Phytochemical Analysis最新文献

Introduction: This study explores the cytotoxic activity-guided isolation of the underground parts of Laserpitium hispidum M. Bieb and Laserpitium petrophilum Boiss. & Heldr., which have not been previously investigated.

Objectives: The aim is to isolate and evaluate bioactive compounds from Laserpitium L. species with anticancer potential.

Material and methods: This study involves bioactivity-guided isolation and structural studies of the pure compounds utilizing NMR, UV-Vis, IR spectroscopies, and HRMS. The cytotoxic activity of the isolated compounds was evaluated in vitro and in vivo, whereas molecular modeling, docking, and ADME predictions were conducted using Schrödinger software.

Results: The study isolated phenylpropanoids (laserine (1), latifolone (2), myristicin (3)), sterol (stigmasterol (4)), polyenes (falcarindiol (5)), sesquiterpene lactone (11-hydroxybadkhyzin (6)), and nordaucane sesquiterpene (norlasidiol angelate (7)) from L. hispidum, whereas L. petrophilum yielded 10β-acetoxy-8α-angeloyloxy-6αH,7αH-guaian-3-en-12,6-olide (8), 10β-acetoxy-8α-senecioyloxy-6αH,7αH-guaian-3-en-6,12-olide (9) and acetylisomontanolide (10). Molecular docking simulations revealed stable interactions between compounds 7 and 9 with estrogen receptor α (ERα) and vascular endothelial growth factor receptor 2 (VEGFR2), with compound 7 showing superior stability and binding affinity. In silico ADME predictions indicated favorable pharmacokinetic properties, including high oral absorption.

Conclusion: Compounds 7 and 9, representing new nordaucane and sesquiterpene lactones, have not been previously reported. In vitro cytotoxicity revealed that compound 7 exhibits potent anti-cancer activity against MCF-7 cells, whereas compound 9 showed reduced cytotoxicity. In vivo testing in Caenorhabditis elegans supported these findings, suggesting safety and efficacy in organisms. In silico results emphasize the potential of these compounds, with compound 7 promising due to its stability and strong binding affinity.

Introduction: This study investigates the composition and antibacterial properties of essential oil extracted from Pinus koraiensis (Siebold & Zucc) pine needles using a liquid nitrogen freezing treatment combined with solvent-free microwave extraction (LNSFM).

Objective: The aim is to develop a low-energy, high-efficiency extraction method for conifer essential oils, analyze their chemical composition, and evaluate their antibacterial efficacy.

Methodology: Pine needle samples were frozen with liquid nitrogen and subsequently crushed. The essential oil was extracted using solvent-free microwave technology. A single-factor test and response surface methodology were employed to optimize extraction parameters. The extraction efficiency of LNSFM was compared with traditional methods through kinetics, and the essential oil components were analyzed using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity of the extracted volatile oil was tested against Escherichia coli and Staphylococcus aureus.

Conclusion: LNSFM proves to be a green and efficient extraction method suitable for obtaining volatile oils from pine needles, which demonstrate significant antibacterial properties.

Introduction: Flavonoids are the main nonvolatile component responsible for the anti-rheumatoid arthritis (RA) synovitis activities of Artemisia argyi Folium. However, the effective ingredient remains unidentified. Spectrum-effect relationships analysis was a reliable and efficient strategy for herbal effective ingredient discovery.

Objectives: This study aimed to screen the effective ingredients within the total flavonoid from Artemisia argyi Folium (TFAA) that exhibit anti-RA synovitis activities based on spectrum-effect relationship.

Methods: TFAA was obtained through ethanol extraction and subsequent purification with D101 resin from 15 distinct batches of Artemisia argyi Folium. The fingerprint of TFAA was established using HPLC, and its efficacy against RA synovitis was evaluated by determining the inhibition rate of nitric oxide (NO) on MH7A synovioblast induced by TNF-α. Common peaks were identified using HPLC-MS/MS and authentic standards. The spectrum-effect relationships between the fingerprints and efficacy were analyzed by gray relational analysis (GRA), canonical correlation analysis (CCA), and partial least squares regression analysis (PLSR) to pinpoint the peaks responsible for the anti-RA synovitis activity, and the results were further verified by in vitro anti-RA synovitis experiments and molecular docking studies.

Results: The fingerprint revealed 14 common peaks, and 12 compounds were identified, including four caffeoylquinic acids and eight flavonoids. Among them, five flavonoids-X10 (hispidulin), X11 (jaceosidin), X12 (centaureidin), X13 (eupatilin), and X14 (casticin)-were highly relevant to anti-RA synovitis activity. Verification experiments confirmed their inhibitory effect on NO production and cytokine secretion in MH7A cells, showing anti-RA synovitis potential, which was consistent with the established spectrum effect relationship. The underlying mechanism might be related to the inhibition of iNOS.

Conclusion: Hispidulin, jaceosidin, centaureidin, eupatilin, and casticin were the key effective ingredient of TFAA responsible for its anti-RA synovitis effects. These compounds can serve as quality control markers for Artemisia argyi Folium and as lead compounds for anti-RA synovitis treatment.

Chebulae Fructus (TCF) is a traditional Chinese medicine and Tibetan medicine with high medicinal value, but its quality control indicators still need clarification. In this study, a strategy was proposed to specify the quality markers (Q-markers) of TCF by constructing a multidimensional feature network that includes dimensions of effectiveness, content, traceability, and specificity. Network pharmacology analysis was performed to validate the effectiveness of the chemical constituents in TCF through creating a TCF-component-disease-target-pathway network. By combining fingerprints analysis with UPLC-QTOF-MS, 17 differential components were identified among 19 batches of TCF samples. Serum pharmacochemical analysis on rats identified seven prototype components absorbed into the blood. The scores for the four dimensions were calculated using these identified components as candidates, and a multidimensional feature network based on the "spider-web" model was constructed. Ultimately, chebulinic acid, ellagic acid, chebulagic acid, methyl gallate, gallic acid, chebulic acid, and trigalloylglucose were clarified as Q-markers of TCF. These Q-markers screened out in this study are closely linked to the efficacy of TCF and can serve as indicator components for quality control of TCF.

Introduction: Silibinin (silybin), a bioactive component derived from the seeds of milk thistle (Silybum marianum), is recognized for its diverse pharmacological properties, including antioxidant, anti-inflammatory, and hepatoprotective effects. Given its therapeutic significance, accurately quantifying silybin in various formulations is essential. High-performance thin-layer chromatography (HPTLC) is a powerful analytical technique frequently used for this purpose. In this study, an HPTLC method was validated according to the International Council for Harmonization (ICH) guidelines to determine the concentration of silybin. The design of experiments (DoE), specifically the Box-Behnken design, was employed to optimize and understand the influence of critical method variables.

Methodology: The HPTLC method validation was performed using silica gel F254 HPTLC plates. The variables investigated included the composition of the mobile phase (% v/v), saturation time (minutes), and temperature in degree Celsius (°C), with the Box-Behnken design for optimization. The mobile phase consisted of chloroform, acetone, and formic acid in a 7:2:1 (v/v) ratio. Both the formulated scaffold and standard drug were applied to the plates, which were then processed in a twin chamber. After development, the plates were scanned at 288 nm using the Camag TLC Scanner IV with Vision CATS software.

Results: The validated HPTLC method demonstrated a strong linear relationship within the silybin concentration range of 2-10 μg/mL. The limit of detection (LOD) and limit of quantification (LOQ) for silybin were determined to be 0.469 and 1.423 μg/mL, respectively. Recovery studies indicated that the method provided accurate quantification, with recovery rates ranging from 97.53% to 99.82%. These results confirm the method's high accuracy, outstanding linearity, and reliability for the quantification of silybin in formulations.

Conclusion: The validated HPTLC method proved to be a reliable analytical tool for the quantification of silybin in various formulations, particularly those containing polymers. The method's strong linearity, precision, and accuracy align with the ICH guidelines, making it suitable for routine analysis in quality control laboratories. The use of the Box-Behnken design for method optimization highlights the importance of systematic experimentation in achieving robust analytical outcomes.

Introduction: Benincasa hispida (Thunb.) Cogn. (Cucurbitaceae) is an essential food plant in India possessing antihyperglycemic and antihyperlipidemic activities.

Objective: The objective included comparative estimation of α-glucosidase and α-amylase enzyme inhibition potential of B. hispida fractions prepared by microwave-assisted extraction and prediction of metabolite interaction against non-insulin-dependent diabetes mellitus by metabolite profiling based network pharmacology analysis.

Methods: A validated microwave-assisted extraction method was employed to obtain different fractions of B. hispida fruits. The in vitro enzyme assay was done with p-nitrophenyl-α-D-glucopyranoside and acarbose as standard to evaluate antidiabetic potential. The phytomolecules present in the active fraction were identified by UHPLC-QToF-MS/MS analysis. Network pharmacology analysis gave possible gene and disease association, combination synergy network, and predicted probable mechanism of action.

Results: The highest enzyme inhibition potential (IC₅₀) was shown by the ethyl acetate fraction (0.546 ± 0.17 mg/mL and 1.134 ± 0.42 mg/mL) compared to acarbose (0.298 ± 0.08 mg/mL and 0.532 ± 0.38 mg/mL), respectively, for α-glucosidase and α-amylase addressing the potential role in ameliorating non-insulin-dependent diabetes mellitus. Metabolite profiling resulted in the identification of 17 metabolites, and a synergy between the identified molecules suggested multimolecule action in the amelioration of non-insulin-dependent diabetes mellitus through insulin resistance pathway, AMPK signaling pathway, PPAR signaling pathway, and PI3K-Akt signaling pathway. Combination synergy of identified molecules was observed through a multitarget approach to manage non-insulin-dependent diabetes mellitus.

Conclusion: Polyphenol-enriched fraction of B. hispida fruits and identified phytocompounds ameliorate non-insulin-dependent diabetes mellitus. Thus, enriched extract of B. hispida can be further investigated in order to develop high-quality, safe, and effective products for the management of non-insulin-dependent diabetes mellitus.

Introduction: Daphne pontica L. is an evergreen shrub that is recorded as an anti-diarrheic plant in Turkish folk medicine. Previous studies on D. pontica have reported, albeit slightly, the isolation of daphnane diterpenoids, but no systematic phytochemical analysis of daphnane diterpenoids has been conducted.

Objective: This study aimed to comprehensively investigate daphnane diterpenoids in the extracts from the different parts (stems, leaves, and fruits) of D. pontica.

Methods: An ultra-high-performance liquid chromatography coupled with Q-Exactive hybrid quadrupole Orbitrap mass spectrometer (UHPLC-Q-Exactive-Orbitrap MS) was used for the qualitative analysis of D. pontica. The stems, leaves, and fruits of D. pontica were extracted with diethyl ether. Each extract was then pretreated by a solid phase extraction cartridge and subjected to LC-MS/MS analysis. Detected daphnane diterpenoids were tentatively identified by comparison with an in-house daphnane library, and their chemical structures were estimated in detail by MS/MS fragmentation evaluation.

Results: A total of 33 kinds of daphnanes were identified from the different parts of D. pontica, and were classified into three subtypes: daphnane orthoester, polyhydroxy daphnane, and macrocyclic daphnane orthoester. Among them, six daphnanes were postulated to be previously unreported compounds based on MS/MS fragmentation elucidation. Furthermore, the three plant parts showed similar daphnane diterpenoid profiles, with the stems containing the most abundant daphnane diterpenoids.

Conclusion: This is the first study to perform qualitative analysis of daphnane diterpenoids systematically and comprehensively in different parts of D. pontica. The results revealed that D. pontica is a plant resource rich in a variety of daphnane diterpenoids.

Aim: The aim of this study is to analyze the chemical composition of raspberry using liquid chromatography-mass spectrometry (LC-MS) technology, predict the potential effects of raspberry in treating type 2 diabetes through network pharmacology, and conduct preliminary validation through in vitro experiments.

Methods: A Waters CORTECS C18 column (3.0 mm × 100 mm, 2.7 μm) was used; mobile phase A consisted of 0.1% formic acid in water and mobile phase B consisted of 0.1% formic acid in acetonitrile. Gradient elution was performed with full-scan mode in both positive and negative ion modes, covering a mass range of m/z 100-1500. The chemical components of raspberry were analyzed and identified based on secondary spectra from databases and relevant literature. The disease targets related to type 2 diabetes were searched, and protein-protein interaction network analysis as well as gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted on the intersecting targets of the active components of raspberry and the disease. HepG2 cells were used for experimental validation, with high glucose-induced insulin resistance models established. The CCK-8 method was employed to assess the effects of raspberry on cell proliferation, while Western blotting was used to measure the expression of proteins related to the AGE/RAGE signaling pathway.

Results: A total of 47 components were identified, including 10 organic acids, 15 flavonoids, 12 phenols, 2 alkaloids, 4 terpenoids, 1 miscellaneous compound, 1 stilbene, 1 steroid and its derivatives, and 1 diterpenoid. Through database screening, seven active components were identified: kaempferol, epicatechin, ellagic acid, crocetin, stigmasterol, fisetin, and isorhamnetin. KEGG and GO results indicated that the therapeutic effects of raspberry on type 2 diabetes may be related to the advanced glycation end product (AGE)- receptor for advanced glycation end product (RAGE) signaling pathway. Establishment of an insulin resistance model in HepG2 cells demonstrated that, compared to the control group, the raspberry treatment group upregulated p53 protein expression while downregulating the expression of RAGE, Akt1, and Caspase-3 proteins.

Conclusion: This study preliminarily elucidates that the therapeutic effects of raspberry in treating type 2 diabetes may be mediated through the inhibition of the AGE-RAGE signaling pathway, providing important references for the study of the pharmacological basis and clinical application of raspberry.

Introduction: Quantitative determination of pharmacologically active constituents in medicinal plants is critical for quality control. Due to the chemical complexity of the crude plant extracts, the presence of interfering compounds is often problematic for the unambiguous quantitation of the designed bioactive compounds. Considering the method of quantification, quantitative NMR spectroscopy (qNMR) has gained substantial popularity as a powerful and effective technique for both qualitative and quantitative analyses of natural products.

Objective: The aim of this study is to develop a quantitative NMR method for quantifying the bioactive phenylbutanoids in Zingiber cassumunar rhizome crude extract.

Methods: Quantitative ¹H NMR (qHNMR) measurements were performed on a 600 MHz NMR spectrometer using an internal standard for the determination of the absolute quantities of four phenylbutanoids in Z. cassumunar rhizome crude extract.

Results: The direct quantification of four characteristic phenylbutanoids, i.e., (E)-1-(3',4'-dimethoxyphenyl)butadiene (DMPBD), (E)-1-(2',4',5'-trimethoxyphenyl)butadiene (TMPBD), (E)-4-(3',4'-dimethoxyphenyl)but-3-en-1-ol, and (E)-4-(3',4'-dimethoxyphenyl)but-3-en-1-yl acetate, in crude extract by qHNMR using an internal standard was achieved, with high specificity and sensitivity. The selected ¹H NMR signals could unambiguously be assigned and did not overlap with other resonances, including the highly similar compounds DMPBD and TMPBD. The method is linear in the concentration range of 0.70-14.52 mg/mL, with a limit of quantification of 0.46-0.68 mg/mL. The RSD values of intraday and interday precisions are in the range of 0.23%-0.74% and 0.29%-0.52%, respectively. The average recoveries are 99.54%-100.18%.

Conclusions: A rapid, accurate, and precise method using ¹H NMR for the simultaneous quantitation of four phenylbutanoids in the crude extract of Z. cassumunar rhizome was developed and validated.

Introduction: The inherent complexity of traditional Chinese medicine (TCM) poses significant challenges in directly correlating quality evaluation with clinical efficacy. Banxia-Houpo Decoction (BHD), a classical TCM formula, has demonstrated efficacy in treating globus hystericus. However, the intricate composition of BHD, which contains both volatile and non-volatile active components, complicates efforts to ensure its consistent quality and clinical effectiveness.

Objective: The aim of this study was to introduce an integrated approach that combines non-targeted multicomponent analysis, network pharmacology, and multivariate chemometrics to identify quality markers for the effective quality control of BHD.

Materials and methods: First, a nontargeted high-definition MSE method based on ultraperformance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UHPLC-QTOF-MS) was developed for the comprehensive multi-component characterization of BHD. Next, the quality markers of nonvolatile compounds in BHD were identified through network pharmacology analysis. Subsequently, volatile organic compounds (VOCs) in BHD samples were analyzed via headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS). Finally, the orthogonal partial least squares discriminant analysis (OPLS-DA) model was applied to screen for potential markers.

Results: Based on in-house library-driven automated peak annotation and comparison with 25 reference compounds, 128 components were identified for the first time. Additionally, honokiol, magnolol, magnoflorine, 6-gingerol, rosmarinic acid, and adenosine were preliminarily identified as potential quality markers for BHD through network pharmacology analysis. By employing two complementary techniques, HS-SPME-GC-MS and HS-GC-IMS, a total of 145 volatile compounds was identified in the BHD samples. Four potential differential VOCs in the BHD samples were further identified based on the variable importance in projection (VIP ≥ 1.5) using HS-GC-IMS combined with chemometric analysis.

Conclusion: In conclusion, this study not only contributes to establishing quality standards for BHD but also offers new insights into quality assessment and identification in the development of classical formulations enriched with volatile components.