Identifying absorbable bioactive constituents of yupingfeng powder acting on COVID-19 through integration of UPLC-Q/TOF-MS and network pharmacology analysis

Exploring the material basis and molecular targets of Changma Xifeng tablet in treating Tourette syndrome: an integrative approach of network pharmacology and miRNA analysis

This study was to investigate the mechanism of Changma Xifeng tablet, a traditional Chinese medicine in the treatment of Tourette syndrome. Network pharmacology was utilized to pinpoint blood-entering constituents of Changma Xifeng and explore their potential targets. Additionally, differential microRNA expression analysis was conducted to predict Tourette syndrome-associated targets, complemented by molecular docking and dynamics simulations to support the interactions of the active compounds with these targets. The study identified 98 common targets between Changma Xifeng and Tourette syndrome, which may be involved in the treatment process. A protein-protein interaction network and a drug-active ingredient-disease target network highlighted the formulation's multi-component, multi-target therapeutic approach. Eight pivotal targets-AR, GRM5, MET, RORA, HTR2A, CNR1, PDE4B, and TOP1-were identified at the intersection of microRNA and drug targets. Molecular docking revealed 12 complexes with favorable binding energies below - 7 kcal/mol, specifically: AR with Alfacalcidol, TOP1 with Albiflorin, GRM5 with Arachidic Acid, GRM5 with Palmitic Acid, AR with Arachidic Acid, AR with 2-Hydroxyoctadecanoic Acid, RORA with Pinellic Acid, RORA with Palmitic Acid, AR with Acoronene, AR with Epiacoronene, AR with 4,4'-Methylenediphenol, and HTR2A with Calycosin. Our molecular docking and molecular dynamics simulations suggest potential stable interactions between the formulation's active components and target proteins. These computational methods provide a preliminary theoretical framework that will guide our future experimental work. The study provides a scientific rationale for the use of traditional Chinese medicine in Tourette syndrome management and offers new insights for drug development.

Study on the enhanced efficacy mechanism of vinegar-processed Cyperus rotundus in the treatment of primary dysmenorrhea

The enhanced efficacy of vinegar-processed Cyperus rotundus (VCR) in treating primary dysmenorrhea (PD) has been observed. However, the active components and potential mechanisms of synergy are still unclear. The objective of this study was to develop a method that combines bionic technology, plant metabolomics and network pharmacology to discover the active components and potential mechanisms underlying the enhanced therapeutic effects of VCR for PD. Vinegar processing alters the flavor of C. rotundus, leading to changes in its properties. The acidic nature of vinegar enhances the selectivity of the medicine toward the liver, thereby improving its ability to soothe the liver, regulate qi and provide pain relief. Through gas chromatography-mass spectrometry and multivariate statistical analysis, 30 key differential components between raw C. rotundus and VCR have been screened and identified. These differential components primarily exert their therapeutic effects in treating PD by modulating targets such as interleukin-6, TNF, TP53 and PTGS2, as well as pathways including the estrogen signaling pathway, ovarian steroidogenesis, the TNF signaling pathway and the HIF-1 signaling pathway. The findings of this study serve as a reference for the application of VCR in compound formulas and clinic practiceal. Furthermore, the methodology employed in this study provides research insights for the processing of other Chinese medicines.

Quantification of binding capacity of natural products to target proteins by sensors integrating SERS labeling and photocrosslinked molecular probes

Natural products-based screening of active ingredients and their interactions with target proteins is an important ways to discover new drugs. Assessing the binding capacity of target proteins, particularly when multiple components are involved, presents a significant challenge for sensors. As far as we know, there is currently no sensor that can accomplish high-throughput quantitative analysis of natural product-target protein binding capacity based on Raman spectroscopy. In this study, a novel sensor model has been developed for the quantitative analysis of binding capacity based on Surface-Enhanced Raman Spectroscopy (SERS) and Photocrosslinked Molecular Probe (PCMP) technology. This sensor, named SERS-PCMP, leverages the high throughput of molecular probe technology to investigate the active ingredients in natural products, along with the application of SERS labelling technology for target proteins. Thus it significantly improves the efficiency and accuracy of target protein identification. Based on the novel strategy, quantitative analysis of the binding capacity of 20 components from Shenqi Jiangtang Granules (SJG) to α-Glucosidase were completed. Ultimately, the binding capacity of these active ingredients was ranked based on the detected Raman Intensity. The compounds with higher binding capacity were Astragaloside IV (Intensity, 138.17), Ginsenoside Rh2 (Intensity, 87.46), Ginsenoside Rg3 (Intensity, 73.92) and Ginsenoside Rh1 (Intensity, 64.37), which all exceeded the binding capacity of the positive drug Acarbose (Intensity, 28.75). Furthermore, this strategy also performed a high detection sensitivity. The limit of detection for the enzyme using 0.1 mg of molecular probe magnetic nanoparticles (MP MNPs) was determined to be no less than 0.375 μg/mL. SERS-PCMP sensor integrating SERS labeling and photocrosslinked molecular probes which offers a fresh perspective for future drug discovery studies. Such as high-throughput drug screening and the exploration of small molecule-target protein interactions in vitro.

Rapid identification of various chemical components in Cinnamomi ramulus by UPLC-Q-Orbitrap-MS

Cinnamomi ramulus (CR) is a common Chinese herbal medicine with a long history. It is often used to treat exogenous wind-cold diseases in clinic, but its chemical compositions remain to be studied. In this study, CR was extracted with 75% ethanol, and UPLC-Q-Orbitrap-MS combined with data post-processing method was used to identify the chemical components in the extract. Through this technology, the components in CR can be separated and accurately identified. A total of 61 compounds were identified, including 14 simple phenylpropanoids, 3 coumarins, 5 lignans, 14 flavonoids, 10 benzoic acids, 8 organic acids, and 7 others. This study confirmed the existence of these compounds in CR and speculated the cleavage pathways of each compound, which enriched the mass spectrometry data and cleavage rules. This study can provide a reference for CR and other research.

Simultaneous quantitation of 15 bioactive components in Yupingfeng granules by LC-MS/MS

Yupingfeng granules (YPFG) is commonly used in the treatment of immunological diseases, inflammations, and pulmonary diseases. Several studies have found that chromones, flavones, and saponins were the major bioactive compounds of YPFG. However, few studies have reported accurate quantification methods of these compounds. This study aimed to establish a simple and rapid method by using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to determine 15 bioactive compounds in YPFG. The experimental parameters including extraction methods, extraction solvents, extraction time, solid-liquid ratio, and LC-MS/MS condition were optimized. The linearity, precision, repeatability, stability, and recovery of the established method were evaluated. The contents of 15 bioactive compounds in seven batches of YPFG samples were analyzed by the established method and the results were compared with the values determined by HPLC. The optimal extraction condition was to extract 0.1 g of YPFG by ultrasound with 50 mL 50% ethanol for 30 min. A Waters ACQUITY UPLCBEH C18 column using the 0.1% formic acid water solution and acetonitrile as mobile phase with a gradient elution was applied to the chromatographic separation. The linearity, precision, repeatability, stability, and recovery of the method were within acceptable ranges. Compared with HPLC analysis methods in Chinese Pharmacopoeia and literature, the established method was faster, simpler, more accurate, and more reliable. The method of simultaneous determination of 15 components in YPFG by LC-MS might provide a basis for the study of the bioactive compounds and the improvement of the quality standard of YPFG.

Combination of in silico prediction and convolutional neural network framework for targeted screening of metabolites from LC-HRMS fingerprints: A case study of "Pericarpium Citri Reticulatae - FructusAurantii"

In this study, a novel approach is introduced, merging in silico prediction with a Convolutional Neural Network (CNN) framework for the targeted screening of in vivo metabolites in Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) fingerprints. Initially, three predictive tools, supplemented by literature, identify potential metabolites for target prototypes derived from Traditional Chinese Medicines (TCMs) or functional foods. Subsequently, a CNN is developed to minimize false positives from CWT-based peak detection. The Extracted Ion Chromatogram (EIC) peaks are then annotated using MS-FINDER across three levels of confidence. This methodology focuses on analyzing the metabolic fingerprints of rats administered with "Pericarpium Citri Reticulatae - Fructus Aurantii" (PCR-FA). Consequently, 384 peaks in positive mode and 282 in negative mode were identified as true peaks of probable metabolites. By contrasting these with "blank serum" data, EIC peaks of adequate intensity were chosen for MS/MS fragment analysis. Ultimately, 14 prototypes (including flavonoids and lactones) and 40 metabolites were precisely linked to their corresponding EIC peaks, thereby providing deeper insight into the pharmacological mechanism. This innovative strategy markedly enhances the chemical coverage in the targeted screening of LC-HRMS metabolic fingerprints.

Exploring the chemical components of Kuanchang-Shu granule and its protective effects of postoperative ileus in rats by regulating AKT/HSP90AA1/eNOS pathway

BACKGROUND

Postoperative ileus (POI) is a common obstruction of intestinal content passage caused by almost all abdominal operations that seriously strokes the quality of life of patients. Kuanchang-Shu granule (KCSG), a classic modified prescription based on "Da-Cheng-Qi Decoction", has obtained satisfactory efficacy in the clinical therapeutics of POI. However, its material basis and holistic molecular mechanism against POI have not been revealed.

METHODS

The chemical ingredients of KCSG were first characterized by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). Subsequently, an integration strategy of the network pharmacology and molecular docking based on above identified ingredients was performed to unveil the potential targets involved in the treatment of KCSG on POI. Finally, intestinal manipulation induced rat POI model was constructed to verify the efficacy and predicted mechanism of KCSG against POI.

RESULTS

In total, 246 ingredients mainly including organic acids, flavonoids, quinones, alkaloids, terpenoids, phenylpropanoids and phenols were identified. 41 essential ingredients, 24 crucial targets as well as 15 relevant signaling pathways were acquired based on network pharmacology analysis. Pharmacodynamic research showed that KCSG treatment could protect intestinal histological damage, promote the recovery of measurement of gastrointestinal transit disorder and inhibit the secretion of myeloperoxidase in the distal ileum tissues. The up-regulated expression of p-AKT and down-regulated expression of p-eNOS and HSP9OAA1 predicted by molecular docking and validated by western blotting showed that AKT/eNOS/HSP90AA1 pathway may be one of the crucial mechanisms that mediates the protective effect of KCSG.

A practical strategy enabling more reliable identification of ginsenosides from Panax quinquefolius flower by dimension-enhanced liquid chromatography/mass spectrometry and quantitative structure-retention relationship-based retention behavior prediction

To accurately identify the metabolites is crucial in a number of research fields, and discovery of new compounds from the natural products can benefit the development of new drugs. However, the preferable phytochemistry or liquid chromatography/mass spectrometry approach is time-/labor-extensive or receives unconvincing identifications. Herein, we presented a strategy, by integrating offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), exclusion list-containing high-definition data-dependent acquisition (HDDDA-EL), and quantitative structure-retention relationship (QSRR) prediction of the retention time (tR), to facilitate the in-depth and more reliable identification of herbal components and thus to discover new compounds more efficiently. Using the saponins in Panax quinquefolius flower (PQF) as a case, high orthogonality (0.79) in separating ginsenosides was enabled by configuring the XBridge Amide and CSH C18 columns. HDDDA-EL could improve the coverage in MS2 acquisition by 2.26 folds compared with HDDDA (2933 VS 1298). Utilizing 106 reference compounds, an accurate QSRR prediction model (R2 = 0.9985 for the training set and R2 = 0.88 for the validation set) was developed based on Gradient Boosting Machine (GBM), by which the predicted tR matching could significantly reduce the isomeric candidates identification for unknown ginsenosides. Isolation and establishment of the structures of two malonylginsenosides by NMR partially verified the practicability of the integral strategy. By these efforts, 421 ginsenosides were identified or tentatively characterized, and 284 thereof were not ever reported from the Panax species. The current strategy is thus powerful in the comprehensive metabolites characterization and rapid discovery of new compounds from the natural products.

Uncovering the molecular mechanisms of Fructus Choerospondiatis against coronary heart disease using network pharmacology analysis and experimental pharmacology

Fructus Choerospondiatis (FC), a Mongolian medicine, was mainly used in Mongolian medical theory for the treatment of coronary heart disease (CHD). Nonetheless, the main components and mechanisms of action of FC in the treatment of coronary artery disease have not been studied clearly.

AIM OF THE STUDY

The aim of this study is to identify the components of FC and analyze the pathways affected by the targets of these components to probe into the potential mechanisms of action of FC on coronary heart disease.

MATERIALS AND METHODS

Identification of compounds in FC employing high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF-MS) method, then further investigate the network pharmacology and molecular docking to obtain potential targets and elucidate the potential mechanism of action of FC in the therapy of CHD. Experimental validation was established to verify the mechanism of FC in vitro.

RESULTS

21 FC components were identified and 65 overlapping targets were gained. In addition, these ingredients regulated AMPK and PPAR signaling pathway by 65 target genes including IL6, AKT1 and PPARg, etc. Molecular docking displayed that the binding ability of the key target PPARg to FC components turned out to be better. Experimental validation proved that FC treatment decreased the expression of PPARg (p < 0.05) compare with model group, which may be involved in the PPAR signaling pathway.

CONCLUSIONS

This study was the first to elucidate the mechanism of action of components of FC for the treatment of CHD using network pharmacology. It alleviated CHD by inhibiting the expression of PPARg to attenuate hypoxia/reoxygenation injury, and the results give a basis for elucidating the molecular mechanism of action of FC for the treatment of coronary heart disease.

A systematic pharmacology-based in vivo study to reveal the effective mechanism of Yupingfeng in asthma treatment

BACKGROUND

The clinical effect of Yupingfeng (YPF) has been confirmed in asthma patients, however, it lacks a study to verify its pharmacological mechanism.

HYPOTHESIS/PURPOSE

To reveal the molecular basis and potential pharmacological mechanism of YPF in the treatment of asthma.

STUDY DESIGN AND METHODS

First, a systems pharmacology-based method integrating pharmacokinetic screening, target prediction, network analyses, GO and KEGG analyses were used for the systematic deciphering of the mechanism of YPF in asthma. Second, differentially expressed genes (DEGs) between asthma patients and healthy controls were identified by GEO2R online tool. Third, based on systems pharmacology and DEGs results, molecular docking was performed utilizing the Discovery Studio 2020 Client version to detect the binding capacity between compounds and targets. Finally, ovalbumin (OVA)-challenged C57BL/6 mice were treated with YPF or its effective compound to assess the predictions.

RESULTS

A total of 35 active compounds were filtered out, with 87 potential targets being identified for further analysis after target fishing and matching. Quercetin, kaempferol, and wogonin were identified as the main ingredients in YPF. The signaling pathways of phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT), tumor necrosis factor (TNF) and IL-17 were identified as the top signaling pathways in KEGG enrichment analysis. GEO2R tools of NCBI discovered five DEGs that overlapped with the therapeutic targets of YPF. Wogonin was proven to be the top active compound in YPF through the results of molecular docking. In vivo experiments indicated that YPF and wogonin significantly attenuated airway resistance and lung inflammation by decreasing the levels of inflammatory cytokines and key factors in PI3K/AKT, IL-17, and TNF signaling pathways.

CONCLUSIONS

YPF and its main active compound wogonin may exert some therapeutic effects on asthma inflammation through multiple molecular targets and signaling pathways including PI3K/AKT, IL-17 and TNF-α.

Bioinformatic assay reveal the potential mechanism of Guizhi-Shaoyao-Zhimu decoction against rheumatoid arthritis and mild-to-moderate COVID-19

BACKGROUND AND OBJECTIVE

Patients with rheumatoid arthritis (RA) are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than healthy population, but there is still no therapeutic strategy available for RA patients with corona virus disease 2019 (COVID-19). Guizhi-Shaoyao-Zhimu decoction (GSZD), Chinese ancient experience decoction, has a significant effect on the treatment of Rheumatism and gout. To prevent RA patients with mild-to-moderate COVID-19 from developing into severe COVID-19, this study explored the potential possibility and mechanism of GSZD in the treatment of this population.

METHODS

In this study, we used bioinformatic approaches to explore common pharmacological targets and signaling pathways between RA and mild-to-moderate COVID-19, and to assess the potential mechanisms of in the treatment of patients with both diseases. Beside, molecular docking was used to explore the molecular interactions between GSZD and SARS-CoV-2 related proteins.

RESULTS

Results showed that 1183 common targets were found in mild-to-moderate COVID-19 and RA, of which TNF was the most critical target. The crosstalk signaling pathways of the two diseases focused on innate immunity and T cells pathways. In addition, GSZD intervened in RA and mild-to-moderate COVID-19 mainly by regulating inflammation-related signaling pathways and oxidative stress. Twenty hub compounds in GSZD exhibited good binding potential to SARS-CoV-2 spike (S) protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), papain-like protease (PLpro) and human angiotensin-converting enzyme 2 (ACE2), thereby intervening in viral infection, replication and transcription.

CONCLUSIONS

This finding provides a therapeutic option for RA patients against mild-to-moderate COVID-19, but further clinical validation is still needed.

Diuretics in Different Samples: Update on the Pretreatment and Analysis Techniques

Diuretics are drugs that promote the excretion of water and electrolytes in the body and produce diuretic effects. Clinically, they are often used in the treatment of edema caused by various reasons and hypertension. In sports, diuretics are banned by the World Anti-Doping Agency (WADA). Therefore, in order to monitor blood drug concentration, identify drug quality and maintain the fairness of sports competition, accurate, rapid, highly selective and sensitive detection methods are essential. This review provides a comprehensive summary of the pretreatment and detection of diuretics in various samples since 2015. Commonly used techniques to extract diuretics include liquid-liquid extraction, liquid-phase microextraction, solid-phase extraction, solid-phase microextraction, among others. Determination methods include methods based on liquid chromatography, fluorescent spectroscopy, electrochemical sensor method, capillary electrophoresis and so on. The advantages and disadvantages of various pretreatment and analytical techniques are elaborated. In addition, future development prospects of these techniques are discussed.

Advances in the chemical constituents, pharmacological properties and clinical applications of TCM formula Yupingfeng San

Yupingfeng San (YPFS) is a famous and commonly used traditional Chinese medicine (TCM) formula for the treatment of chronic obstructive pulmonary disease, asthma, respiratory tract infections, and pneumonia in China. It is composed of three Chinese herbs, including Astragali Radix, Atractylodis Macrocephalae Rhizoma and Saposhnikoviae Radix. In this review, the relevant references on YPFS were searched in the Web of Science, PubMed, China National Knowledge Infrastructure (CNKI), and other databases. Literatures published from 2000 to 2022 were screened and summarized. The constituents in YPFS could be classified into nine groups according to their structures, including flavonoids, saponins, essential oils, coumarins, lactones, amino acids, organic acids, saccharides, chromones and others. The importance of chemical constituents in YPFS were demonstrated for specific pathological processes including immunoregulatory, anti-inflammatory, anti-tumor and pulmonary diseases. This article systematically reviewed the up-to-date information on its chemical compositions, pharmacology and safety, that could be used as essential data and reference for clinical applications of YPFS.

Deciphering the Mechanism of YuPingFeng Granules in Treating Pneumonia: A Network Pharmacology and Molecular Docking Study

Objective

YuPingFeng Granules (YPFGs) is an herbal formula clinically used in China for more than 100 years to treat pneumonia. Nevertheless, the mechanism of YPFG in pneumonia treatment has not been established. This network pharmacology-based strategy has been performed to elucidate active compounds as well as mechanisms of YPFG in pneumonia treatment.

Methods

First, active compounds of YPFG were identified in the traditional Chinese medicine systems pharmacology (TCMSP) database, and then the targets related to the active compounds were obtained from TCMSP and Swiss Target Prediction databases. Next, using DisGeNET, DrugBank, and GeneCards databases, we got therapeutic targets of pneumonia and common targets between pneumonia targets and YPFG. After that, a protein-protein interaction (PPI) network of pneumonia composed of common targets was built to analyze the interactions among these targets, which focused on screening for hub targets by topology. Then, online software and the ClusterProfiler package were utilized for the enrichment analysis of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data. Finally, the visualization software of Autodock was used for molecular docking among the hub target proteins.

Results

10 hub genes were selected by comparing the GO and KEGG functions of pneumonia targets with those of the common targets of YPFG and pneumonia. By using molecular docking technology, a total of 3 active ingredients have been verified as being able to combine closely with 6 hub targets and contribute to their therapeutic effects.

Conclusion

This research explored the multigene pharmacological mechanism of action of YPFG against pneumonia through network pharmacology. The findings present new ideas for studying the mechanism of action of Chinese medicine against pneumonia caused by bacteria.

A new strategy for the rapid identification and validation of direct toxicity targets of psoralen-induced hepatotoxicity

The interaction between small-molecule compounds of traditional Chinese medicine and their direct targets is the molecular initiation event, which is the key factor for toxicity efficacy. Psoralen, an active component of Fructus Psoraleae, is toxic to the liver and has various pharmacological properties. Although the mechanism of psoralen-induced hepatotoxicity has been studied, the direct target of psoralen remains unclear. Thus, the aim of this study was to discover direct targets of psoralen. To this end, we initially used proteomics based on drug affinity responsive target stability (DARTS) technology to identify the direct targets of psoralen. Next, we used surface plasmon resonance (SPR) analysis and verified the affinity effect of the 'component-target protein'. This method combines molecular docking technology to explore binding sites between small molecules and proteins. SPR and molecular docking confirmed that psoralen and tyrosine-protein kinase ABL1 could be stably combined. Based on the above experimental results, ABL1 is a potential direct target of psoralen-induced hepatotoxicity. Finally, the targets Nrf2 and mTOR, which are closely related to the hepatotoxicity caused by psoralen, were predicted by integrating proteomics and network pharmacology. The direct target ABL1 is located upstream of Nrf2 and mTOR, Nrf2 can influence the expression of mTOR by affecting the level of reactive oxygen species. Immunofluorescence experiments and western blot results showed that psoralen could affect ROS levels and downstream Nrf2 and mTOR protein changes, whereas the ABL1 inhibitor imatinib and ABL1 agonist DPH could enhance or inhibit this effect. In summary, we speculated that when psoralen causes hepatotoxicity, it acts on the direct target ABL1, resulting in a decrease in Nrf2 expression, an increase in ROS levels and a reduction in mTOR expression, which may cause cell death. We developed a new strategy for predicting and validating the direct targets of psoralen. This strategy identified the toxic target, ABL1, and the potential toxic mechanism of psoralen.

Multivariate Statistical Analysis of Metabolites in Anisodus tanguticus (Maxim.) Pascher to Determine Geographical Origins and Network Pharmacology

Anisodus tanguticus (Maxim.) Pascher, has been used for the treatment of septic shock, analgesia, motion sickness, and anesthesia in traditional Tibetan medicine for 2,000 years. However, the chemical metabolites and geographical traceability and their network pharmacology are still unknown. A total of 71 samples of A. tanguticus were analyzed by Ultra-Performance Liquid Chromatography Q-Exactive Mass Spectrometer in combination with chemometrics developed for the discrimination of A. tanguticus from different geographical origins. Then, network pharmacology analysis was used to integrate the information of the differential metabolite network to explore the mechanism of pharmacological activity. In this study, 29 metabolites were identified, including tropane alkaloids, hydroxycinnamic acid amides and coumarins. Principal component analysis (PCA) explained 49.5% of the total variance, and orthogonal partial least-squares discriminant analysis (OPLS-DA) showed good discrimination (R2Y = 0.921 and Q2 = 0.839) for A. tanguticus samples. Nine differential metabolites accountable for such variations were identified through variable importance in the projection (VIP). Through network pharmacology, 19 components and 20 pathways were constructed and predicted for the pharmacological activity of A. tanguticus. These results confirmed that this method is accurate and effective for the geographic classification of A. tanguticus, and the integrated strategy of metabolomics and network pharmacology can explain well the "multicomponent--multitarget" mechanism of A. tanguticus.