Network pharmacology and bioinformatics approach reveals the hypolipidemic mechanism of Dan Tian Jiang Zhi pill

Elucidating the protective mechanism of ganoderic acid DM on breast cancer based on network pharmacology and in vitro experimental validation

Ganoderma lucidum, a popular medicinal fungus, has been utilized to treat a variety of diseases. It possesses a unique therapeutic and pharmacological reputation in suppressing cancer/tumor progression, especially breast cancer, due to its embedded rich bioactive chemical constituents, mainly triterpenoids (ganoderic acids). The most prevalent malignant tumor in women with a high mortality and morbidity rate is breast cancer. Ganoderic acids A, D, DM, F, and H are evidenced in previous research to have breast cancer-preventive properties by exhibiting autophagic and apoptosis, anti-proliferative, and anti-angiogenesis effects. However, the anti-breast cancer mechanism remains unclear. The putative targets of the ganoderic acids were further determined using bioinformatics techniques and molecular docking calculation. Finally, the key targets were verified in vitro. A total of 53 potential target proteins associated with 202 pathways were predicted to be related to breast cancer. The potential targets were narrowed down to six key targets (AKT1, PIK3CA, epidermal growth factor receptor [EGFR], STAT1, ESR1, and CTNNB1), using different algorithms of the CytoHubba plugin, which were further validated using molecular docking analysis. The ganoderic acid DM (GADM) and the targets (PIK3CA and EGFR) with the strongest interactions were validated via MDA-MB-231 and MCF7 cells. The expression level of PIK3CA in both MDA-MB-231 and MCF7 cells was dose-dependently suppressed by GADM, whereas EGFR expression was unexpectedly increased, which warrants further investigation. These data indicated that the network pharmacology-based prediction of GADM targets for treating human breast cancer could be reliable.

Network pharmacology prediction and molecular docking-based strategy to explore the potential mechanism of squalene against inflammation

Squalene (SQ) has been documented in the past for its ability to reduce inflammation, but its mechanism needs more information. In this study, we investigated squalene as an anti-inflammatory drug candidate and the framework involved in treating inflammation (INF) using the network pharmacology concept. The molecular targets of SQ and INF that are available in databases and the overlaps between these targets were demonstrated using InteractiVenn. The protein-protein networks were generated that in turn revealed several key targets and were further processed with Cytoscape. The gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) studies were performed. We also performed molecular docking tests that validated the binding affinity of molecular targets and drugs. A total of 100 SQ targets and 11,417 INF-related targets yielded 93 overlapping targets. Seven core targets, CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R were found to be relevant with respective to SQ's anti-inflammatory activity. The underlying mechanism of SQ with regard to INF was interpreted by analyzing various enrichment analyses along with the KEGG pathway. In conclusion, SQ played a vital role in the management of INF by regulating CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R. The research outcomes are crucial as they offer significant insights into the use of SQ for combating inflammation.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00217-0.

Explore the Potential Ingredients for Detoxification of Honey-Fired Licorice (ZGC) Based on the Metabolic Profile by UPLC-Q-TOF-MS

Licorice is well known for its ability to reduce the toxicity of the whole prescription in traditional Chinese medicine theory. However, honey-fired licorice (ZGC for short), which is made of licorice after being stir-fried with honey water, is more commonly used for clinical practice. The metabolism in vivo and detoxification-related compounds of ZGC have not been fully elucidated. In this work, the chemical constituents in ZGC and its metabolic profile in rats were both identified by high ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The network pharmacology was applied to predict the potential detoxifying ingredients of ZGC. As a result, a total of 115 chemical compounds were identified or tentatively characterized in ZGC aqueous extract, and 232 xenobiotics (70 prototypes and 162 metabolites) were identified in serum, heart, liver, kidneys, feces, and urine. Furthermore, 41 compounds absorbed in serum, heart, liver, and kidneys were employed for exploring the detoxification of ZGC by network pharmacology. Ultimately, 13 compounds (five prototypes including P5, P24, P30, P41 and P44, and 8 phase Ⅰ metabolites including M23, M47, M53, M93, M100, M106, M118, and M134) and nine targets were anticipated to be potential mediums regulating detoxification actions. The network pharmacology analysis had shown that the ZGC could detoxify mainly through regulating the related targets of cytochrome P450 and glutathione. In summary, this study would help reveal potential active ingredients in vivo for detoxification of ZGC and provided practical evidence for explaining the theory of traditional Chinese medicine with modern technology.

Medicine in motion: Opportunities, challenges and data analytics-based solutions for traditional medicine integration into western medical practice

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional pharmacopeias have been developed by multiple cultures and evaluated for efficacy and safety through both historical/empirical iteration and more recently through controlled studies using Western scientific paradigms and an increasing emphasis on data science methodologies for network pharmacology. Traditional medicines represent likely sources of relatively inexpensive drugs for symptomatic management as well as potential libraries of new therapeutic approaches. Leveraging this potential requires hard evidence for efficacy that separates science from pseudoscience.

MATERIALS AND METHODS

We performed a review of non-Western medical systems and developed case studies that illustrate the epistemological and practical translative barriers that hamper their transition to integration with Western approaches. We developed a new data analytics approach, in silico convergence analysis, to deconvolve modes of action, and potentially predict desirable components of TM-derived formulations based on computational consensus analysis across cultures and medical systems.

RESULTS

Abstraction, simplification and altered dose and delivery modalities were identified as factors that influence actual and perceived efficacy once a medicine is moved from a non-Western to Western setting. Case studies on these factors highlighted issues with translation between non-Western and Western epistemologies, including those where epistemological and medicinal systems drive markets that can be epicenters for zoonoses such as the novel Coronavirus. The proposed novel data science approach demonstrated the ability to identify and predict desirable medicinal components for a test indication, pain.

CONCLUSIONS

Relegation of traditional therapies to the relatively unregulated nutraceutical industry may lead healthcare providers and patients to underestimate the therapeutic potential of these medicines. We suggest three areas of emphasis for this field: First, vertical integration and embedding of traditional medicines into healthcare systems would subject them to appropriate regulation and evidence-based practice, as viable integrative implementation mode. Second, we offer a new Bradford-Hill-like framework for setting research priorities and evaluating efficacy, with the goal of rescuing potentially valuable therapies from the nutraceutical market and discrediting those that are pseudoscience. Third, data analytics pipelines offer new capacity to generate new types of TMS-inspired medicines that are rationally-designed based on integrated knowledge across cultures, and also provide an evaluative framework against which to test claims of fidelity and efficacy to TMS made for nutraceuticals.