A Novel Strategy for Screening Active Components in Cistanche tubulosa Based on Spectrum-Effect Relationship Analysis and Network Pharmacology

Integrated UHPLC-mS/mS analysis, spectrum-effect relationship, and molecular docking to study the antidiabetic components of Cyclocarya paliurus

The leaves of Cyclocarya paliurus (Batal) Iljinsk., a plant native to China that has long been used in traditional Chinese medicine to treat diabetes. It remains to be determined what chemical constituents are responsible for this effect. The aim of this study was to identify the antidiabetic components of C. paliurus using the spectrum-effect relationship and confirmed using molecular docking. The components of C. paliurus were detected using ultra-high-performance liquid chromatography mass spectrometry/mass spectrometry (UHPLC-MS/MS) and ultra-high-performance liquid chromatography-diode array detector (UHPLC-DAD). C. paliurus could significantly reduce glycosylated haemoglobin, blood glucose levels and blood lipid profile. Esculetin, shikimic acid, isoquercitrin, quercitrin, kaempferol-3-O-rhamnoside, tricin, and pterocaryoside A were determined to be the main antidiabetic components of C. paliurus. Results revealed that the antidiabetic effect of C. paliurus was due to the combination of multiple chemical components. The method developed is valuable for identifying the active ingredients of this plant species.

Screening Antioxidant Components in Yiwei Decoction Using Spectrum-Effect Relationship and Network Pharmacology

Yiwei decoction (YWD) is a classic prescription with the function of nourishing stomach yin. In this study, the effective components of antioxidant activity of YWD and its possible mechanism were discussed from the point of view of spectral effect relationship and network pharmacology. Firstly, the fingerprints of 10 batches of YWD were established by UPLC-PDA technique, and the 1,1-diphenyl-2-picryl-hydrazyl radical (DPPH) scavenging rate and total antioxidant capacity (T-AOC) were used as the indicators for antioxidant activity in vitro. Then, the spectral effect relationship between the fingerprint profiles and antioxidant capacity was analyzed through grey relational analysis (GRA) and orthogonal projections to latent structures (OPLS). In addition, network pharmacology was employed to predict the potential mechanisms of YWD in the treatment of antioxidant-related diseases. The spectrum-effect relationship indicated that three common peaks were likely to be the most decisive active components, identified as verbascoside, psoralen, and vitexin, respectively. Based on network pharmacology analysis, a total of 83 target genes shared by the active components and antioxidant-related diseases were collected. AKT1, HSP90AA1, SRC, CASP3, and MTOR were closely related to antioxidant therapy and considered as core therapeutic targets. The potential mechanisms of YWD were obtained through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, molecular docking simulations were conducted to evaluate the binding activities between the core therapeutic targets and corresponding compounds. The excellent core protein-compound complexes obtained by molecular docking were simulated by molecular dynamics simulation. The results showed that the active compounds had good binding ability with the selected targets. This study successfully identified the effective components of YWD and predicted the potential targets and pathways, which provided a new idea for the application of YWD in the treatment of antioxidant stress in the future. In addition, the potential active components provide valuable implications for drug screening of related diseases.

Differential proteins from EVs identification based on tandem mass tags analysis and effect of Treg-derived EVs on T-lymphocytes in COPD patients

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a widespread respiratory disease. This study examines extracellular vesicles (EVs) and proteins contained in EVs in COPD.

METHODS

Blood samples were collected from 40 COPD patients and 10 health controls. Cytokines including IFN-γ, TNF-α, IL-1β, IL-6, IL-8, and IL-17, were measured by ELISA. Small EVs samples were extracted from plasma and identified by transmission electron microscope (TEM), nanoparticle tracking analysis (NTA), and Western blot. Protein components contained in EVs were analyzed by Tandem Mass Tags (TMT) to identify differential proteins. Treg-derived EV was extracted and added to isolated CD8+, Treg, and Th17 subsets to assess its effect on T-lymphocytes.

RESULTS

ELISA revealed higher levels of all cytokines and flow cytometry suggested a higher proportion of Treg and Th17 cells in COPD patients. After identification, TMT analysis identified 207 unique protein components, including five potential COPD biomarkers: BTRC, TRIM28, CD209, NCOA3, and SSR3. Flow cytometry revealed that Treg-derived EVs inhibited differentiation into CD8+, CD4+, and Th17 cells.

CONCLUSION

The study shows that cytokines, T-lymphocyte subsets differences in COPD and Treg-derived EVs influence T-lymphocyte differentiation. Identified biomarkers may assist in understanding COPD pathogenesis, prognosis, and therapy. The study contributes to COPD biomarker research.

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.