Exploring the mechanism of aidi injection for lung cancer by network pharmacology approach and molecular docking validation

Chemistry of Bairui granules and its mechanisms in the protective effect against methotrexate-induced liver injury

BACKGROUND

Bairui granules (BRKL), a traditional Chinese medicine preparation, possess a range of pharmacological effects. However, its impact on methotrexate (MTX)-induced liver damage remains unexplored.

PURPOSE

The present work focused on investigating the potential protection of BRKL on MTX-induced liver damage, along with its potential active ingredients and underlying mechanisms.

METHODS

We evaluated the hepatoprotective activities of BRKL in liver-damaged Wistar rats induced by intraperitoneal MTX injection, observing the liver's morphological and pathological features. Additionally, we measured serum ALT, AST, and LDH levels using kits. Ultra High-Performance Liquid Chromatography-Q-Exactive Orbitrap Mass Spectrometry (UHPLC-Q-Exactive Orbitrap MS) analyzed BRKL composition, and network pharmacology strategy predicted and analyzed BRKL's targets and pathways. Thereafter, we conducted molecular docking for analyzing affinity of bioactive ingredients for targets with Autodock. At last, results were verified through in vitro experiments.

RESULTS

The animal experiments revealed the significant protection of BRKL against MTX-mediated rat liver damage. A total of 64 major chemical constituents were identified in BRKL by UHPLC-Q-Exactive Orbitrap MS. We then applied the network-based pharmacological strategy to clarify BRKL's molecular mechanism on liver damage based on the identified components. The targets EGFR, SRC, PIK3R1, AKT1, and ESR1, as well as compounds isorhamnetin 3,7-O-diglucoside, β-ecdysone, chrysoeriol, apigenin, and diosmetin, may play pivotal roles in treating MTX-mediated liver damage. According to our in vitro experiments, isorhamnetin 3,7-O-diglucoside may exert its liver-protective effect via AKT/NF-κB pathway.

CONCLUSION

BRKL protected against MTX-mediated liver injury, and the bioactive ingredients, key pathways, and liver injury-related molecular targets have been identified. These findings provide new insights into using BRKL in treating liver damage and propose a feasible approach to exploring phytomedicine's chemical and pharmacological foundation.

Exploring the mechanism of Semen Strychni in treating amyotrophic lateral sclerosis based on network pharmacology

Semen Strychni (SS), known as an agonist of central nervous system, is a traditional herb widely used in treating amyotrophic lateral sclerosis (ALS) in small doses to relieve muscle weakness and improve muscle strength. However, the potential mechanisms and the main components of SS in treating ALS remain unclear. To explore the underlying mechanism of SS in treating ALS based on network pharmacology and molecular docking. The active components of SS were obtained using TCMSP, Herb, ETCM, and BATMAN-TCM. The targets of SS were gained from PharmMapper. The targets of ALS were searched on Genecards, Drugbank, DisGeNET, OMIM, TTD and GEO database. After obtaining the coincidence targets, we submitted them to the STRING database to build a protein-protein interaction network. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed subsequently. The active components and targets were further investigated using molecular docking technology. 395 targets of SS and 1925 targets of ALS were obtained with 125 common targets. The protein-protein interaction analysis indicated that SRC, AKT1, MAPK1, EGFR, and HSP90AA1 received the higher degree value and were considered the central genes. The Ras, PI3K-Akt, and MAPK signaling pathway could be involved in the treatment of ALS. Brucine-N-oxide obtained the lowest binding energy in molecular docking. This study explored the mechanism of SS in the treatment of ALS and provides a new perspective for future study. However, further experimental studies are needed to validate the therapeutic effect.

Exploration and validation of Taraxacum mongolicum anti-cancer effect

Taraxacum mongolicum gained a lot of concern and was applied in 93 formulas in China due to its fame as a traditional Chinese medicine. The earliest recorded application of Taraxacum mongolicum was traced back to the Han dynasty. Generations of doctors boosted the usage and enriched the pharmacological mechanism. Clinical application of the Taraxacum mongolicum is flourishing as it treats multiple diseases. This study aims to explore the anti-cancer effect, retrieve the active ingredients and screen the key targets of Taraxacum mongolicum in cancer therapy. We collected and evaluated 10 key active compounds to investigate the anti-cancer effect via 69 significant targets and a variety of biological processes and pathways. Gene Ontology (GO) enrichment analysis uncovered targets associated with protein phosphorylation, cell proliferation and apoptotic processes via regulation of kinases, ATP and enzyme binding activities. Half of the top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were directly involved in cancer. Based on standard selection criteria, seven hub targets were obtained. These targets functioned through distinct patterns and pathways in realizing the anti-cancer effect. Molecular docking was conducted to validate the potential combination between compounds and hub targets to explore the pharmacological mechanism of key compounds in Taraxacum mongolicum against cancer. In summary, our findings indicate that the famous and widely used Chinese herb, Taraxacum mongolicum, shows good anti-cancer effect through its active compounds, targeted genes, and multiple involved biological processes. The results may provide a theoretical basis for subsequent experimental validation and drug development of Taraxacum mongolicum extract against cancer.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.