Network pharmacology combined with GEO database identifying the mechanisms and molecular targets of Polygoni Cuspidati Rhizoma on Peri-implants

Network pharmacology and bioinformatic integrative analysis reveals candidate gene targets and potential therapeutic of East Kalimantan propolis against hepatocellular carcinoma

Introduction

Hepatocellular Carcinoma (HCC) is commonly treated with surgery, liver transplantation, and chemotherapy, but recurrence and metastasis remain challenges. Natural complementary therapies like propolis, known for its hepatoprotective properties, are gaining interest due to limited efficacy and toxicity of conventional chemotherapy. This study aims to identify core targets for HCC, assess the therapeutic potential of East Kalimantan propolis (EKP) from stingless bees, and analyze the molecular interactions.

Methods

EKP compounds were analyzed using target prediction tools related to HCC, alongside clinical data from the Gene Expression Omnibus (GEO) database, to identify overlapping genes with clinical relevance. The selected genes were then subjected to protein-protein interaction (PPI), GO and KEGG enrichment, immunohistochemical comparison and survival analysis to identify potential core targets and related pathways for HCC therapy. Furthermore, molecular docking and dynamics were conducted to verify the molecular interactions and stability of EKP compounds with targets.

Results

108 genes have been selected as HCC potential targets, which mostly associated with MicroRNAs in cancer, chemical carcinogenesis, and viral carcinogenesis pathways. These targets were obtained by overlapping genes from GEO clinical databases and target predictors. PPI network analysis revealed 4 main targets of propolis in HCC. Furthermore, differential expression genes, survival analysis, and Immunohistochemical analysis from databases suggested that AKR1C3 and MAPK1 promote HCC progression and shorten survival rate of HCC patients. Molecular docking and dynamic studies confirmed strong binding affinity and stability of Baicalein, Chrysin, Quercetin, and Myricetin with receptor targets within simulation time.

Conclusions

This study provides insight into the mechanism of action of EKP on HCC and identifies AKR1C3 and MAPK1 as candidate target treatments for future drug development.

Nerolidol rescues hippocampal injury of diabetic rats through inhibiting NLRP3 inflammasome and regulation of MAPK/AKT pathway

Despite the observation of diabetes-induced brain tissue damage and impaired learning and memory, the underlying mechanism of damage remains elusive, and effective, targeted therapeutics are lacking. Notably, the NLRP3 inflammasome is highly expressed in the hippocampus of diabetic individuals. Nerolidol, a naturally occurring compound with anti-inflammatory and antioxidant properties, has been identified as a potential therapeutic option for metabolic disorders. However, the ameliorative capacity of nerolidol on diabetic hippocampal injury and its underlying mechanism remain unclear. Network pharmacology and molecular docking was used to predict the signaling pathways and therapeutic targets of nerolidol for the treatment of diabetes. Then established a diabetic rat model using streptozotocin (STZ) combined with a high-fat diet and nerolidol was administered. Morris water maze to assess spatial learning memory capacity. Hematoxylin and eosin and Nissl staining was used to detect neuronal damage in the diabetic hippocampus. Transmission electron microscopy was used to detect the extent of damage to mitochondria, endoplasmic reticulum (ER) and synapses. Immunofluorescence was used to detect GFAP, IBA1, and NLRP3 expression in the hippocampus. Western blot was used to detect apoptosis (Bcl-2, BAX, and Cleaved-Caspase-3); synapses (postsynaptic densifying protein 95, SYN1, and Synaptophysin); mitochondria (DRP1, OPA1, MFN1, and MFN2); ER (GRP78, ATF6, CHOP, and caspase-12); NLRP3 inflammasome (NLRP3, ASC, and caspase-1); inflammatory cytokines (IL-18, IL-1β, and TNF-α); AKT (P-AKT); and mitogen-activated protein kinase (MAPK) pathway (P-ERK, P-p38, and P-JNK) related protein expression. Network pharmacology showed that nerolidol's possible mechanisms for treating diabetes are the MAPK/AKT pathway and anti-inflammatory effects. Animal experiments demonstrated that nerolidol could improve blood glucose, blood lipids, and hippocampal neuronal damage in diabetic rats. Furthermore, nerolidol could improve synaptic, mitochondrial, and ER damage in the hippocampal ultrastructure of diabetic rats by potentially affecting synaptic, mitochondrial, and ER-related proteins. Further studies revealed that nerolidol decreased neuroinflammation, NLRP3 and inflammatory factor expression in hippocampal tissue while also decreasing MAPK pathway expression and enhancing AKT pathway expression. However, nerolidol improves hippocampal damage in diabetic rats cannot be shown to improve cognitive function. In conclusion, our study reveals for the first time that nerolidol can ameliorate hippocampal damage, neuroinflammation, synaptic, ER, and mitochondrial damage in diabetic rats. Furthermore, we suggest that nerolidol may inhibit NLRP3 inflammasome and affected the expression of MAPK and AKT. These findings provide a new experimental basis for the use of nerolidol to ameliorate diabetes-induced brain tissue damage and the associated disease.

Exploration of compatibility rules and discovery of active ingredients in TCM formulas by network pharmacology

Network pharmacology is an interdisciplinary field that utilizes computer science, technology, and biological networks to investigate the intricate interplay among compounds/ingredients, targets, and diseases. Within the realm of traditional Chinese medicine (TCM), network pharmacology serves as a scientific approach to elucidate the compatibility relationships and underlying mechanisms of action in TCM formulas. It facilitates the identification of potential active ingredients within these formulas, providing a comprehensive understanding of their holistic and systematic nature, which aligns with the holistic principles inherent in TCM theory. TCM formulas exhibit complexity due to their multi-component characteristic, involving diverse targets and pathways. Consequently, investigating their material basis and mechanisms becomes challenging. Network pharmacology has emerged as a valuable approach in TCM formula research, leveraging its holistic and systematic advantages. The manuscript aims to provide an overview of the application of network pharmacology in studying TCM formula compatibility rules and explore future research directions. Specifically, we focus on how network pharmacology aids in interpreting TCM pharmacological theories and understanding formula compositions. Additionally, we elucidate the process of utilizing network pharmacology to identify active ingredients within TCM formulas. These findings not only offer novel research models and perspectives for integrating network pharmacology with TCM theory but also present new methodologies for investigating TCM formula compatibility. All in all, network pharmacology has become an indispensable and crucial tool in advancing TCM formula research.

Uncovering the anti-breast cancer activity potential of east Kalimantan propolis by In vitro and bioinformatics analysis

Numerous side effects of breast cancer drugs have prompted researchers to explore more into new therapeutic approaches derived from natural substances. In this context, our study focused on uncovering the potential of East Kalimantan propolis from Trigona apicalis for breast cancer treatment including the underlying mechanisms through bioinformatics approached. We conducted integrated in vitro and bioinformatics analysis of network pharmacology, molecular docking, molecular dynamics and MM-GBSA analysis. Initially, in vitro cytotoxic assay demonstrated the anti-breast cancer activity potential of ethanol extract of East Kalimantan propolis, particularly its ethyl acetate fraction, which exhibited similar activity to doxorubicin, as indicated by their IC50 value. This study revealed eight propolis compounds, consisting of flavonoids and phenolic acids, in East Kalimantan propolis. By integrating microarray datasets (GSE29431, GSE36295, and GSE42568) analysis with potential targets derived from propolis compounds, 39 shared target genes were identified. Subsequently, GO and KEGG pathway, protein-protein interaction (PPI) network, core hub genes and gene expression analysis revealed three major targets, namely, PTGS2, CXCL2, and MMP9. Among them, only MMP9 was highly expressed in breast cancer than normal. Moreover, molecular docking revealed the six of propolis compounds which exhibited pronounced binding affinity towards MMP-9, better than marimastat as control drug. Dynamic simulation confirmed the stability of chrysin and quercetin as best compounds. Additionally, MM-GBSA analysis revealed a relative binding energy for chrysin (-25.6403 kcal/mol) that was comparable to marimastat (-27.3827 kcal/mol). In conclusion, this study reveals how East Kalimantan Propolis affect breast cancer and emphasizes MMP9 as a key target for future therapeutics.

Network pharmacological study and in vitro studies validation-Molecular dynamics simulation of Cistanche deserticola in promoting periodontitis and bone remodeling

OBJECTIVE

Periodontitis is a chronic infectious disease, characterized by loss of alveolar bone and supporting tissues. Cistanche deserticola(Cd), a local medicinal herb in Xinjiang, possesses favorable biological characteristics and potential applications. Our aim is to investigate the remodeling properties of Cd extract and elucidate the specific mechanisms underlying its therapeutic effects on periodontitis, by employing a combination of basic experimental and network pharmacology approaches.

METHODS

Firstly, UHPLC-QTOF-MS analysis was conducted on Cd extract to identify its main components, with several compounds were identified by standard. Subsequently, in vitro studies were performed using the Cd extract on MC3T3-E1 cells. Cell proliferation viability was assessed using CCK-8 and apoptosis assays, while ALP and ARS staining and quantitative experiments, qRT-PCR, and Western blot assays were employed to evaluate the osteogenic differentiation capability. Network pharmacology analysis was then carried out using the identified compounds to establish a database of Cd components and targets, along with a database of periodontitis. The intersection of these databases revealed the network relationship between Cd components-mapped genes-signaling pathways. KEGG/GO pathway analysis of the targets was performed to filter potential enriched pathways. PPI/CytoHubba protein interaction network analysis was utilized to identify hub genes. Molecular docking and molecular dynamics simulations were employed to analyze the docking and interaction between core gene and Cd components.

RESULTS

We detected 38 major components in the Cd extract, with Echinacoside, Acteoside, Tubuloside A, and Cistanoside A undergoing standard substance verification. In vitro studies indicated that the Cd, at concentrations below 100 μg/ mL, did not affect cell proliferation and inhibited apoptosis. Osteogenesis assays demonstrated that Cd at concentrations of 1 μg/ mL, 10 μg/ mL, and 100 μg/ mL significantly promoted the osteogenic differentiation ability of MC3T3-E1 cells. It also notably upregulated the mRNA and protein levels of Alp, Bmp2, Runx2, and Opn, and the optimal concentration was 10 μg/mL. Network pharmacology results revealed the network relationship between Cd's components, crossed targets and signaling pathways. Combined with KEGG/GO pathway analysis and PPI/CytoHubba protein interaction network analysis. The key pathway and hub genes of Cd regulating periodontitis are both related to hypoxia pathway and HIF-1α. Molecular docking results showed a strong binding affinity between Cd compounds and hub genes, and molecular dynamics simulation results indicated the stability of the complexes formed between HIF-1α and several Cd compounds.

CONCLUSION

Cistanche deserticola exhibits a notable capacity to promote bone regeneration, and its mechanism of action in regulating periodontitis is associated with the hypoxia signaling pathway. HIF-1α may serve as a potential core gene. Future research will focus on exploring the mechanism of Cd in intervene periodontitis and promoting bone remodeling in hypoxic environment.

Mechanochemical Properties of Mucoadhesive Tablets Based on PVP/HPβCD Electrospun Nanofibers as Local Delivery of Polygoni cuspidati Extract for Treating Oral Infections

This study investigated the ability of PVP/HPβCD-based electrospun nanofibers to enhance the dissolution rate of poorly soluble polydatin and resveratrol, the main active components of Polygoni cuspidati extract. To make a solid unit dosage form that would be easier to administer, extract-loaded nanofibers were ground. SEM examination was used to analyze the nanostructure of the fibers, and the results of the cross-section of the tablets showed that they had maintained their fibrous structure. The release of the active compounds (polydatin and resveratrol) in the mucoadhesive tablets was complete and prolonged in time. Additionally, the possibility of staying on the mucosa for a prolonged time has also been proven for both tablets from PVP/HPβCD-based nanofibers and powder. The appropriate physicochemical properties of the tablets, along with the proven antioxidant, anti-inflammatory, and antibacterial properties of P. cuspidati extract, highlight the particular benefits of the mucoadhesive formulation for use as a drug delivery system for periodontal diseases.

Bioinformatics Analysis of the Prognostic Significance of VPS16 in Hepatocellular Carcinoma and Its Role in Drug Screening

Background

Vacuolar protein sorting 16 (VPS16) overexpression was recently considered related to cancer growth and drug resistance; however, little is known about whether VPS16 plays a vital role in liver hepatocellular carcinoma (LIHC).

Methods

The TIMER2 online database was used to analyze the expression of VPS16 in pancancer, and the Xena Browser was used to explore the correlation between VPS16 expression level and survival time. R language was used to test the survival data of 374 LIHC cases in the TCGA database. DESeq2 was used for differentially expressed gene (DEG) analysis. The HPA database was used to verify the expression level of VPS16 in LIHC. The clusterProfiler package was used to analyze functions and related signaling pathways via GO/KEGG enrichment analysis. Drug sensitivity analysis and molecular docking technology were used to screen the most sensitive drugs targeting VPS16 molecules.

Results

Pancancer analysis showed that VPS16 was highly expressed in various tumors, especially in LIHC. With the increase in the T stage and grade of LIHC, the expression level of VPS16 was also increased. The expression of VPS16 was negatively correlated with the overall survival of LIHC patients. The stage can be used as an independent prognostic factor. A total of 63 sensitive drugs were found, and 19 drugs were displaying strong molecular binding energy with VPS16.

Conclusion

VPS16 may be a potential biomarker for the diagnosis and prognosis of LIHC. Drugs targeting VPS16 may be used in the treatment of LIHC in the future.