Prediction of Molecular Mechanisms for LianXia NingXin Formula: A Network Pharmacology Study

Chinese Herbal Medicines for Coronary Heart Disease: Clinical Evidence, Pharmacological Mechanisms, and the Interaction with Gut Microbiota

Coronary heart disease (CHD) is a common type of cardiovascular disease (CVD) that has been on the rise in terms of both incidence and mortality worldwide, presenting a significant threat to human health. An increasing body of studies has shown that traditional Chinese medicine (TCM), particularly Chinese herbal medicines (CHMs), can serve as an effective adjunctive therapy to enhance the efficacy of Western drugs in treating CHD due to their multiple targets and multiple pathways. In this article, we critically review data available on the potential therapeutic strategies of CHMs in the intervention of CHD from three perspectives: clinical evidence, pharmacological mechanisms, and the interaction with gut microbiota. We identified 20 CHMs used in clinical practice and it has been found that the total clinical effective rate of CHD patients improved on average by 17.78% with the intervention of these CHMs. Subsequently, six signaling pathways commonly used in treating CHD have been identified through an overview of potential pharmacological mechanisms of these 20 CHMs and the eight representative individual herbs selected from them. CHMs could also act on gut microbiota to intervene in CHD by modulating the composition of gut microbiota, reducing trimethylamine-N-oxide (TMAO) levels, increasing short-chain fatty acids (SCFAs), and maintaining appropriate bile acids (BAs). Thus, the therapeutic potential of CHMs for CHD is worthy of further study in view of the outcomes found in existing studies.

Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy

MOTIVATION

Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA).

RESULTS

We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/XinmengLiao/Open_MoA.

Predicting Coupled Herbs for the Treatment of Hypertension Complicated with Coronary Heart Disease in Real-World Data Based on a Complex Network and Machine Learning

Hypertension and coronary heart disease are the most common cardiovascular diseases, and traditional Chinese medicine is applied as an auxiliary treatment for common cardiovascular diseases. This study is based on 3 years of electronic medical record data from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine. A complex network and machine learning algorithm were used to establish a screening model of coupled herbs for the treatment of hypertension complicated with coronary heart disease. A total of 5688 electronic medical records were collected to establish the prescription network and symptom database. The hierarchical network extraction algorithm was used to obtain core herbs. Biological features of herbs were collected from public databases. At the same time, five supervised machine learning models were established based on the biological features of the coupled herbs. Finally, the K-nearest neighbor model was established as a screening model with an AUROC of 91.0%. Seventy coupled herbs for adjuvant treatment of hypertension complicated with coronary heart disease were obtained. It was found that the coupled herbs achieved the purpose of adjuvant therapy mainly by interfering with cytokines and regulating inflammatory and metabolic pathways. These results show that this model can integrate the molecular biological characteristics of herbs, preliminarily screen combinations of herbs, and provide ideas for explaining the value in clinical applications.

Elaborate the Mechanism of Ancient Classic Prescriptions (Erzhi Formula) in Reversing GIOP by Network Pharmacology Coupled with Zebrafish Verification

Osteoporosis is a degenerative disease that endangers human health. At present, chemical drugs used for osteoporosis have serious side effects. Therefore, it is valuable to search herbs with high safety and good curative effect in antiosteoporosis. Erzhi formula (EZF), an ancient classic compound, has been reported to have a beneficial effect in antiosteoporosis, but its mechanism is unclear. In this paper, the active compounds of EZF were found in Systems Pharmacology Database, and gene targets related to osteoporosis were obtained in GeneCards. The GO functional and KEGG pathway enrichment analysis were performed by Metascape. The network of “components-targets-signal pathway” was constructed by Cytoscape. Next, molecular docking between the active components and hub genes related to the PI3K-Akt signaling pathway was conducted by Autodock. In the verification experiment, the zebrafish induced by prednisolone (PNSL) was used to reproduce glucocorticoid-induced osteoporosis (GIOP) model, and then the reversal effects of EZF were systematically evaluated according to the behavior, skull staining area, bone mineralization area (BMA), average optical density (AOD), and cumulative optical density (COD). Finally, it was shown that 24 components in EZF could regulate 39 common gene targets to exert antiosteoporosis effect. Besides, the main regulatory mechanisms of EZF were 4 signaling pathways: PI3K-Akt, JAK-STAT, AGE-RAGE, and cancer pathway. In PI3K-Akt signaling pathway, wedelolactone, dimethyl wedelolactone, specnuezhenide, ursolic acid, acacetin, beta-sitosterol, apigenin, and kaempferol can bind tightly with EGF, IL-2, and IL-4 genes. Compared with the model group, the moving distance, swimming speed, and cumulative swimming time of zebrafish in EZF group were significantly increased (P < 0.05). Meanwhile, the BMA and COD of zebrafish were significantly improved after the intervention of EZF (P < 0.05). In summary, the 24 components of EZF exert their antiosteoporosis effects by regulating 39 related gene targets, among which the PI3K signaling pathway is crucial. EZF can promote bone formation and reversed GIOP through “multicomponent/multitarget/multipathway” and the medium dose of EZF may be the most suitable concentration for the treatment of GIOP in zebrafish model.

Identification of cardiomyopathy-related core genes through human metabolic networks and expression data

Background

Cardiomyopathy is a complex type of myocardial disease, and its incidence has increased significantly in recent years. Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common and indistinguishable types of cardiomyopathy.

Results

Here, a systematic multi-omics integration approach was proposed to identify cardiomyopathy-related core genes that could distinguish normal, DCM and ICM samples using cardiomyopathy expression profile data based on a human metabolic network. First, according to the differentially expressed genes between different states (DCM/ICM and normal, or DCM and ICM) of samples, three sets of initial modules were obtained from the human metabolic network. Two permutation tests were used to evaluate the significance of the Pearson correlation coefficient difference score of the initial modules, and three candidate modules were screened out. Then, a cardiomyopathy risk module that was significantly related to DCM and ICM was determined according to the significance of the module score based on Markov random field. Finally, based on the shortest path between cardiomyopathy known genes, 13 core genes related to cardiomyopathy were identified. These core genes were enriched in pathways and functions significantly related to cardiomyopathy and could distinguish between samples of different states.

Conclusion

The identified core genes might serve as potential biomarkers of cardiomyopathy. This research will contribute to identifying potential biomarkers of cardiomyopathy and to distinguishing different types of cardiomyopathy.

Study on the molecular mechanism of nightshade in the treatment of colon cancer

The present study attempts to explore the effective components, action targets, and potential mechanism of nightshade for colon cancer treatment. The relationship network diagram of 'traditional Chinese medicine - component - target - disease' was firstly constructed by employing network pharmacology. Experiments were conducted in vivo and in vitro to verify the influence of quercetin, the core effective component of nightshade, on colon cancer. Meanwhile, the regulatory effects of quercetin on core targets and main signaling pathways were determined. Based on the network diagram of 'traditional Chinese medicine - component - target - disease' and KEGG analysis, quercetin might exhibit certain effects on colon cancer treatment by regulating the biological behavior of core targets related to cell apoptosis in tumors including PIK3R1, PIK3CA, Akt1, and Akt2. Furthermore, quercetin has been demonstrated in vitro experiments to suppress the proliferation and migration of colon cancer cells whereas promote their apoptosis in a dose-dependent fashion. In vivo experiments indicate that quercetin had an antitumor effect on human colon cancer SW480 cells in nude mice bearing tumors. Furthermore, PIK3CA could bind to quercetin directly, which is validated by immunocoprecipitation. Therefore, the activation of PI3K/AKT phosphorylation was inhibited by quercetin and moreover the expressions of apoptotic proteins caspase-3 and Bcl2-Associated X protein (BAX) were up-regulated. In conclusion, the potential mechanism of nightshade lies in the activation of the PI3K/AKT signaling pathway inhibited by quercetin, thus promoting apoptosis of colon cancer cells for colon cancer treatment.

Using the Symptom Patient Similarity Network to Explore the Difference between the Chinese and Western Medicine Pathways of Ischemic Stroke and its Comorbidities

Methods

Individualized treatment of traditional Chinese medicine (TCM) provides a theoretical basis for the study of the personalized classification of complex diseases. Utilizing the TCM clinical electronic medical records (EMRs) of 7170 in patients with IS, a patient similarity network (PSN) with shared symptoms was constructed. Next, patient subgroups were identified using community detection methods and enrichment analyses were performed. Finally, genetic data of symptoms, herbs, and drugs were used for pathway and GO analysis to explore the characteristics of pathways of subgroups and to compare the similarities and differences in genetic pathways of herbs and drugs from the perspective of molecular pathways of symptoms.

Results

We identified 34 patient modules from the PSN, of which 7 modules include 98.48% of the whole cases. The 7 patient subgroups have their own characteristics of risk factors, complications, and comorbidities and the underlying genetic pathways of symptoms, drugs, and herbs. Each subgroup has the largest number of herb pathways. For specific symptom pathways, the number of herb pathways is more than that of drugs.

Conclusion

The research of disease classification based on community detection of symptom-shared patient networks is practical; the common molecular pathway of symptoms and herbs reflects the rationality of TCM herbs on symptoms and the wide range of therapeutic targets.

Chinese Patent Medicine Liuweiwuling Tablet had Potent Inhibitory Effects on Both Wild-Type and Entecavir-Resistant Hepatitis B Virus (HBV) in vitro and Effectively Suppressed HBV Replication in Mouse Model

Liuweiwuling Tablet (LWWL) is a licensed Chinese patent medicine (approval number: Z20060238) included in the national health insurance for anti-inflammation of chronic HBV infection, whereas its anti-HBV effect remains clarification. The study aimed to clarify its antiviral effect and related mechanisms. HepG2.2.15 cells (wild-type HBV-replicating cells) and HepG2. A64 cells (entecavir-resistant HBV-replicating cells) were used for in vitro test. Hydrodynamic injection-mediated HBV-replicating mouse model was used for in vivo test. Active compounds and related mechanisms for antiviral effect of LWWL were analyzed using network pharmacology and transcriptomics. The inhibition rates of LWWL (0.8 mg/ml) on HBV DNA, HBsAg, and pgRNA were 57.06, 38.55, and 62.49% in HepG2.2.15 cells, and 51.57, 17.57, and 53.88% in HepG2. A64 cells, respectively. LWWL (2 g kg^-1 d^-1 for 4 weeks)-treated mice had 1.16 log₁₀ IU/mL decrease of serum HBV DNA, and more than 50% decrease of serum HBsAg/HBeAg and hepatic HBsAg/HBcAg. Compared to tenofovir control, LWWL was less effective in suppressing HBV DNA but more effective in suppressing HBV antigens. Thirteen differentially-expressed genes were found in relation to HBV-host interaction and some of them were enriched in interferon (IFN)-β pathway in LWWL-treated HepG2.2.15 cells. CD3⁺CD4⁺ T-cell frequency and serum IFN-γ were significantly increased in LWWL-treated mice compared to LWWL-untreated mice. Among 26 compounds with potential anti-HBV effects that were predicted by network pharmacology, four compounds (quercetin, luteolin, wogonin, and kaempferol) were experimentally confirmed to have antiviral potency. In conclusion, LWWL had potent inhibitory effect on both wild-type and entecavir-resistant HBV, which might be associated with increasing IFN-β and IFN-γ production.

Network Pharmacology-Based Strategy to Investigate Pharmacological Mechanisms of Qiaoshao Formula for Treatment of Premature Ejaculation

Background

Qiaoshao (QS) formula, a traditional Chinese medicine (TCM) comprising seven herbs, has been clinically proven to have a favorable treatment effect on premature ejaculation (PE). However, its underlying pharmacological mechanisms in the treatment of PE need to be further clarified.

Methods

In the present study, a network pharmacology-based strategy was adopted. The active compounds of QS formula were obtained from the Chinese medicine database, and the potential targets of these compounds were collected from the DrugBank database to construct compound-compound targets network. PE-related targets were identified from human disease databases and used to construct the protein-protein interaction (PPI) networks. Compound-disease target PPI network was constructed by merging the PPI network of disease-targets and compound-targets. Cluster and enrichment analyses were performed on the PPI network of disease targets and compound-disease targets. The influence of QS formula on serum 5-HT, NO, oxytocin, and thyroid hormones of PE patients was verified.

Results

Four primary pharmacological networks of QS formula were constructed, including the compound-compound targets network, PPI network of PE-related targets and compound-disease targets, and the QS-PE mechanism network. The module and pathway enrichment analyses revealed that the QS formula had the potential to affect varieties of biological process and pathways, such as nitric oxide biosynthetic process, oxytocin, thyroid hormone, TNF, PI3K-Akt, and the HIF-1 signaling pathway, that play an important role in the pathogenesis of PE. Meanwhile, the QS formula has been clinically confirmed to regulate the serum level of 5-HT, NO, oxytocin, and TT in PE patients.

Conclusion

This study preliminarily discovered the potential targets and pathways of QS formula in the treatment of PE, which laid a good foundation for further experimental research.

Clinical features and the traditional Chinese medicine therapeutic characteristics of 293 COVID-19 inpatient cases

Coronavirus disease 2019 (COVID-19) is now pandemic worldwide and has heavily overloaded hospitals in Wuhan City, China during the time between late January and February. We reported the clinical features and therapeutic characteristics of moderate COVID-19 cases in Wuhan that were treated via the integration of traditional Chinese medicine (TCM) and Western medicine. We collected electronic medical record (EMR) data, which included the full clinical profiles of patients, from a designated TCM hospital in Wuhan. The structured data of symptoms and drugs from admission notes were obtained through an information extraction process. Other key clinical entities were also confirmed and normalized to obtain information on the diagnosis, clinical treatments, laboratory tests, and outcomes of the patients. A total of 293 COVID-19 inpatient cases, including 207 moderate and 86 (29.3%) severe cases, were included in our research. Among these cases, 238 were discharged, 31 were transferred, and 24 (all severe cases) died in the hospital. Our COVID-19 cases involved elderly patients with advanced ages (57 years on average) and high comorbidity rates (61%). Our results reconfirmed several well-recognized risk factors, such as age, gender (male), and comorbidities, as well as provided novel laboratory indications (e.g., cholesterol) and TCM-specific phenotype markers (e.g., dull tongue) that were relevant to COVID-19 infections and prognosis. In addition to antiviral/antibiotics and standard supportive therapies, TCM herbal prescriptions incorporating 290 distinct herbs were used in 273 (93%) cases. The cases that received TCM treatment had lower death rates than those that did not receive TCM treatment (17/273 = 6.2% vs. 7/20= 35%, P = 0.0004 for all cases; 17/77= 22% vs. 7/9= 77.7%, P = 0.002 for severe cases). The TCM herbal prescriptions used for the treatment of COVID-19 infections mainly consisted of Pericarpium Citri Reticulatae, Radix Scutellariae, Rhizoma Pinellia, and their combinations, which reflected the practical TCM principles (e.g., clearing heat and dampening phlegm). Lastly, 59% of the patients received treatment, including antiviral, antibiotics, and Chinese patent medicine, before admission. This situation might have some effects on symptoms, such as fever and dry cough. By using EMR data, we described the clinical features and therapeutic characteristics of 293 COVID-19 cases treated via the integration of TCM herbal prescriptions and Western medicine. Clinical manifestations and treatments before admission and in the hospital were investigated. Our results preliminarily showed the potential effectiveness of TCM herbal prescriptions and their regularities in COVID-19 treatment.

Network pharmacology-based study on the mechanism of Yiganling capsule in hepatitis B treatment

Background

Yiganling (YGL) capsule is a traditional Chinese medicine preparation consisting of eight herbs that has been clinically proven to have a favorable treatment effect on Hepatitis B (HB). However, due to its multiple targets and multi-pharmacological effects, the mechanisms of YGL capsule in the treatment of HB are unknown.

Methods

First, the chemical constituents of YGL capsules were obtained from the Chinese medicine database, and YGL capsules were constructed. Second, active compounds were screened by the ADME model. The target fishing model was used to screen the corresponding targets of active compounds and to construct a compounds and compound targets network. Using human disease databases and literature mining, we systematically identified genes associated with HB, constructed disease-specific protein-protein interaction networks, and performed clustering and enrichment analyses of these networks. These networks were then merged to obtain a compound-disease target network, and cluster and enrichment analyses were performed on the compound-disease target network to acquire a compounds-disease targets-mechanism network and a clustering network.

Results

We successfully built eight pharmacological network diagrams, including four primary networks and other network maps. The four dominating network maps included a HB disease-associated protein-protein interaction network, a YGL capsule compounds-target network, a YGL capsule ingredient target-HB disease target network, and a YGL-HB disease mechanism network. Other networks included a pathway of HB disease targets, the HB disease protein-protein interaction cluster analysis network, and the YGL-HB target clustering network.

Conclusion

This study successfully forecasted, illuminated, and confirmed the synergistic effects of HB disease molecules and discovered the potential of HB relevant targets, clusters, and target-related biological processes and signaling pathways. Our research not only provides theoretical support for the molecular and pharmacological mechanisms of YGL capsule in HB treatment, but also provides new research methods for the study of the other traditional Chinese medicinal compounds.

Network Pharmacology in Research of Chinese Medicine Formula: Methodology, Application and Prospective

Chinese medicine (CM) is usually prescribed as CM formula to treat disease. The lack of effective research approach makes it difficult to elucidate the molecular mechanisms of CM formula owing to its complicated chemical compounds. Network pharmacology is increasingly applied in CM formula research in recent years, which is identified suitable for the study of CM formula. In this review, we summarized the methodology of network pharmacology, including network construction, network analysis and network verification. The aim of constructing a network is to achieve the interaction between the bioactive compounds and targets and the interaction between various targets, and then find out and validate the key nodes via network analysis and network verification. Besides, we reviewed the application in CM formula research, mainly including targets discovery, bioactive compounds screening, toxicity evaluation, mechanism research and quality control research. Finally, we proposed prospective in the future and limitations of network pharmacology, expecting to provide new strategy and thinking on study for CM formula.