HPLC fingerprints, for efficient and convenient quality evaluation. Moreover, a cost-effective, rapid, and accurate multi-component quantification technique known as the "Multi-markers assay by the monolinear method (MAML)" and the "FT-IR quantitative model" were explored. The HPLC fingerprints were evaluated using a systematically quantified fingerprint method, while the electrochemical fingerprints, based on the Belousov-Zhabotinsky oscillation reaction principle, were effectively analyzed and characterized using oxidation induction times and oscillation lifetimes. Multi-component quantitative analysis was carried out through the MAML and FT-IR quantitative models. The HPLC fingerprint successfully classified the 22 samples into eight grades with excellent discrimination. Active ingredient content analysis was achieved using reliable parameters obtained from electrochemical fingerprinting. The no significant difference in the quantitative results proves the accuracy of the MAML method. Additionally, successful FT-IR quantitative prediction models were developed for chlorogenic acid, isovitexin, and chlorpheniramine maleate. This study offers a dependable and effective approach for enhancing the quality control of KC, and it can provide new insights for improving the quality analysis methods in the field of TCM.

Spectrum-Effect Relationships as an Effective Approach for Quality Control of Natural Products: A Review

As natural products with biological activity, the quality of traditional Chinese medicines (TCM) is the key to their clinical application. Fingerprints based on the types and contents of chemical components in TCM are an internationally recognized quality evaluation method but ignore the correlation between chemical components and efficacy. Through chemometric methods, the fingerprints represented by the chemical components of TCM were correlated with its pharmacodynamic activity results to obtain the spectrum-effect relationships of TCM, which can reveal the pharmacodynamic components information related to the pharmacodynamic activity and solve the limitations of segmentation of chemical components and pharmacodynamic research in TCM. In the 20th anniversary of the proposed spectrum-effect relationships, this paper reviews its research progress in the field of TCM, including the establishment of fingerprints, pharmacodynamic evaluation methods, chemometric methods and their practical applications in the field of TCM. Furthermore, the new strategy of spectrum-effect relationships research in recent years was also discussed, and the application prospects of this technology were discussed.

Identification of Efficacy-Associated Markers to Discriminate Flos Chrysanthemum and Flos Chrysanthemi Indici Based on Fingerprint-Activity Relationship Modeling: A Combined Evaluation over Chemical Consistence and Quality Consistence

Monitoring the quality consistency of traditional Chinese medicines, or herbal medicines (HMs), is the basis of assuring the efficacy and safety of HMs during clinical applications. The purpose of this work was to characterize the difference in hydrophilic antioxidants and related bioactivities between Flos Chrysanthemum (JH) and its wild relatives (Chrysanthemum indicum L.; YJH) based on the establishment of fingerprint-efficacy relationship modeling. The concentrations of the total phenolics and flavonoids of JH samples were shown to be generally higher than those of YJH, but the concentration distribution ranges of YJH were significantly greater compared to JH samples, possibly related to environmental stress factors leading to the concentration fluctuations of phytochemicals during the growth and flowering of Chrysanthemum cultivars. Correspondingly, the total antioxidant capabilities of JH were greatly higher than those of YJH samples, as revealed by chemical assays, including DPPH and ABTS radical scavenging activities and FRAP assays. In addition, cellular-based antioxidant activities confirmed the results of chemical assays, suggesting that the differences in antioxidant activities among the different types of Chrysanthemums were obvious. The extracts from YJH and JH samples showed significant α-glucosidase inhibitory activity and lipase-inhibitory activity, implying the modulatory effects on lipid and glucose metabolisms, which were also confirmed by an untargeted cell-based metabolomics approach. The selected common peaks by similarity analysis contributed to the discrimination of YJH and JH samples, and the modeling of the fingerprint-bioactivity relationship identified neochlorogenic acid, isochlorogenic acid A, and linarin as efficacy-associated chemical markers. These results have demonstrated that integrating HPLC fingerprints and the analysis of similarity indexes coupled with antioxidant activities and enzyme-inhibitory activities provides a rapid and effective approach to monitoring the quality consistency of YJH/JH samples.

Quality assessment of traditional Chinese medicine based on data fusion combined with machine learning: A review

The authenticity and quality of traditional Chinese medicine (TCM) directly impact clinical efficacy and safety. Quality assessment of traditional Chinese medicine (QATCM) is a global concern due to increased demand and shortage of resources. Recently, modern analytical technologies have been extensively investigated and utilized to analyze the chemical composition of TCM. However, a single analytical technique has some limitations, and judging the quality of TCM only from the characteristics of the components is not enough to reflect the overall view of TCM. Thus, the development of multi-source information fusion technology and machine learning (ML) has further improved QATCM. Data information from different analytical instruments can better understand the connection between herbal samples from multiple aspects. This review focuses on the use of data fusion (DF) and ML in QATCM, including chromatography, spectroscopy, and other electronic sensors. The common data structures and DF strategies are introduced, followed by ML methods, including fast-growing deep learning. Finally, DF strategies combined with ML methods are discussed and illustrated for research on applications such as source identification, species identification, and content prediction in TCM. This review demonstrates the validity and accuracy of QATCM-based DF and ML strategies and provides a reference for developing and applying QATCM methods.

Exploration of the anti-inflammatory mechanism of Lanqin oral solution based on the network pharmacology analysis optimized by Q-markers selection

Network pharmacology is widely used to predict the mechanism of traditional Chinese medicines (TCM), but the framework in traditional network pharmacology analysis ignores the relationship between the concentration of components and drug efficacy. Lanqin oral solution (LOS) is a TCM formulation that widely used in the clinical treatment of pharyngitis, but its pharmacodynamic mechanism is still unknown. The present study was designed to elaborate the anti-inflammatory mechanism of LOS based on the quality markers (Q-markers). The efficacy of LOS was correlated with the fingerprint common peaks by chemometrics to select key peaks, and the Q-markers were further confirmed by mass spectrometry. Network pharmacology analysis was performed based on the chosen Q-markers to elaborate the potential pharmacodynamic mechanisms. Four efficacy-related chromatographic peaks were screened by the novel competitive adaptive reweighted sampling (CARS) spectrum-effect relationship analysis and series of other chemometrics methods. Four peaks were further characterized as the Q-markers in the LOS by mass spectrometry, i.e., geniposide, berberine, palmatine and baicalin. The ingredient-target network demonstrated that the LOS showed more impact on the NF-κB signaling pathway to elicit anti-inflammatory ability. Overall, the present study has introduced CARS into the spectrum-effect relationship analysis for the first time, which complemented the commonly applied chemometric methods. The network established based on the screened Q-markers was highly interpretable and successfully achieved the prediction of the anti-inflammatory mechanism of LOS. The proposed workflow provides a systematic method for exploring the mechanism of TCM based on identifying efficacy indicators. More importantly, it offers a reference for clarifying the mechanisms for other TCM formulations.

Discovery of Hepatotoxic Equivalent Markers and Mechanism of Polygonum multiflorum Thunb. by Metabolomics Coupled with Molecular Docking

Polygonum multiflorum Thunb. (PMT), a commonly used Chinese herbal medicine for treating diseases such as poisoning and white hair, has attracted constant attention due to the frequent occurrence of liver injury incidents. To date, its hepatotoxic equivalent markers (HEMs) and potential hepatotoxic mechanisms are still unclear. In order to clarify the HEMs of PMT and further explore the potential mechanisms of hepatotoxicity, firstly, the chemical constituents in PMT extract were globally characterized, and the fingerprints of PMT extracts were established along with the detection of their hepatotoxicity in vivo. Then, the correlations between hepatotoxic features and component contents were modeled by chemometrics to screen HEMs of PMT, which were then further evaluated. Finally, the hepatotoxic mechanisms of PMT were investigated using liver metabolomics and molecular docking. The results show that the chemical combination of 2,3,5,4-tetrahydroxystilbene-2-O-β-D-glucoside (TSG) and emodin-8-O-glucoside (EG) was discovered as the HEMs of PMT through pre-screening and verifying process. Liver metabolomics revealed that PMT caused liver injury by interfering with purine metabolism, which might be related to mitochondrial function disorder and oxidative injury via the up-regulations of xanthosine and xanthine, and the down-regulation of 5' nucleotidase (NT5E) and adenylate kinase 2 (AK2). This study not only found that the HEMs of PMT were TSG and EG, but also clarified that PMT might affect purine metabolism to induce liver injury, which contributed to our understanding of the underlying mechanisms of PMT hepatotoxicity.

Characterization of the anti-AChE potential and alkaloids in Rhizoma Coptidis from different Coptis species combined with spectrum-effect relationship and molecular docking

Coptis species are the main source of Rhizoma Coptidis (RC) drugs, which have always been used to treat Alzheimer's disease in the clinical experience of ancient China. However, many species of this genus have been largely underutilized until now. With this fact, this research has been designed to investigate for the first time the anti-acetylcholinesterase (AChE) property of different extracts for RC drugs from four Coptis species (C. chinensis, C. deltoidea, C. teeta and C. omeiensis) and to quantify the main alkaloids. Petroleum ether, ethyl acetate and n-butanol fractions of RC drugs were sequentially collected using an accelerated solvent extraction technique. Spectrum-effect relationship and molecular docking were applied to analyse the relationships between alkaloids and AChE inhibitory activity. The N-butanol extract was proven to be the main active fraction, and C. teeta may be the best source of RC drugs for Alzheimer's disease treatment, with significantly lower IC 20, IC 50 and IC 80 values for AChE inhibition. The UPLC/QqQ-MS quantitative analysis showed that the accumulations of 10 alkaloids in RC drugs from different sources greatly varied. Three data processing methods (Random forest, Boruta and Pearson correlation) comprehensively analysed the spectrum-effect relationship and revealed that columbamine, berberine and palmatine were the most important AChE inhibitors that could be used as quality markers to select RC drugs for Alzheimer's disease treatment. In addition, the dominant compounds were successfully docked against AChE to verify the binding affinity and interactions with the active site. The present study can contribute to the reasonable development and utilization of RC drugs from different sources, especially to provide certain evidence for their application in the treatment of Alzheimer's disease.

Discovery of potential hypoglycemic metabolites in Cassiae Semen by coupling UHPLC-QTOF-MS/MS combined plant metabolomics and spectrum-effect relationship analyses

Cassiae Semen (CS) is consumed as fried tea or medicinal food in Asian areas. Its two commercial forms, namely raw and fried CS, exert different clinical applications, in which fried CS is commonly applied as a functional tea for losing weight. To prevent confusion in the use of the two forms of CS, a comprehensive strategy by combining plant metabolomics and spectrum-effect relationship analyses was developed for the fast and efficient discrimination of raw and fried CS, and further for the discovery of the potential hypoglycemic metabolites of CS to control its quality. First, the plant metabolic profiling of raw and processed samples was performed by UHPLC-QTOF-MS/MS. A total of 1111 differential metabolites were found to well distinguish the raw and fried CS after analyzing by MPP software. Subsequently, α-glucosidase inhibition of raw and fried CS was investigated. As a result, fried CS demonstrated much stronger α-glucosidase inhibition activity than the raw sample. By analyzing the spectrum-effect relationship with GRA, BCA, and PLSR, 14 potential hypoglycemic-related compounds were discovered. As anticipated, they were also found as the differential metabolites of the raw and fried samples with a potential hypoglycemic effect, which might be beneficial for the quality control of CS tea. Additionally, molecular docking analysis was conducted to reveal the underlying inhibition mechanisms of the four most critical constituents, including physcion, chrysoobtusin, aurantio-obtusin, and obtusifolin. This study provides a powerful tool for the discrimination of processed samples and fast screening of the active constituents in complex natural products on a high-throughput basis.

A stepwise strategy integrating metabolomics and pseudotargeted spectrum–effect relationship to elucidate the potential hepatotoxic components in Polygonum multiflorum

Polygonummultiflorum (PM) Thunb., a typical Chinese herbal medicine with different therapeutic effect in raw and processed forms, has been used worldwide for thousands of years. However, hepatotoxicity caused by PM has raised considerable concern in recent decades. The exploration of toxic components in PM has been a great challenge for a long time. In this study, we developed a stepwise strategy integrating metabolomics and pseudotargeted spectrum–effect relationship to illuminate the potential hepatotoxic components in PM. First, 112 components were tentatively identified using ultraperformance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS). Second, based on the theory of toxicity attenuation after processing, we combined the UPLC-Q-TOF-MS method and plant metabolomics to screen out the reduced differential components in PM between raw and processed PM. Third, the proposed pseudotargeted MS of 16 differential components was established and applied to 50 batches of PM for quantitative analysis. Fourth, the hepatocytotoxicity of 50 batches of PM was investigated on two hepatocytes, LO2 and HepG2. Last, three mathematical models, gray relational analysis, orthogonal partial least squares analysis, and back propagation artificial neural network, were established to further identify the key variables affecting hepatotoxicity in PM by combining quantitative spectral information with toxicity to hepatocytes of 50 batches of PM. The results suggested that 16 components may have different degrees of hepatotoxicity, which may lead to hepatotoxicity through synergistic effects. Three components (emodin dianthrones, emodin-8-O-β-D-glucopyranoside, PM 14-17) were screened to have significant hepatotoxicity and could be used as toxicity markers in PM as well as for further studies on the mechanism of toxicity. Above all, the study established an effective strategy to explore the hepatotoxic material basis in PM but also provides reference information for in-depth investigations on the hepatotoxicity of PM.

Multiple Fingerprints and Spectrum-Effect Relationship of Polysaccharides from Saposhnikoviae Radix

PMP-HPLC, FT-IR, and HPSEC fingerprints of 10 batches of polysaccharides from Saposhnikoviae Radix with different production areas and harvest times have been prepared, and the chemometrics analysis was performed. The anti-allergic activity of 10 batches of Saposhnikoviae Radix polysaccharide (SP) was evaluated, and the spectrum-effect relationship of the 10 batches of SP was analyzed by gray correlation degree with the chromatographic fingerprint as the independent variable. The results showed that the PMP-HPLC, HPSEC, and FT-IR fingerprints of 10 batches of SP had a high similarity. Two monosaccharides (rhamnose and galactose), the polysaccharide fragment Mn = 8.67 × 106~9.56 × 106 Da, and the FT-IR absorption peak of 892 cm−1 can be used as the quality control markers of SPs. All 10 batches of SP could significantly inhibit the release of β-HEX in RBL-231 cells, and the polysaccharides harvested from Inner Mongolia in the winter had the best anti-allergic activity. The spectrum-effect relationship model showed that the monosaccharide composition and molecular weight were related to the anti-allergic activity of the SPs. Multiple fingerprints combined with spectrum-effect relationship analysis can evaluate and control the quality of SPs from the aspects of overall quality and efficacy, which has more application value.

A precise efficacy determination strategy of traditional Chinese herbs based on Q-markers: Anticancer efficacy of Astragali radix as a case

BACKGROUND

As a "multi-components and multi-efficacy" complex system, traditional Chinese herbs are universally distributed and applied in treating clinical diseases. However, the efficacy deviation and ambiguous clinical location are affected by different effects and content of components caused by uncertain factors in the production process. It further restricts resource allocation and clinical medication and hinders modernization and globalization. In this study, a precise efficacy determination strategy was innovatively proposed, aiming to quantitatively predict the efficacy of herbs and obtain precise medicinal materials. Quality-markers (Q-markers) characterizing the efficacy are conducive to achieving precise efficacy determination.

PURPOSE

With the anticancer efficacy of Astragali radix (AR) as a case, the present study was designed to establish a methodology for precise efficacy determination based on Q-markers characterizing specific efficacy.

METHODS

Guided by the basic principles of Q-markers, the potential Q-markers characterizing the anticancer efficacy of AR were screened through molecular simulation and network pharmacology. The activity of Q-markers was evaluated on MDA-MB-231 cells, and the content of Q-markers was determined by HPLC. A quantitative efficacy prediction model of the relationship between the influencing factors and anticancer efficacy was further constructed through the effect-constituents index (ECI) and machine learning and verified by biotechnology, which can be directly applied to predict the efficacy in numerous samples.

RESULTS

Astragaloside I, astragaloside II, and astragaloside III inhibited the proliferation of MDA-MB-231 cells and were successfully quantified in AR samples, reflecting the effectiveness and measurability of Q-markers. Gradient Boost Regression showed the best performance in the quantitative efficacy prediction model with EV_test= 0.815, R²_test= 0.802. The results of precise efficacy determination indicated that 1-2-3 (Wuzhai, Shanxi, two years, C segment) sample performed best in 54 batches of AR samples with biased anticancer efficacy. Furthermore, AR samples with higher ECI had higher anticancer efficacy and vice versa.

CONCLUSION

The precise efficacy determination strategy established in the present study is reliable and proved in the AR case, which is expected to support resource allocation optimization, efficacy stability improvement, and precise clinical medication achievement.

Advances in Fingerprint Analysis for Standardization and Quality Control of Herbal Medicines

Herbal drugs or herbal medicines (HMs) have a long-standing history as natural remedies for preventing and curing diseases. HMs have garnered greater interest during the past decades due to their broad, synergistic actions on the physiological systems and relatively lower incidence of adverse events, compared to synthetic drugs. However, assuring reproducible quality, efficacy, and safety from herbal drugs remains a challenging task. HMs typically consist of many constituents whose presence and quantity may vary among different sources of materials. Fingerprint analysis has emerged as a very useful technique to assess the quality of herbal drug materials and formulations for establishing standardized herbal products. Rather than using a single or two marker(s), fingerprinting techniques take great consideration of the complexity of herbal drugs by evaluating the whole chemical profile and extracting a common pattern to be set as a criterion for assessing the individual material or formulation. In this review, we described and assessed various fingerprinting techniques reported to date, which are applicable to the standardization and quality control of HMs. We also evaluated the application of multivariate data analysis or chemometrics in assisting the analysis of the complex datasets from the determination of HMs. To ensure that these methods yield reliable results, we reviewed the validation status of the methods and provided perspectives on those. Finally, we concluded by highlighting major accomplishments and presenting a gap analysis between the existing techniques and what is needed to continue moving forward.

Evaluating the quality consistency of Keteling capsules by three-dimensional quantum fingerprints and HPLC fingerprint

Keteling capsules (KCs), as a kind of Traditional Chinese Medicine (TCM), have been widely used in curing cough and relieving asthma. However, the complicated compositions make it challenging to evaluate their quality consistency by common methods. Herein, we explored comprehensive and efficient strategies by combining the multiple techniques to monitor and assess the characteristics of KCs. We employed the fingerprints and corresponding quantum fingerprints by fourier transform infrared spectroscopy (FT-IR), ultraviolet (UV), and differential scanning calorimetry (DSC). The antioxidant activity profiles were also studied combined with the result of three-dimensional quantum fingerprints and showed a good correlation with the internal structure and physical-chemical state. Furthermore, the 17 samples were separated and identified simultaneously by HPLC quantitative fingerprint, of which four active ingredients (chlorogenic acid, p-coumaric acid, vitexin and isovitexin) were quantitatively determined. The 17 samples were successfully classified into different grades by the systematically quantified fingerprint method (SQFM) and the quality of the samples was integrated according to the mean algorithm. The mean algorithm fusion of different evaluation techniques was compared to reveal the relationship between them, which indicated the effective improvement in accuracy and integrality. The combination of multiple analytical techniques developed in this study would effectively improve the existing single analytical methods and provide new strategy for drug quality consistency control.

Machine Learning Approaches in Traditional Chinese Medicine: A Systematic Review

Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithms. Owing to all research of traditional Chinese medicine (TCM) belonging to the digitalization of clinical records or experimental works, a massive and complex amount of data has become an inextricable part of the related studies. It is thus not surprising that ML approaches, as novel and efficient tools to mine the useful knowledge from data, have created inroads in a diversity of scopes of TCM over the past decade of years. However, by browsing lots of literature, we find that not all of the ML approaches perform well in the same field. Upon further consideration, we infer that the specificity may inhere between the ML approaches and their applied fields. This systematic review focuses its attention on the four categories of ML approaches and their eight application scopes in TCM. According to the function, ML approaches are classified into four categories, including classification, regression, clustering, and dimensionality reduction, and into 14 models as follows in more detail: support vector machine, least square-support vector machine, logistic regression, partial least squares regression, k-means clustering, hierarchical cluster analysis, artificial neural network, back propagation neural network, convolutional neural network, decision tree, random forest, principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis. The eight common applied fields are divided into two parts: one for TCM, such as the diagnosis of diseases, the determination of syndromes, and the analysis of prescription, and the other for the related researches of Chinese herbal medicine, such as the quality control, the identification of geographic origins, the pharmacodynamic material basis, the medicinal properties, and the pharmacokinetics and pharmacodynamics. Additionally, this paper discusses the function and feature difference among ML approaches when they are applied to the corresponding fields via comparing their principles. The specificity of each approach to its applied fields has also been affirmed, whereby laying a foundation for subsequent studies applying ML approaches to TCM.

A Strategy for Screening the Lipid-Lowering Components in Alismatis Rhizoma Decoction Based on Spectrum-Effect Analysis

Alismatis Rhizoma decoction (ARD), comprised of Alisma plantago-aquatica subsp. orientale (Sam.) Sam and Atractylodes macrocephala Koidz. at a ratio of 5 : 2, is a classic traditional Chinese medicine (TCM) formula with successful clinical hypolipidemic effect. This paper aimed to explore the major bioactive compounds and potential mechanism of ARD in the treatment of hyperlipidemia on the basis of spectrum-effect analysis and molecular docking. Nine ARD samples with varying ratios of the constituent herbs were prepared and analyzed by UPLC-Q-TOF/MS to obtain the chemical spectra. Then, the lipid-lowering ability of the nine samples was tested in an oleic acid-induced lipid accumulation model in human hepatoma cells (HepG₂). Grey relational analysis and partial least squares regression analysis were then performed to determine the correlation between the chemical spectrums and lipid-lowering efficacies of ARD. The potential mechanisms of the effective compounds were investigated by docking with the farnesoid X receptor (FXR) protein. The results indicated that alisol B 23-acetate, alisol C 23-acetate, and alisol B appeared to be the core effective components on hyperlipidemia in ARD. Molecular docking further demonstrated that all three compounds could bind to FXR and were potential FXR agonists for the treatment of hyperlipidemia. This study elucidated the effective components and potential molecular mechanism of action of ARD for treating hyperlipidemia from a perspective of different compatibility, providing a new and feasible reference for the research of TCM formulas such as ARD.

Quality assessment of Succus Bambusae oral liquids based on gas chromatography/mass spectrometry fingerprints and chemometrics

RATIONALE

Succus Bambusae is consumed as a kind of herbal medicine and natural beverage in China. However, the current quality standards for Succus Bambusae are low and lack safety indicators, which makes it difficult to effectively guarantee its quality. Therefore, it is of great significance to study the identification and quality control technology for the product.

METHODS

We have developed a set of qualitative and quantitative methods based on gas chromatography/mass spectrometry (GC/MS) for the analysis of volatile components in Succus Bambusae oral liquid (SBOL). Combining GC/MS fingerprint analysis and related chemometrics algorithms, with similarity evaluation, Hotelling T² and distance to Model X (DModX) as criteria, the quality consistency of different batches was evaluated, and SBOL samples from different manufacturers were differentiated.

RESULTS

Twenty-nine volatile components were preliminarily identified from 40 batches of SBOL samples from six manufacturers, and six Q-markers (Quality Markers) for the SBOLs were discussed and determined using GC/MS. The products from different manufacturers were distinguished using chemometrics.

CONCLUSIONS

The results showed that the quality of the SBOL samples from different batches and different manufacturers fluctuated greatly, which suggested that research into the raw materials and manufacturing techniques should be strengthened to improve the quality of SBOL and ensure its quality consistency.

Multi-parametric cellular imaging coupled with multi-component quantitative profiling for screening of hepatotoxic equivalent markers from Psoraleae Fructus

BACKGROUND

The hepatotoxicity of Chinese herbal medicine (CHM) is an important reason for its restrictive application. Psoraleae Fructus (PF), a commonly used CHM for treatment of osteoporosis and vitiligo etc., has caused serious concern due to the frequent occurrence of liver injury incidents. To date, its hepatotoxic equivalent markers (HEMs) and potential mechanisms are still unclear.

PURPOSE

To discover and validate the HEMs of PF and further explore the potential mechanisms of hepatotoxicity.

METHODS

Multi-parametric cellular imaging was performed by high content screening, and multi-component quantitative profiling was conducted by ultra-high performance liquid chromatography coupled with triple-quadrupole mass spectrometry. The correlations between hepatotoxic features and component contents were modeled by chemometrics including partial least square regression, back propagation-artificial neural network, and hierarchical cluster analysis. Then the candidate HEMs of PF were screened out and subjected to hepatotoxic equivalence assessment in primary hepatocytes, zebrafish, and mice, and the hepatotoxic mechanisms of PF were investigated.

RESULTS

The chemical combination of psoralen and isopsoralen was discovered as the HEMs of PF through pre-screening and verifying process. PF was demonstrated to induce oxidative stress, mitochondrial dysfunction and cellular apoptosis.

CONCLUSIONS

This study not only provides a rational strategy for screening HEMs from CHMs like PF, but also contributes to understanding the underlying mechanisms of PF hepatotoxicity.

Determination of inhibitory activity of Salvia miltiorrhiza extracts on xanthine oxidase with a paper-based analytical device

A novel paper-based analytical device (PAD) was prepared and applied to determine the xanthine oxidase (XOD) inhibitory activity of Salvia miltiorrhiza extracts (SME). First, polycaprolactone was 3D printed on filter paper and heated to form hydrophobic barriers. Then the modified paper was cut according to the specific design. Necessary reagents including XOD for the colorimetric assay were immobilized on two separate pieces of paper. By simply adding phosphate buffer, the reaction was performed on the double-layer PAD. Quantitative results were obtained by analyzing the color intensity with the specialized device system (consisting of a smartphone, a detection box and sandwich plates). The 3D-printed detection box was small, with a size of 9.0 cm × 7.0 cm × 11.5 cm. Color component G performed well in terms of linearity and detection limits and thus was identified as the index. The reaction conditions were optimized using a definitive screening design. Moreover, a 10% glycerol solution was found to be a suitable stabilizer. When the stabilizer was added, the activity of XOD could be maintained for at least 15 days under 4 °C or −20 °C storage conditions. The inhibitory activity of SME was investigated and compared to that of allopurinol. The results obtained with the PAD showed agreement with those obtained with the microplate method. In conclusion, the proposed PAD method is simple, accurate and has a potential for point-of-care testing. It also holds promise for use in rapid quality testing of medicinal herbs, intermediate products, and preparations of traditional Chinese medicines.

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The inhibitory activity of Salvia miltiorrhiza extracts on xanthine oxidase was determined with PADs.

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A double-layer structure of PAD was designed to avoid enzyme-substrate reactions during storage.

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A reaction device and a detection system were suitable for point-of-care test.

Screen of anti-migraine active compounds from Duijinsan by spectrum-effect relationship analysis and molecular docking

ETHNOPHARMACOLOGICAL RELEVANCE

Duijinsan (DJS) is a famous Chinese medicine prescription composed of Radix scutellariae (RS) and Rhei Radix (RRR), which has been mainly used for treating migraine.

AIM OF THE STUDY

This study aimed to uncover the anti-migraine active compounds from DJS and preliminary predicted the pharmacological mechanism by evaluating the spectrum-effect relationship between high-performance liquid chromatography (HPLC) fingerprints and anti-migraine effects of Duijinsan (DJS) extract combined with molecular docking.

MATERIALS AND METHODS

HPLC and LC-MS were applied for chemical analyses of DJS extracts in different proportions. Inhibition of DJS extracts on trigeminal nerve cell releasing calcitonin gene related peptide (CGRP) experiment was performed. The active compounds were screened by spectrum-effect relationship analysis and confirmed by molecular docking and the activities of major predicted compounds were validated in vitro.

RESULTS

Twenty-six common peaks were assigned and identified from the fingerprints of different proportions DJS extracts. In vitro experimental results showed that DJS extracts inhibited inflammation and release of CGRP from trigeminal nerve cells. Five predicted active compounds, Chrysin 6-C-arabinoside 8-C-glucoside, Chrysin 6-C-glucoside 8-C-arabinoside, baicalin, Chrysin-7-O-Beta-D-glucoronide and Oroxylin A 7-O-glucuronide were sorted out according to spectrum-effect relationship analysis and molecular docking comprehensively. In vitro validation experiments showed that all the predicted compounds inhibited the CGRP releasing and the activation of TRPV1 channel. Baicalin, chrysin-7-O-β-D-glucuronide and Oroxylin A-7-glucoronide significantly inhibited the activation of TRPV1 channel.

CONCLUSION

Chrysin 6-C-arabinoside 8-C-glucoside, Chrysin 6-C-glucoside 8-C-arabinoside, baicalin, Chrysin-7-O-Beta-D-glucoronide and Oroxylin A 7-O-glucuronide which can inhibit the CGRP releasing and the activation of TRPV1 channel were screened as the anti-migraine active compounds by spectrum-effect relationship analysis and molecular docking.

Prediction of allergic reaction risk of Shenmai injection based on real-world evidence coupled with UPLC-Q-TOF-MS

The allergic reaction (AR) of Chinese herbal injection (CHI) has become one of the most noticeable focuses of public health in China. However, it still remains a considerable controversy as to whether low-molecular-weight components in CHI have potential sensitization. In this study, the relationship between AR and low-molecular-weight component profile of Shenmai injection was explored by an interdisciplinary technology integrating real-world evidence and ultra-performance liquid chromatography-quadrupole time-of-flight mass spectroscopy (UPLC-Q-TOF-MS). The AR information of hospitalized patients was obtained by comprehensively analyzing real-world evidence from January 2015 to June 2019 at two Chinese hospitals. The UPLC-Q-TOF-MS was exploited to systematically investigate the low-molecular-weight component profile with 50-1500 m/z mass range, and 3725 MS1 peaks were detected. The optimized partial least squares discriminant analysis model was established to map the influence of low-molecular-weight components on AR. The results of this study showed that high levels of organic acids administered intravenously might be a potential risk factor for inducing AR. By using this method, Shenmai injection with high AR risk could be recognized precisely with 100% accuracy before clinical use.

Correlations between phytochemical fingerprints of Moringa oleifera leaf extracts and their antioxidant activities revealed by chemometric analysis

INTRODUCTION

Moringa oleifera Lam. is widely cultivated and applied in tropical and subtropical areas. Numerous studies have been focused on the antioxidant capacity of M. oleifera leaves, but its correlated bioactive phytochemicals remain elusive.

OBJECTIVE

In order to search for the corresponding chemical compounds from M. oleifera leaves responsible for their antioxidant activity, the correlations between phytochemical fingerprints of 15 batches of M. oleifera leaves and their antioxidant activities were investigated by using chemometric analysis.

MATERIAL AND METHODS

Fifteen batches of M. oleifera leaves were extracted with 90% ethanol solution, and their phytochemical fingerprints and antioxidant activities were estimated by using high-performance liquid chromatography-ultraviolet-electrospray ionisation tandem mass spectrometry (HPLC-UV/ESI-MS/MS), and three detected methods, namely 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, 2,2'-azinobis-(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) assay and ferric-reducing antioxidant power (FRAP) assay, respectively. Chemometric analysis was then applied to reveal the correlations between their phytochemical fingerprints and corresponding antioxidant capacity.

RESULTS

Fifteen M. oleifera leaf extracts exhibited strong antioxidant activities, in which 24 common compounds were identified by LC-MS. Furthermore, the partial least squares (PLS) analysis indicated that compounds 14, 16, 18 and 23 were the main potential effective components in at least two antioxidant tests. They were identified as kaempferol 3-O-rutinoside, quercetin 3-O-(6″-malonyl-glucoside), kaempferol 3-O-glucoside, and quercetin derivative, respectively.

CONCLUSION

The correlations between phytochemical fingerprints of M. oleifera leaf extracts and their corresponding antioxidant capacities were revealed by chemometric analysis, which provides an alternative method for screening for potential bioactive compounds with antioxidant capacity from M. oleifera leaves.

Quality control of Semen Hoveniae by high-performance liquid chromatography coupled to Fourier transform-ion cyclotron resonance mass spectrometry

A method based on high-performance liquid chromatography and Fourier transform-ion cyclotron resonance mass spectrometry was developed to control the quality of Semen Hoveniae. First, the chromatographic fingerprint was established in combination with the chemometrics methods such as similarity analysis, cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis to discover the qualitative markers. Then, an high-performance liquid chromatography mass spectrometry method was developed to identify the chemical constituents in Semen Hoveniae. Moreover, the content of dihydromyricetin and dihydroquercetin in Semen Hoveniae were determined by high-performance liquid chromatography. As a result, nine common peaks were assigned in the fingerprints and the similarity of the 13 batch samples varied from 0.425 to 0.993, indicating an obviously different quality. Dihydromyricetin and dihydroquercetin were the main qualitative markers to differ the quality of Semen Hoveniae. Meanwhile, a total of 21 chemical compounds were characterized by high-performance liquid chromatography mass spectrometry and six of them were identified by comparing with information of reference standards. Finally, the content of dihydromyricetin and dihydroquercetin in 13 batch samples varied from 0.824  to 7.499 mg/g and from 0.05941  to 4.258 mg/g , respectively. In conclusion, the methods developed here will provide sufficient qualitative and quantitative information for the quality control of Semen Hoveniae.

Bioactivity-guided discovery of quality control markers in rhizomes of Curcuma wenyujin based on spectrum-effect relationship against human lung cancer cells

BACKGROUND

Due to the diversity of the ingredients, the complexity of the mechanism of action, the uncertainty of the effective ingredients, coupled with the multiple species and multiple growing areas, the quality control (QC) of Traditional Chinese Medicines (TCMs) is challenging. Discovering and identifying effective compounds from the complex extracts of TCMs and then establishing a scientific QC method is the key to the holistic QC of TCMs.

PURPOSE

To develop an anti-lung-cancer-guided spectrum-effect relationship approach for the discovery of QC markers of the rhizome of Curcuma wenyujin (WEZ) and establish a bioactive compounds-based holistic QC method.

METHODS

The chemical profiling of the volatile oil (WVO) from 42 batches of WEZ collected from different growing areas was performed by GC-MS. The anti-lung cancer activity of different WVO samples was determined by CCK-8 assay against human lung cancer cells (A549). The apoptosis and cell cycle analysis under different concentrations of WVO were detected by flow cytometry. SIMCA-P software was used to perform multivariate statistical analysis on the chemical composition of different WVO samples and to find the different components. Active compounds were screened using a PLSR model of the spectrum-effect relationship. Bioactive compounds-based fingerprint and quantification of the leading bioactive compounds were developed by GC-MS and GC-FID, respectively.

RESULTS

Seventy-eight compounds were detected in WVO and 54 were successfully identified. The multivariate statistical analysis uncovered that WVO components and the anti-A549 activity of WVO at the concentration of 60 nl/ml differ greatly according to the origin of the plant. The WVO at the concentration of 60 nl/ml (IC₅₀) increased A549 cells apoptosis significantly with late and early apoptosis of 15.61% and 7.80%, and the number of cells in the G2/M phase were also increased significantly under this concentration. The spectrum-effect relationship analysis revealed that 44 compounds were positively correlated with their activities, and the result was verified by A549 cell viability assay. Sixteen positively correlated compounds were further selected as QC markers according to their relative amount > 0.5% and anticancer activity. Finally, the 16 QC markers-based GC-MS fingerprint was established to holistically control the quality of WEZ, and a GC-FID method was developed for the quantification of leading bioactive compounds, β-elemene and β-caryophyllene.

CONCLUSION

Based on an anti-lung-cancer-guided spectrum-effect relationship approach, the bioactive compounds-based holistic QC method was successfully developed for WEZ, which could provide a valuable reference for the QC of TCMs.

Using Spectrum-Effect Relationships Coupled with LC-TOF-MS to Screen Anti-arrhythmic Components of the Total Flavonoids in Hypericum attenuatum Extracts

This research explored the HPLC fingerprints of Hypericum attenuatum Choisy, which has anti-arrhythmic activity. HPLC was adopted to perform a determination of chemical fingerprints of H. attenuatum specimens acquired through seven distinct sources. The anti-arrhythmic activity of each H. attenuatum sample was obtained through pharmacodynamics experiments in animals. A regression analysis and correlation analysis were utilized to calculate the relationship of the peak and pharmacological effectiveness with the identified peak. Peaks numbered 5, 7, 13 and 14 in the fingerprint were regarded as the likely anti-arrhythmic agents. The fingerprint was compared with reference standards for identification of the correlative peaks. Liquid chromatography-time-of-flight-mass spectrometry was applied to identify its structure. As a consequence, a universal model was established for the utilization of HPLC to investigate anti-arrhythmic activity and the spectrum-effect relationship among H. attenuatum. This model is available for the discovery of the major bioactive constituents of Hypericum.

Study on the Spectrum-Effect Relationship of the Traditional Effect of Saponins in Glycyrrhiza uralensis Fisch

Licorice is a traditional Chinese medicine that has been used for a long time in China and still in great use today. The effect of licorice on tonifying spleen and invigorating qi has been proved for thousands of years, but the material basis of its effect is not clear. In this paper, we established the fingerprints of 21 batches of licorice collected from different origins in China with High-Performance Liquid Chromatography (HPLC) to identify the common peaks. Its effect of tonifying spleen and invigorating qi was confirmed through a series of praxiology experiments. The spectrum-effect relationship between HPLC fingerprints and its effect of tonifying spleen and invigorating qi of licorice was examined by gray relational analysis and partial least squares regression analysis. Results showed that the effect of licorice on tonifying spleen and invigorating qi resulted from various compounds and peaks. X₂–X₆ is presumed to be the main pharmacological substance base. This research successfully identified the spectrum-effect relationship between HPLC fingerprints and the effect of licorice on tonifying spleen and invigorating qi. The research method based on the spectrum-effect relationship helps provide new research ideas and strategies for the study of the basis of the medicinal materials and quality control of traditional Chinese medicine.

Holistic quality evaluation of compound liquorice tablets using capillary electrophoresis fingerprinting combined with chemometric methods

Integrated quality control of herbal medicine using eco-friendly capillary zone electrophoresis and equal weight ratio quantitative fingerprint method.

UHPLC-qMS spectrum-effect relationships for Rhizoma Paridis extracts

Rhizoma Paridis (RP) with significant anti-tumor and haemostatic effects, has been used as the raw material of many Traditional Chinese preparations. However, its active ingredients are still unclear. The present study aimed to discover bioactive ingredients from RP based on spectrum-relationship and chemometric methods. Firstly, the saponins extract was prepared by phytochemical methods. Furthermore, UHPLC-QTOF-MS and UHPLC-qMS were incorporated to establish an efficient and sensitive method for obtaining the chemical profiles of RP. A total of 34 saponins were characterized in RP and 13 of them were assigned as common peaks in 25 batches of samples. After evaluation of the anti-tumor and haemostatic activities of samples, spectrum-effect relationships were investigated by the grey relational analysis (GRA), orthogonal projections to latent structures (OPLS) and back propagation artificial neural network (BP-ANN). These analyses showed that polyphyllin VII (P27), polyphyllin II (P30), dioscin (P31) and polyphyllin I (P33) play a role in the haemostatic effects of RP whereas polyphyllin VII (P27), dioscin (P31), polyphyllin I (P33), progenin III (P34) were assigned as candidate ingredients accounting for the anti-tumor activity of RP. The anti-tumor and haemostatic activities of these screened ingredients were subsequently verified in vitro. Collectively, the present study established the spectrum-effect relationship mode of RP and discovered the bioactive compounds of RP, which could be also used for exploration of bioactive compounds in herbal medicines, especially for trace compounds.

Assay of active pharmaceutical ingredients in drug products based on relative response factors: Instrumentation insights and practical considerations

Relative Response Factors (RRFs) can be used for quantitation of one compound against another and it is widely used for Impurity analysis of pharmaceutical products; however, the application in potency assay is limited. Through an extensive study shown in this paper, it can be concluded that using the "RRF methodology" for potency assay is much more challenging compared to impurity analysis, due to the much tighter criteria required for potency analysis. The effects of instrument settings, which are rarely discussed or recognized in current HPLC analytical method development and quality release testing, are discussed. These factors impact the RRF just as much as other commonly recognized HPLC parameters. The effects of UV detector settings, i.e. Slit Width, Step Width, Band Width, and Data Collection Module, have been explored. This phenomenon has been demonstrated using three compounds to observe the impact of their quantitation due to the significant RRF variations. Finally, principles to reduce RRF variations have been discussed, and practical considerations of RRF application to method development and method transfer are provided.

An integrated strategy for discovering effective components of Shaoyao Gancao decoction for treating neuropathic pain by the combination of partial least-squares regression and multi-index comprehensive method

ETHNOPHARMACOLOGICAL RELEVANCE

Neuropathic pain, the incidence of which ranges from 5 to 8% in the general population, remains challenge in the treatment. Shaoyao Gancao decoction (SGD) is a Chinese classical formula used to relieve pain for thousands of years and has been applied for neuropathic pain nowadays. However, the effective components of SGD for the treatment of neuropathic pain remains unclear.

AIMS OF STUDY

To investigate the effect and potential mechanism of SGD against neuropathic pain and further reveal the effective components of SGD in the treatment of neuropathic pain.

MATERIALS AND METHODS

Spared nerve injury (SNI) model rats of neuropathic pain were orally given SGD to intervene, the components in vivo after SGD administration were determined, behavior indicators, biochemical parameters, and metabolomics were applied for assessing the efficacy. Then correlation between components and biomarkers was analyzed by pearson correlation method. To further measure the contribution of components to efficacy, the combination of partial least-squares regression (PLSR) and multi-index comprehensive method was carried out, according to the corresponding contribution degree of the results, the components with large contribution degree were considered as the effective components.

RESULTS

SGD exhibited a significant regulatory effect on neuropathic pain, which could increase the pain threshold and decrease the levels of SP, β-EP, PGE2 and NO. With the high resolution of UPLC-Q-TOF/MS technology, a total of 128 compounds from SGD were identified and 44 of them were absorbed in blood. Besides, 40 serum biomarkers were identified after intervention of SGD and the metabolic pathways were constructed. The key metabolic pathways including Glycerophospholipid metabolism, Linoleic acid metabolism, Alpha-linolenic acid metabolism, Glycosylphosphatidylinositol-anchor biosynthesis and Arachidonic acid metabolism may be related to the regulation of neuropathic pain. Metabolomics combined with PLSR and multi-index comprehensive method was utilized to discover 5 components including paeonol, DL-Arabinose, benzoic acid, hispaglabridin A and paeonilactone C as effective components of SGD in the treatment of neuropathic pain. This strategy was used to explore the effective components of SGD and elucidate its possible analgesic mechanism.

CONCLUSION

This study demonstrate that SGD significantly relieved neuropathic pain and elucidated the effective components of SGD for treating neuropathic pain, the strategy as an illustrative case study can be applied to other classical formula and is beneficial to improve the quality and efficacy.

Identification of Antitumor Constituents in Toad Venom by Spectrum-Effect Relationship Analysis and Investigation on Its Pharmacologic Mechanism

(1) Background: Toad venom (Bufonis Venenum, known as ‘Chansu’ in Chinese), the secretion of the ear-side gland and skin gland of Bufo gargarizans cantor or Duttaphrynus melanostictus Schneider, has been utilized to treat several diseases in China for thousands of years. However, due to the chemical variability of the components, systematic chemical composition and the key pharmacophores in toad venom have not yet fully understood. Besides, it contains a variety of effective compounds with different physiological activity and chemotypes, mainly including alkaloids, bufogenins, bufotoxins, and so on. The recent pharmacological researches have demonstrated that several bufogenins have remarkable pharmacological effects, such as anti-inflammatory, analgesic effects, and anti-tumor effects. Aim of the study: To identify the bioactive compounds and pharmacophores originating from toad venom based on analyzing spectrum-effect relationship by chemometrics and to explore the anti-cancer mechanism primarily. (2) Materials and methods: Fingerprint of the 21 batches of samples was established using HPLC (High Performance Liquid Chromatography). The anti-tumor activity of extracts were determined by in-vitro assays. Chemometric analysis was used to establish the spectrum-effect model and screen for active ingredients. Pharmacodynamic tests for the screened active compound monomers were conducted with in-vitro assays. Further anti-tumor mechanisms were investigated using western blot and flow cytometry. (3) Results: The established spectrum-effect model has satisfactory fitting effect and predicting accuracy. The inhibitory effect of major screened compounds on lung carcinoma cells A549 were validated in vitro, demonstrating that arenobufagin, telocinobufogenin, and cinobufotalin had significant anti-tumor effects. Through further investigation of the mechanism by western blotting and flow cytometry, we elucidated that arenobufagin induces apoptosis in A549 cells with the enhanced expression of cleaved PARP (poly (ADP-ribose) polymerase). These results may provide valuable information for further structural modification of bufadienolides to treat lung cancer and a method for discovery of anti-tumor active compounds. Conclusions: Our research offers a more scientific method for screening the principal ingredients dominating the pharmacodynamic function. These screened compounds (arenobufagin, etc.) were proven to induce apoptosis by overactivation of the PARP-pathway, which may be utilized to make BRCA (breast cancer susceptibility gene) mutant cancer cells more vulnerable to DNA damaging agents and kill them.

Spectrum-effect relationship between fingerprints and hemopoietic effects of small molecular fraction of Polygoni Multiflori radix praeparata

Polygoni multiflori Radix Praeparata (PMRP) is a traditional medicine used for nourishing essence and blood in China. However, it is unclear which PMRP compounds are responsible for its hematopoietic effect. In this study, spectrum-effect relationship was used to discovery potential hematopoietic compounds. The fingerprints of 20 PMRP batches were established by HPLC and the hematopoietic effect was determined using red blood cell, hemoglobin, hematocrit, and platelet indexes in aplastic anemia model mice. The spectrum-effect relationship between common peaks and hematopoietic efficacy values was established using gray relational analysis and partial least squares analysis. Spectrum-effect relationship results showed that peaks 21 (emodin-8-O-(6´-O-acetyl)-β-D-glucoside), 15 (2, 3, 5, 4'-tetrahydroxystilbene-2-O-di-glucoside), 16 (cis-2,3,5,4'-tetrahydroxy-stilbene-2-O-β-D-glucoside), 11 (unknown), 20(unknown, 12 (epicatechin), 29 (carboxyl emodin), and 31 (emodin) in the fingerprints were closely related to the hematopoietic effect. This work successfully established the spectrum-effect relationship between PMRP hematopoietic effect and its fingerprints, which can be used to explain the material basis for the PMRP hematopoietic effect.