Spectrum-Effect Relationships Between High-Performance Liquid Chromatography Fingerprints and Hepatoprotective Activities of Cuscutae Semen.

BACKGROUND: Cuscutae Semen (CS) is a commonly used hepatoprotective traditional Chinese medicine, but the chemical components responsible for its hepatoprotective activity are unclear. OBJECTIVE: The purpose of this study was to evaluate the spectrum-effect relationships between HPLC fingerprints and hepatoprotective effects of CS, and to identify its bioactive components. METHODS: Phytochemical isolation of CS extracts was first carried out and 14 potential bioactive compounds were obtained. Chemical fingerprinting was performed on 27 batches of CS from different sources by HPLC, and further analyzed by similarity analysis (SA) and hierarchical clustering analysis (HCA). Pharmacodynamic testing was performed in a CCl4-induced, acute liver injury cell model to assess the hepatoprotective activity of CS by measuring the cell viability and levels of alanine transaminase (ALT) and aspartate aminotransferase (AST). Bivariate correlations analysis (BCA) and orthogonal projections to latent structures (OPLS) were used to analyze the spectrum-effect relationships of CS. RESULTS: The results showed that the chemical fingerprints of CS were closely correlated with its hepatoprotective activity. Peaks 1, 10, 18, 19, 21, 22, and 24 might be potential hepatoprotective compounds in CS, and the validation experiments of isolated compounds indicated that chlorogenic acid (P10), hyperoside (P21), isoquercitrin (P22), and astragalin (P24) were the main hepatoprotective components. CONCLUSION: By combining chemical fingerprints with hepatoprotective evaluation, the present study provides important guidance for QC and clinical use of CS. HIGHLIGHTS: (1) Ten potential bioactive compounds were isolated from CS; (2) The spectrum-effect relationship of CS was molded by HPLC and analysed by OPLS and BCA. (3) Four compounds including chlorogenic acid were the main hepatoprotective components.

Identification of antidiabetic components in Uncariae Rammulus Cum Uncis based on phytochemical isolation and spectrum-effect relationship analysis.

OBJECTIVES: Uncariae Rammulus Cum Uncis (URCU) is a commonly used herbal medicine to treat diabetes. This work is aimed to discover and identify the antidiabetic components from URCU extract. METHODS: Column chromatography and recrystallisation were used to separate individual compounds from URCU extract, and the obtained individual compounds were used for determination of α-glucosidase inhibitory activity. Molecular docking was applied to predict the molecular interactions. High-performance liquid chromatography (HPLC) was used for fingerprint analysis of 12 batches of URCU. HPLC fingerprints were assessed by the similarity analysis (SA) and hierarchical clustering analysis (HCA). The spectrum-effect relationship analysis of URCU was assessed by orthogonal partial least squares (OPLS) and bivariate correlation analysis (BCA). RESULTS: A total of 10 potential bioactive compounds were isolated and six of them showed potent α-glucosidase inhibitory activity (IC50 = 4.21-166.10 µM). The molecular docking results revealed that the binding energy was consistent with the results of α-glucosidase inhibition activity analysis (-8.55 to -4.84 kcal/mol). The ethanol extracts of the 12 batches of URCU showed inhibitory effect on α-glucosidase in a dose-dependent manner, and the IC50 values ranged from 0.94 µg/mL to 12.57 µg/mL. The spectrum-effect relationship analysis results indicated that 13 peaks might be potential antidiabetic compounds in URCU, including 18 (hyperoside) and 19 (rutin). CONCLUSION: A comprehensive connection between URCU chemical components and α-glucosidase inhibitory activity was established for the first time by using a spectrum-effect relationship model, which might be applicable to the quality control of URCU.

Network pharmacology analysis and experimental validation to explore the mechanism of sea buckthorn flavonoids on hyperlipidemia.

ETHNOPHARMACOLOGICAL RELEVANCE: Sea buckthorn is popularly used as a herbal medicine and food additive in the world. Sea buckthorn flavonoids (SF) is reported to have an ameliorative effect on obesity and hyperlipidemia (HLP). AIM: To identify the major bioactive compounds and the lipid-lowering mechanism of SF. METHODS: We used network pharmacology analysis and in vitro experiments to identify the major bioactive compounds and the lipid-lowering mechanism of SF. RESULTS: A total of 12 bioactive compounds, 60 targets related to SF and HLP were identified, and a component-target-disease network was constructed. The KEGG analysis revealed that SF regulated cholesterol metabolism, fat digestion and absorption, and PPAR signaling pathways in HLP. The experimental validation indicated that sea buckthorn flavonoids extract (SFE) and 4 bioactive compounds reduced lipid droplet accumulation, up-regulated the mRNA expression of PPAR-γ, PPAR-α, ABCA1 and CPT1A, etc, down-regulated SREBP-2 and its target gene LDLR, which are closely related to cholesterol conversion into bile acids, de novo synthesis and fatty acids oxidation. The major bioactive flavonoid isorhamnetin (ISOR) also increased the protein expression of PPAR-γ, LXRα and CYP7A1. CONCLUSION: SF might promote cholesterol transformation into bile acids and cholesterol efflux, inhibit cholesterol de novo synthesis and accelerate fatty acids oxidation for ameliorating HLP.

Network pharmacology approach to elucidate possible action mechanisms of Sinomenii Caulis for treating osteoporosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Sinomenii Caulis (SC) is a well-konwn traditional Chinese medicine used for treatment of rheumatoid arthritis (RA), dermatophytosis and paralysis. Patients with RA are usually secondary to osteoporosis, but the potential protective effect of SC on osteoporosis (OP) is seldom reported and its possible action mechanism is little known. AIM: The purpose of this study was to demonstrate the anti-osteoporosis effects of SC extract and alkaloids in prednisolone (Pre)-induced OP of zebrafish, and then to explore the potential mechanism of SC on system level by network pharmacology. METHODS: Firstly, zebrafish OP model was established to investigate the anti-osteoporosis effect of SC. Secondly, the targets of SC and OP from multiple databases were collected, and Compound-Target-Pathway network based on protein-protein interaction (PPI) was constructed. Moreover, gene enrichment and annotation were performed via the DAVID server. Finally, the reliability of the network pharmacology prediction results in Pre-induced OP of zebrafish was verified by qRT-PCR. RESULTS: The results indicated that SC extract and alkaloids have remarkable ability to promote bone formation of cranial bones and reduce TRAP contents in Pre-induced OP of zebrafish. 32 OP-related ingredients in SC and 77 OP-related targets were screened from multiple databases, and 15 OP-related pathways were enriched by the KEGG database. Further experimental validation indicated that SC extract and alkaloids could regulate the expression of MAPK14, CASP3, CXCL8, IL-1ß, IL6, PTGS2, TNF-α, ESR1, and MMP9 for treatment of OP. CONCLUSION: In summary, we conducted an integrative analysis to provide convincing evidence that SC may partially alleviate OP by inhibiting pro-inflammatory cytokines and regulating of RANK/RANKL/OPG system.

The mechanisms of baicalin ameliorate obesity and hyperlipidemia through a network pharmacology approach.

Obesity is one of the main causes of human cardiovascular and cerebrovascular diseases. Baicalin, a bioactive flavonoid isolated from the herbal medicine Scutellaria baicalensis Georgi, is reported to ameliorate obesity and hyperlipidemia. However, its mechanism remains unclear. Here, we used network pharmacology to explore the potential mechanism of baicalin on a system level. First, we predicted the targets of baicalin and diseases, and then protein-protein interaction (PPI) networks were constructed. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was performed via the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server. Lastly, we confirmed the results of the network analysis by palmitic acid (PA) treated human hepatoma cells (HepG2) in vitro. The results indicated that 37 targets related to obesity treated by baicalin were predicted by network pharmacology, and top 10 related pathways were extracted by the KEGG database. Baicalin treatment could reduce triglyceride (TG) contents and lipid droplet accumulation in PA-treated HepG2 cells. The anti-obesity effects of baicalin might be due to the up-regulation of solute carrier family 2 member 1 (SLC2A1) and down-regulation of tumor necrosis factor (TNF), nuclear factor kappa B subunit 1 (NFKB1), sterol regulatory element binding transcription factor 1 (SREBF1), peroxisome proliferator activated receptor gamma and caspase 3 (CASP3). Our results indicated that baicalin may regulate key inflammatory markers, adipogenesis process, and apoptosis for treatment of obesity.

Integration of Zebrafish Model and Network Pharmacology to Explore Possible Action Mechanisms of Morinda officinalis for Treating Osteoporosis.

Osteoporosis (OP) is a metabolic bone disease affecting nearly 200 million individuals globally. Morinda officinalis F.C.How (MOH) has long been used as a traditional herbal medicine for the treatment of bone fractures and joint diseases in China. However, it still remains unclear how the compounds in MOH work synergistically for treating OP. In this study, we used prednisolone (PNSL)-induced zebrafish OP model to screen the antiosteoporosis components in MOH. A network pharmacology approach was further proposed to explore the underlying mechanism of MOH on OP. The PNSL-induced zebrafish model validated that two anthraquinones, one iridoid glycoside, and two saccharides exerted antiosteoporotic effect. We constructed the components-targets network and obtained the enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. A total of 26 candidate compounds of MOH and 257 related targets could probably treat OP through regulating osteoclast differentiation and MAPK signaling pathway. Our work developed a strategy to screen the antiosteoporosis components and explore the underlying mechanism of MOH for treating OP at a network pharmacology level.

Development and validation of a supercritical fluid chromatography method for fast analysis of six flavonoids in Citri Reticulatae Pericarpium.

The study is aimed to develop a rapid and efficient supercritical fluid chromatography coupled with diode-array detection (SFC-DAD) method for simultaneous quantification of six flavonoids in Citri Reticulatae Pericarpium (CRP). The chromatographic parameters including stationary phase, mobile phase composition, back pressure, temperature and flow rate, were systematically optimized with single-factor test. The results indicated that the six compounds were baseline separated on an Agilent Zorbax RX-SIL column using gradient elution within 10 min. The optimized mobile phase was constituted of carbon dioxide (CO2) and methanol. And the parameters were set as follows: backpressure, 95 bar; temperature, 45 °C; flow rate, 0.8 mL/min. The optimized method showed satisfactory retention and resolution for the analytes. The method was validated to demonstrate its selectivity, linearity, precision, accuracy and robustness. Thus, the verified SFC method was successfully applied to quantification of flavonoids present in CRP samples. The results indicated that SFC has the potential to become an excellent alternative for the analysis of flavonoids in herbal medicines, owning to its intrinsic features like high efficiency, separation speed and eco-friendly characteristics.

Rapid profiling of alkaloid analogues in Sinomenii Caulis by an integrated characterization strategy and quantitative analysis.

Alkaloids, the principal constituents in the caulis of Sinomenium acutum, have gained an increasing interest over the past decades since they are widely employed as a clinical treatment for rheumatoid arthritis. In the present study, an integrated characterization strategy by combining mass defect filtering-based structure classification (MDFSC) and diagnostic fragment-ion-based extension (DFIBE) was firstly proposed for rapid profiling of alkaloids in Sinomenii Caulis (SC) via ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS). The rectangular MDFSC window could more accurately screen the target alkaloids of different types, and the DFIBE could facilitate the acquisition of characteristic fragment ions for structural elucidation of alkaloids. High-performance liquid chromatography (HPLC) fingerprints with principal component analysis (PCA) and hierarchical clustering analysis (HCA) was established for identifying the chemical markers and simultaneous determination of sinomenine, magnoflorine, menisperine, stepharanine and ehydrodiscretine. A total of 91 alkaloids, including 82 targeted ones (26 morphinans, 22 aporphines, 20 protoberberines and 14 benzylisoquinolines) were unambiguously identified or tentatively characterized in SC, and 14 of them were reported for the first time. Sinomenine and magnoflorine could be selected as chemical markers to evaluate the quality of SC from different localities. In conclusion, the proposed method provided a potential approach for chemical profiling and holistic quality control of herbal medicines.

Identification of anti-inflammatory components in Sinomenii Caulis based on spectrum-effect relationship and chemometric methods.

The present study aimed to identify the anti-inflammatory components in Sinomenii Caulis (SC) based on spectrum-effect relationship and chemometric methods. A phytochemical investigation of SC extract was performed firstly and afforded eleven potential bioactive compounds. The HPLC fingerprints of 19 batches of SC samples were evaluated by the chemometric methods such as similarity analysis (SA) and hierarchical clustering analysis (HCA). The anti-inflammatory effects of these samples were determined by inhibition of Nitric Oxide (NO) production. Partial least squares regression (PLSR) and artificial neural network (ANN) were used to explore the spectrum-effect relationship of SC. The results indicated that there was a close correlation between chemical fingerprint and anti-inflammatory activity of SC, and peaks 8, 9, 12, 13, 14, 16, 19 and 22 might be potential anti-inflammatory compounds in SC. The verification experiments by testing individual compounds and a combination of them indicated that sinomenine (P8), magnoflorine (P13), menisperine (P16) and stepharanine (P19) were the major anti-inflammatory compounds in SC. Collectively, the present study established the spectrum-effect relationship mode of SC and discovered the anti-inflammatory compounds in SC, which could be used for exploration of bioactive components and quality control of herbal medicines.

Quantification and efficient discovery of quality control markers for Emilia prenanthoidea DC. by Fingerprint-Efficacy Relationship Modelling.

An effective and comprehensive evaluation method for identifying the origin and assessing the quality of Emilia prenanthoidea DC. was established, based on analysis of high performance liquid chromatography (HPLC) fingerprint combined with the similarity analysis (SA), the hierarchical cluster analysis (HCA) and principal component analysis (PCA). Different data analysis methods drew a similar conclusion that 12 E. prenanthoidea (EP) samples were categorized into two groups. Evaluated the anti-inflammatory effects of different EP samples by analyzing paw edema (PE), serum superoxide dismutase (SOD) activity, concentrations of serum malondialdehyde (MDA), prostaglandin E2 (PGE2) and tumor necrosis factor α (TNF-α) in the carrageenin-induced acute inflammation mouse model. With the help of Gray Correlation Analysis (GRA), partial least squares regression (PLSR) and artificial neural network (ANN), the relationship between the fingerprints and efficacy of EP was elucidated. As the results, chlorogenic acid, hyperoside and quercitrin could be selected as chemical markers to evaluate the quality of EP from different regions. Thus, a method was established to quantify 7 major bioactive ingredients in the samples under the condition of fingerprint. These results indicated that the HPLC fingerprint coupleing with Profile-Efficacy analysis would have great has potential to identify the medicinal effective components and evaluating the quality of E. prenanthoidea.

Relative tissue distribution and excretion studies of gastrodin and parishin from powder and extract of Gastrodiae Rhizoma in rat by UHPLC-ESI-MS/MS.

New research has indicated that Gastrodiae Rhizome (GR) has potential anti-diabetic and anti-asthmatic effects in mouse models. On the basis of our previous study of the relative bioavailability of gastrodin (GAS) and parishin (PA) from extract and powder of GR, we performed further research on the tissue distribution and excretion of the two analytes. A reliable bioanalytical method for the quantification of GAS and PA in rat tissues and excretion is required. Chromatographic separation was carried out on a gradient mobile phase of acetonitrile-water with 0.1% formic acid. Calibration curves (1/x2 weighted) offered satisfactory linearity (r2 > 0.9835) within 100-3000 ng mL-1 for GAS and (r2 > 0.9862) within 10-1000 ng mL-1 for PA. The relative standard deviations of the intra-day and inter-day precision were all <14.98%, whilst the relative errors of the intra-day and inter-day accuracy were all within ±14.71%. The matrix effect and recovery values were satisfactory in all of the biological matrices examination. The data of relative differences in tissue distribution and excretion of GAS and PA from powder and extract of GR indicated that higher bioavailabilities for GAS and PA were obtained when a dosage of 4 g kg-1 GR powder was used.

Studies on Chromatographic Fingerprint and Fingerprinting Profile-Efficacy Relationship of Saxifraga stolonifera Meerb.

This work investigated the spectrum-effect relationships between high performance liquid chromatography (HPLC) fingerprints and the anti-benign prostatic hyperplasia activities of aqueous extracts from Saxifraga stolonifera. The fingerprints of S. stolonifera from various sources were established by HPLC and evaluated by similarity analysis (SA), hierarchical clustering analysis (HCA) and principal component analysis (PCA). Nine samples were obtained from these 24 batches of different origins, according to the results of SA, HCA and the common chromatographic peaks area. A testosterone-induced mouse model of benign prostatic hyperplasia (BPH) was used to establish the anti-benign prostatic hyperplasia activities of these nine S. stolonifera samples. The model was evaluated by analyzing prostatic index (PI), serum acid phosphatase (ACP) activity, concentrations of serum dihydrotestosterone (DHT), prostatic acid phosphatase (PACP) and type II 5α-reductase (SRD5A2). The spectrum-effect relationships between HPLC fingerprints and anti-benign prostatic hyperplasia activities were investigated using Grey Correlation Analysis (GRA) and partial least squares regression (PLSR). The results showed that a close correlation existed between the fingerprints and anti-benign prostatic hyperplasia activities, and peak 14 (chlorogenic acid), peak 17 (quercetin 5-O-ß-d-glucopyranoside) and peak 18 (quercetin 3-O-ß-l-rhamno-pyranoside) in the HPLC fingerprints might be the main active components against anti-benign prostatic hyperplasia. This work provides a general model for the study of spectrum-effect relationships of S. stolonifera by combing HPLC fingerprints with a testosterone-induced mouse model of BPH, which can be employed to discover the principle components of anti-benign prostatic hyperplasia bioactivity.