Network Pharmacological Screening of Herbal Monomers that Regulate Apoptosis-Associated Genes in Acute Pancreatitis

Deciphering the Underlying Mechanisms of Formula Le-Cao-Shi Against Liver Injuries by Integrating Network Pharmacology, Metabonomics, and Experimental Validation

Le-Cao-Shi (LCS) has long been used as a folk traditional Chinese medicine formula against liver injuries, whereas its pharmacological mechanisms remain elusive. Our study aims to investigate the underlying mechanism of LCS in treating liver injuries via integrated network pharmacology, metabonomics, and experimental validation. By network pharmacology, 57 compounds were screened as candidate compounds based on ADME parameters from the LCS compound bank (213 compounds collected from the literature of three single herbs). According to online compound–target databases, the aforementioned candidate compounds were predicted to target 87 potential targets related to liver injuries. More than 15 pathways connected with these potential targets were considered vital pathways in collectively modulating liver injuries, which were found to be relevant to cancer, xenobiotic metabolism by cytochrome P450 enzymes, bile secretion, inflammation, and antioxidation. Metabonomics analysis by using the supernatant of the rat liver homogenate with UPLC-Q-TOF/MS demonstrated that 18 potential biomarkers could be regulated by LCS, which was closely related to linoleic acid metabolism, glutathione metabolism, cysteine and methionine metabolism, and glycerophospholipid metabolism pathways. Linoleic acid metabolism and glutathione metabolism pathways were two key common pathways in both network pharmacology and metabonomics analysis. In ELISA experiments with the CCl₄-induced rat liver injury model, LCS was found to significantly reduce the levels of inflammatory parameters, decrease liver malondialdehyde (MDA) levels, and enhance the activities of hepatic antioxidant enzymes, which validated that LCS could inhibit liver injuries through anti-inflammatory property and by suppressing lipid peroxidation and improving the antioxidant defense system. Our work could provide new insights into the underlying pharmacological mechanisms of LCS against liver injuries, which is beneficial for its further investigation and modernization.

The underlying mechanisms of anti-hepatitis B effects of formula Le-Cao-Shi and its single herbs by network pharmacology and gut microbiota analysis

Formula Le-Cao-Shi (LCS), a traditional Chinese medicine (TCM), has been used as folk remedy for treating hepatitis B for a long time. In our previous study, the anti-hepatitis B effects of LCS have been verified. In the present study, the anti-hepatitis B activities of LCS and its three single herbs were investigated in vitro by HepG2.2.15 cellular model, and the mechanisms against hepatitis B were deciphered via network pharmacology and gut microbiota analysis. By network pharmacology method, twelve key compounds that played a vital role in LCS were filtered from 213 ingredients. The targets RORA, CDK2, RELA, AKT1, IKBKG, PRKCβ and CASP3 were directly related to hepatitis B pathway, which indicated that LCS could exert anti-hepatitis B effect by co-regulating cell cycle and inflammatory pathways. The interactions between candidate compounds and target proteins that were directly involved in hepatitis B pathway were validated by molecular docking simulation and RT-PCR. By gut microbiota analysis, it was revealed that LCS could alter the disordered microbial composition in the infected ducks towards normal, especially the restoration of three key strains, namely Streptococcus alactolyticus, Enterococcus cecorum and Bacteroides fragilis. The above findings could provide a scientific basis for further development and utilization of LCS against hepatitis B.

Network pharmacology study on the active components of Pterocypsela elata and the mechanism of their effect against cerebral ischemia

Objective

The aim of this study was to identify the active anti-ischemic components of Pterocypsela elata (P. elata) using a network pharmacology approach to construct an effective component anti-cerebral ischemic target network and systematically analyze this medicinal material.

Methods

Pharmacological studies have shown that P. elata has an obvious effect against cerebral ischemia. To identify the potential targets, 14 components of P. elata were docked to each structural element of the targets in the DRAR-CPI database by reverse docking technology. We then compared the identified potential targets with FDA-approved targets for stroke/cerebral infarction treatment in the DrugBank database and identified the active components of P. elata and their potential targets for stroke/cerebral infarction treatment. The active component-target networks were constructed using Cytoscape 3.5.1 software. The target protein-protein interactions were analyzed using the STRING database. KEGG pathway analysis and gene ontology (GO) enrichment analysis were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID).

Results

There were 14 active components identified from P. elata and 21 potential targets identified for cerebral ischemia treatment, including carbonic anhydrase 2, ribosyldihydronicotinamide dehydrogenase, cholinesterase, and glutathione S-transferase P. The main involved pathways include metabolic pathways, complement and coagulation cascades and steroid hormone biosynthesis.

Conclusion

Through a network pharmacology approach, we predicted the active components of P. elata and their potential targets for cerebral ischemia treatment. Our results provide new perspectives and clues for further studies on the anti-cerebral ischemia mechanism of P. elata.

Early Prediction of Persistent Organ Failure by Circulating Endothelial Progenitor Cells in Patients With Acute Pancreatitis

INTRODUCTION

Increased circulating endothelial progenitor cells (cEPC) have been observed in patients with vascular injury associated with sepsis and acute lung injury. However, a role for cEPC in severe acute pancreatitis (SAP) remains unclear. We therefore conducted a prospective study to study whether the quantities of cEPC can predict persistent organ failure (POF) in patients with predicted SAP.

METHODS

A total of 42 predicted SAP patients who were admitted within 24 h after symptom onset and 10 healthy control subjects were enrolled in our study. The proportions of cEPC were analyzed based on flow cytometry simultaneously. Vascular endothelial growth factor (VEGF) levels were measured by enzyme-linked immunosorbent assay.

RESULTS

The percentage of cEPC was significantly higher in patients with predicted SAP compared with healthy controls. Similarly, the levels of VEGF in peripheral blood were also significantly higher in predicted SAP patients than in the controls. Notably, patients with POF had lower proportion of cEPC compared with patients with transient organ failure (TOF). In contrast, patients with POF had a significantly higher level of VEGF compared with TOF. Of note, the percentages of cEPC were significantly inversely correlated with disease severity scores. More importantly, cEPC showed an excellent discriminative power for predicting POF among predicted SAP patients, whereas plasma VEGF and disease severity scores showed moderate accuracy in predicting future POF.

CONCLUSIONS

Peripheral EPC as a novel biomarker is elevated and may aid to predict the development of POF in patients with predicted SAP.

Network pharmacology-based prediction of the active ingredients, potential targets, and signaling pathways in compound Lian-Ge granules for treatment of diabetes

AIMS

Compound Lian-Ge granules (CLGGs) is a traditional Chinese medicine preparation with good hypoglycemic effect and health function. This study was to predict its active ingredients, potential targets, signaling pathways, and investigate its mechanism of "ingredient-targets-pathways."

METHODS

Pharmacodynamics studies on diabetic rats showed that CLGGs had an obvious hypoglycemic effect. On this basis, 27 hypoglycemic active ingredients were screened out. Their targets were confirmed by comparing with these hypoglycemic targets in PharmMapper and DrugBank databases via reversed pharmacophore matching approach. The relationships between ingredients and targets were revealed by comparing data in the String database. A network of "ingredient-target-passageway" was constructed.

RESULTS

Studies showed that CLGGs had 24 active ingredients, ie, berberine, puerarin, danshinolic acid A, and sinigrin, etc. These ingredients involved nine targets, ie, insulin-like growth factor 1 receptor, insulin-degrading enzyme, ɑ-amylase, and so on, and 111 metabolic pathways, eg, hypoxia-inducible factor 1 signaling pathway, PI3K-Akt signaling pathway, mammalian target of rapamycin signaling pathway, and FoxO signaling pathway.

CONCLUSION

Using network pharmacology methods, this study predicted the hypoglycemic active ingredients in CLGGs and revealed their targets, and provided a clue for further exploration of the hypoglycemic mechanism of CLGGs.