Network pharmacology based investigation of the effects of herbal ingredients on the immune dysfunction in heart disease

COIMMR: a computational framework to reveal the contribution of herbal ingredients against human cancer via immune microenvironment and metabolic reprogramming

Immune evasion and metabolism reprogramming have been regarded as two vital hallmarks of the mechanism of carcinogenesis. Thus, targeting the immune microenvironment and the reprogrammed metabolic processes will aid in developing novel anti-cancer drugs. In recent decades, herbal medicine has been widely utilized to treat cancer through the modulation of the immune microenvironment and reprogrammed metabolic processes. However, labor-based herbal ingredient screening is time consuming, laborious and costly. Luckily, some computational approaches have been proposed to screen candidates for drug discovery rapidly. Yet, it has been challenging to develop methods to screen drug candidates exclusively targeting specific pathways, especially for herbal ingredients which exert anti-cancer effects by multiple targets, multiple pathways and synergistic ways. Meanwhile, currently employed approaches cannot quantify the contribution of the specific pathway to the overall curative effect of herbal ingredients. Hence, to address this problem, this study proposes a new computational framework to infer the contribution of the immune microenvironment and metabolic reprogramming (COIMMR) in herbal ingredients against human cancer and specifically screen herbal ingredients targeting the immune microenvironment and metabolic reprogramming. Finally, COIMMR was applied to identify isoliquiritigenin that specifically regulates the T cells in stomach adenocarcinoma and cephaelin hydrochloride that specifically targets metabolic reprogramming in low-grade glioma. The in silico results were further verified using in vitro experiments. Taken together, our approach opens new possibilities for repositioning drugs targeting immune and metabolic dysfunction in human cancer and provides new insights for drug development in other diseases. COIMMR is available at https://github.com/LYN2323/COIMMR.

Pharmacological effects and mechanisms of YiYiFuZi powder in chronic heart disease revealed by metabolomics and network pharmacology

Introduction: YiYiFuZi powder (YYFZ) is a classical formula in Chinese medicine, which is commonly used clinically for the treatment of Chronic Heart Disease (CHD), but it's pharmacological effects and mechanism of action are currently unclear. Methods: An adriamycin-induced CHD model rat was established to evaluate the pharmacological effects of YYFZ on CHD by the results of inflammatory factor level, histopathology and echocardiography. Metabolomic studies were performed on rat plasma using UPLC-Q-TOF/MS to screen biomarkers and enrich metabolic pathways; network pharmacology analysis was also performed to obtain the potential targets and pathways of YYFZ for the treatment of CHD. Results: The results showed that YYFZ significantly reduced the levels of TNF-α and BNP in the serum of rats, alleviated the disorder of cardiomyocyte arrangement and inflammatory cell infiltration, and improved the cardiac function of rats with CHD. The metabolomic analysis identified a total of 19 metabolites, related to amino acid metabolism, fatty acid metabolism, and other metabolic pathways. Network pharmacology showed that YYFZ acts through PI3K/Akt signaling pathway, MAPK signaling pathway and Ras signaling pathway. Discussion: YYFZ treatment of CHD modulates blood metabolic pattern and several protein phosphorylation cascades but importance specific changes for therapeutic effect require further studies.

Network Pharmacology and Molecular Docking Elucidate the Underlying Pharmacological Mechanisms of the Herb Houttuynia cordata in Treating Pneumonia Caused by SARS-CoV-2

Used in Asian countries, including China, Japan, and Thailand, Houttuynia cordata Thumb (H. cordata; Saururaceae, HC) is a traditional herbal medicine that possesses favorable antiviral properties. As a potent folk therapy used to treat pulmonary infections, further research is required to fully elucidate the mechanisms of its pharmacological activities and explore its therapeutic potential for treating pneumonia caused by SARS-CoV-2. This study explores the pharmacological mechanism of HC on pneumonia using a network pharmacological approach combined with reprocessing expression profiling by high-throughput sequencing to demonstrate the therapeutic mechanisms of HC for treating pneumonia at a systemic level. The integration of these analyses suggested that target factors are involved in four signaling pathways, including PI3K-Akt, Jak-STAT, MAPK, and NF-kB. Molecular docking and molecular dynamics simulation were applied to verify these results, indicating a stable combination between four metabolites (Afzelin, Apigenin, Kaempferol, Quercetin) and six targets (DPP4, ELANE, HSP90AA1, IL6, MAPK1, SERPINE1). These natural metabolites have also been reported to bind with ACE2 and 3CLpro of SARS-CoV-2, respectively. The data suggest that HC exerts collective therapeutic effects against pneumonia caused by SARS-CoV-2 and provides a theoretical basis for further study of the active drug-like ingredients and mechanism of HC in treating pneumonia.

Network Pharmacology Integrated Molecular Docking to Explore the Mechanism of Blister Beetle Therapy for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the major causes of cancer death in the world. Studies show that the effective anticancer component in blister beetles is cantharidin, which can improve chemotherapy efficacy, median survival, and prognosis of LUAD. However, the antitumor mechanism of blister beetles has not been fully clarified. This study aimed to identify the key targets of the treatment of LUAD by blister beetles based on the principle of network pharmacology. An integrated approach including network pharmacology and a molecular docking technique was conducted, which mainly comprises target prediction, weighted gene correlation network analysis (WGCNA) analysis, network construction, gene ontology, and pathway enrichment analysis. 35 key targets were obtained and significantly associated with response to external stimuli, collagen binding, cyclin binding, organic acid binding, pyruvate metabolism, glycolysis, and amino acid biosynthesis pathways. Both LASSO regression and the RF model had a high predictive ability, and 9 candidate genes were screened, among which BIRC5 and PLK1 were the key targets for the treatment of LUAD by using blister beetles and showed significant survival significance. Cantharidin exerts its antitumor effects through 8 targets in 32 pathways, while BIRC5 and PLK1 have obvious survival significance.

Mechanisms of magnoliae cortex on treating sarcopenia explored by GEO gene sequencing data combined with network pharmacology and molecular docking

Background

Administration of Magnoliae Cortex (MC) could induce remission of cisplatin-induced sarcopenia in mice, however, whether it is effective on sarcopenia patients and the underlying mechanisms remain unclear.

Methods

Sarcopenia related differentially expressed genes were analysed based on three Gene Expression Omnibus (GEO) transcriptome profiling datasets, which was merged and de duplicated with disease databases to obtain sarcopenia related pathogenic genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were than performed to analyse the role of proteins encoded by sarcopenia related pathogenic genes and the signal regulatory pathways involved in. The main active components and target proteins of MC were obtained by searching traditional Chinese medicine network databases (TCMSP and BATMAN-TCM). MC and sarcopenia related pathogenic genes shared target proteins were identified by matching the two. A protein–protein interaction network was constructed subsequently, and the core proteins were filtered according to the topological structure. GO and KEGG analysis were performed again to analyse the key target proteins and pathways of MC in the treatment of sarcopenia, and build the herbs-components-targets network, as well as core targets-signal pathways network. Molecular docking technology was used to verify the main compounds-targets.

Results

Sarcopenia related gene products primarily involve in aging and inflammation related signal pathways. Seven main active components (Anonaine, Eucalyptol, Neohesperidin, Obovatol, Honokiol, Magnolol, and beta-Eudesmol) and 26 target proteins of MC-sarcopenia, of which 4 were core proteins (AKT1, EGFR, INS, and PIK3CA), were identified. The therapeutic effect of MC on sarcopenia may associate with PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, longevity regulating pathway, and other cellular and innate immune signaling pathways.

Conclusion

MC contains potential anti-sarcopenia active compounds. These compounds play a role by regulating the proteins implicated in regulating aging and inflammation related signaling pathways, which are crucial in pathogenesis of sarcopenia. Our study provides new insights into the development of a natural therapy for the prevention and treatment of sarcopenia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01029-x.

Network Pharmacology-Based Mechanistic Investigation of Jinshui Huanxian Formula Acting on Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic respiratory disease with high incidence, morbidity, and mortality rates. Jinshui Huanxian formula (JHF) is an empirical formula that targets the pathogenesis of lung-kidney qi deficiency and phlegm-blood stasis in pulmonary fibrosis (PF). The purpose of this study was to explore JHF's potential pharmacological mechanisms in IPF therapy using network intersection analysis. JHF's primary active components and corresponding target genes were predicted using various databases. Two sets of IPF disease genes were obtained from the DisGeNET and GEO databases and two sets of IPF drug targets were collected. The disease and drug target genes were analyzed. The JHF target genes that intersected with IPF's differentially expressed genes were identified to predict JHF's targets of action in IPF. The functions and pathways of predicted targets acting on IPF were analyzed using the DAVID and KEGG pathway databases. Finally, the resulting drug target mechanisms were validated in a rat model of PF. The initial analyses identified 494 active compounds and 1,304 corresponding targets for JHF. The intersection analysis revealed four common genes for the JHF targets, IPF disease, and anti-IPF drugs in the KEGG database. Furthermore, these genes were targeted by several JHF compounds. Seventy-two JHF targets were closely related to IPF, which suggests that they are therapeutically relevant. Target screening revealed that they regulate IPF through 18 pathways. The targets' molecular functions included regulation of oxidoreductase activity, kinase regulator activity, phosphotransferase activity, and transmembrane receptor protein kinase activity. In vivo experiments showed that JHF alleviated the degree of PF, including decreases in collagen deposition and epithelial-mesenchymal transition. This study systematically explored JHF's mechanisms to identify the specific target pathways involved in IPF. The generated pharmacological network, paired with in vivo validation, elucidates the potential roles and mechanisms of JHF in IPF therapy.

Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

Objective

To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking.

Methods

Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE).

Results

A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets.

Conclusion

The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

Traditional Chinese medicine in cardiovascular drug discovery

In this virtual special issue entitled "Traditional Chinese Medicine in Cardiovascular Drug Discovery", a collection of 18 basic research, clinical research and review articles was published to highlight the therapeutic potential of traditional Chinese medicine (TCM) and their bioactive components in treating atherosclerosis, coronary artery disease, ischemic cardiomyopathy, heart failure and beyond.

Gynura divaricata exerts hypoglycemic effects by regulating the PI3K/AKT signaling pathway and fatty acid metabolism signaling pathway

OBJECTIVES

The study aimed to examine the anti-diabetic effects of Gynura divaricata (GD) and the underlying mechanism.

METHODS

Information about the chemical compositions of GD was obtained from extensive literature reports. Potential target genes were predicted using PharmMapper and analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). To validate the results from bioinformatics analyses, an aqueous extract of GD was administered to type 2 diabetic rats established by feeding a high-fat and high-sugar diet followed by STZ injection. Key proteins of the PI3K/AKT signaling pathway and fatty acid metabolism signaling pathway were investigated by immunoblotting.

RESULTS

The blood glucose of the rats in the GD treatment group was significantly reduced compared with the model group without treatment. GD also showed activities in reducing the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), and creatinine (CREA). The levels of urine sugar (U-GLU) and urine creatinine (U-CREA) were also lowered after treatment with GD. Bioinformatics analysis showed that some pathways including metabolic pathways, insulin resistance, insulin signaling pathway, PPAR signaling pathway, bile secretion, purine metabolism, etc. may be regulated by GD. Furthermore, GD significantly increased the protein expression levels of PKM1/2, p-AKT, PI3K p85, and GLUT4 in the rat liver. In addition, the expression levels of key proteins in the fatty acid metabolism signaling pathway including AMPK, p-AMPK, PPARα, and CPT1α were significantly upregulated. The anti-apoptotic protein BCL-2/BAX expression ratio in rats was significantly upregulated after GD intervention. These results were consistent with the bioinformatics analysis results.

CONCLUSIONS

Our study suggests that GD can exert hypoglycemic effects in vivo by regulating the genes at the key nodes of the PI3K/AKT signaling pathway and fatty acid metabolism signaling pathway.

Chemical composition and pharmacological mechanism of Qingfei Paidu Decoction and Ma Xing Shi Gan Decoction against Coronavirus Disease 2019 (COVID-19): In silico and experimental study

The Coronavirus Disease 2019 (COVID-19) pandemic has become a huge threaten to global health, which raise urgent demand of developing efficient therapeutic strategy. The aim of the present study is to dissect the chemical composition and the pharmacological mechanism of Qingfei Paidu Decoction (QFPD), a clinically used Chinese medicine for treating COVID-19 patients in China. Through comprehensive analysis by liquid chromatography coupled with high resolution mass spectrometry (MS), a total of 129 compounds of QFPD were putatively identified. We also constructed molecular networking of mass spectrometry data to classify these compounds into 14 main clusters, in which exhibited specific patterns of flavonoids (45 %), glycosides (15 %), carboxylic acids (10 %), and saponins (5 %). The target network model of QFPD, established by predicting and collecting the targets of identified compounds, indicated a pivotal role of Ma Xing Shi Gan Decoction (MXSG) in the therapeutic efficacy of QFPD. Supportively, through transcriptomic analysis of gene expression after MXSG administration in rat model of LPS-induced pneumonia, the thrombin and Toll-like receptor (TLR) signaling pathway were suggested to be essential pathways for MXSG mediated anti-inflammatory effects. Besides, changes in content of major compounds in MXSG during decoction were found by the chemical analysis. We also validate that one major compound in MXSG, i.e. glycyrrhizic acid, inhibited TLR agonists induced IL-6 production in macrophage. In conclusion, the integration of in silico and experimental results indicated that the therapeutic effects of QFPD against COVID-19 may be attributed to the anti-inflammatory effects of MXSG, which supports the rationality of the compatibility of TCM.

Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning

Traditional Chinese medicine (TCM) has long been used in the clinical treatment of coronary heart disease (CHD). TCM is characterized by syndrome-based medication, which is, using different TCM formulae for different syndromes. However, the underlying mode of action remains unclear. In this work, we utilized network pharmacology and machine learning to explore the mechanism of eight classic TCM formulae in the treatment of different types of CHD. First, by integrating multiple databases, a total of 669 potential bioactive compounds and 581 targets of the eight formulae were screened. Then, the effectiveness of these formulae on CHD was evaluated using two network-based indicators. The results showed that each formula's targets were significantly correlated with CHD associated genes and overlapped with the targets of 9 classes of drugs for cardio vascular diseases (CVD) to some degree. Next, from 5 different levels, i.e., herb, symptom, compound, target, and pathway level, we systematically compared the eight formulae using network clustering and hierarchical clustering. We found that all the formulae could be grouped into five clusters and the clustering results were approximately consistent at different levels. All the formulae were involved in 7 pathways closely related to CHD and may exhibit the common effect of relieving angina. Formulae in the same group collectively regulated some unique pathways and suggest further specific indications. For example, the three formulae used for Qi stagnation and blood stasis, Qi deficiency and blood stasis, and Qi-Yin deficiency syndromes acted on two special pathways (TNF signaling pathway, NF-kappa B signaling pathway) and may exert anti-inflammatory and immune-enhancing effects; the two formulae for Yin deficiency of heart and kidney, and Yang deficiency of heart and kidney syndromes regulated two special pathways (PPAR signaling pathway, thyroid hormone signaling pathway) in endocrine system and could improve renal function. Subsequently, we designed a rank algorithm, which integrated network topology with biological function, to identify important targets of these formulae. The results were consistent with the multi-level clustering results. At last, our literature mining validated about 20 % putative targets, as well as clustering results and effects of the formulae by experimental evidences. This study explained the medication patterns and scientific significance of TCM formulae on different types of CHD from perspective of systems biology. It may facilitate the understanding of different types of CHD described by traditional Chinese medicine from the perspectives of modern biology.

Detection of Vasodilators From Herbal Components by a Transcriptome-Based Functional Gene Module Reference Approach

Vasodilatation is one of the key therapeutic strategies for the treatment of various cardiovascular diseases with high blood pressure. Therefore, development of drugs assisting blood vessel dilation is promising. It has been proven that many drugs display definite vasorelaxant effects. However, there are very few studies that systemically explore the effective vasodilators. In this work, we build a transcriptome-based functional gene module reference approach for systematic pursuit of agents with vasorelaxant effects. We firstly curate two functional gene modules that are specifically involved in positive and negative regulation of vascular diameter based on the known gene functional interaction knowledge. Secondly, a collection of gene expression profiles following herbal component treatment are collected from a public gene expression database. Then, the correlation of the gene modules is evaluated in each herbal component–induced gene expression profile by gene set enrichment analysis. The vasorelaxant effects of the candidate compounds can be predicted and ordered by the values of a defined index. Finally, the top 10 candidate compounds are experimentally tested for their vasorelaxant effects on vessel contraction induced by Phe in aortic rings. This strategy integrating different types of technologies is expected to help to create new opportunities for the development of novel vasodilators.