BATMAN-TCM 2.0: an enhanced integrative database for known and predicted interactions between traditional Chinese medicine ingredients and target proteins

Traditional Chinese medicine (TCM) is increasingly recognized and utilized worldwide. However, the complex ingredients of TCM and their interactions with the human body make elucidating molecular mechanisms challenging, which greatly hinders the modernization of TCM. In 2016, we developed BATMAN-TCM 1.0, which is an integrated database of TCM ingredient-target protein interaction (TTI) for pharmacology research. Here, to address the growing need for a higher coverage TTI dataset, and using omics data to screen active TCM ingredients or herbs for complex disease treatment, we updated BATMAN-TCM to version 2.0 (http://bionet.ncpsb.org.cn/batman-tcm/). Using the same protocol as version 1.0, we collected 17 068 known TTIs by manual curation (with a 62.3-fold increase), and predicted ∼2.3 million high-confidence TTIs. In addition, we incorporated three new features into the updated version: (i) it enables simultaneous exploration of the target of TCM ingredient for pharmacology research and TCM ingredients binding to target proteins for drug discovery; (ii) it has significantly expanded TTI coverage; and (iii) the website was redesigned for better user experience and higher speed. We believe that BATMAN-TCM 2.0, as a discovery repository, will contribute to the study of TCM molecular mechanisms and the development of new drugs for complex diseases.

Identification of formononetin as the active compound of CR-SR in hepatocellular carcinoma treatment: An integrated approach combining network pharmacology and weighted gene co-expression networks

Hepatocellular carcinoma (HCC) is a life-threatening disease for which there is no cure. Traditional Chinese medicine is a treasure trove of Medicinals that has been used for thousands of years. In China, the traditional herb pair, Curcumae Rhizoma and Sparganii Rhizoma (CR-SR) represent a classic herbal combination used for the treatment of HCC. However, the drug targets and pharmacological mechanism of action of CR-SR in the treatment of HCC are unclear. To address this, we screened the active components and drug targets of CR-SR from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and a high-throughput experiment- and reference-guided database of traditional Chinese medicines (HERB database). Combined with the weighted co-expression network analysis of dataset GSE76427, we constructed an active component-target-disease regulatory network. It was found that CR-SR's active components for HCC treatment included trans-gondoic acid, beta-sitosterol, stigmasterol, hederagenin, and formononetin. These compounds specifically targeted the genes Estrogen Receptor 1 (ESR1), Cyclin A2 (CCNA2), Checkpoint Kinase 1 (CHEK1), and Nuclear Receptor Coactivator 2 (NCOA2). ESR1, CCNA2, and CHEK1 genes showed significant differences in survival prognosis, expression levels, and statistical significance during the pathological stage. Moreover, their high affinity for formononetin was determined through molecular docking analysis. Cell assays and high-throughput sequencing were performed to reveal that the inhibitory effect of formononetin on HepG2 cell proliferation was related to hepatocyte metabolism and cell cycle regulation-related pathways. This study provides insights into potential HCC treatments.

Rapid identification of chemical constituents in Yinqiao Powder using ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry with data filtering strategy

Yinqiao Powder is a classic and effective prescription for the treatment of many kinds of pneumonia in China. To date, the chemical constituents had not been uncovered. Comprehensive identification of chemical constituents provided a structure basis to discover the potential anti-pneumonia ingredients in Yinqiao Powder. In this paper, ultra-high performance liquid chromatography coupled to quadrupole time of flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) analysis with diagnostic product ions and neutral loss filtering strategy were established and applied for the comprehensive chemical profiling of Yinqiao Powder, which simplified structure elucidation of chemical constituents in Yinqiao Powder. A total of 124 compounds, including 8 C6-C2 glucoside conjugates, 28 iridoid glycosides, 14 lignans, 21 phenylethanol glycosides, 20 triterpenoid saponins, 9 chlorogenic acids and 24 flavonoids were rapidly identified in Yinqiao Powder, and 32 of them were characterized by comparing their MS/MS data and retention time with reference standards. The results indicated that UHPLC-QTOF-MS/MS method coupled with data filtering strategy was feasible and rational to identify the complex chemical constituents of Yinqiao Powder, which would be conducive to discover the active ingredients of Yinqiao Powder for the treatment of pneumonia and establish its quality standard.

Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology

Objective

Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS.

Methods

The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina.

Results

According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets.

Conclusions

In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

Qualitative analysis of chemical components in Lianhua Qingwen capsule by HPLC-Q Exactive-Orbitrap-MS coupled with GC-MS

The Lianhua Qingwen (LHQW) capsule is a popular traditional Chinese medicine for the treatment of viral respiratory diseases. In particular, it has been recently prescribed to treat infections caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, due to its complex composition, little attention has been directed toward the analysis of chemical constituents present in the LHQW capsule. This study presents a reliable and comprehensive approach to characterizing the chemical constituents present in LHQW by high-performance liquid chromatography-Q Exactive-Orbitrap mass spectrometry (HPLC-Q Exactive-Orbitrap-MS) coupled with gas chromatography-mass spectrometry (GC-MS). An automated library alignment method with a high mass accuracy (within 5 ppm) was used for the rapid identification of compounds. A total of 104 compounds, consisting of alkaloids, flavonoids, phenols, phenolic acids, phenylpropanoids, quinones, terpenoids, and other phytochemicals, were successfully characterized. In addition, the fragmentation pathways and characteristic fragments of some representative compounds were elucidated. GC-MS analysis was conducted to characterize the volatile compounds present in LHQW. In total, 17 compounds were putatively characterized by comparing the acquired data with that from the NIST library. The major constituent was menthol, and all the other compounds were terpenoids. This is the first comprehensive report on the identification of the major chemical constituents present in the LHQW capsule by HPLC-Q Exactive-Orbitrap-MS, coupled with GC-MS, and the results of this study can be used for the quality control and standardization of LHQW capsules.

iTRAQ-based quantitative proteomics and network pharmacology revealing hemostatic mechanism mediated by Zingiberis Rhizome Carbonisata in deficiency-cold and Hemorrhagic Syndrome rat models

Zingiberis Rhizome Carbonisata (ZRC) has been used as a hemostatic agent in traditional Chinese medicine (TCM). However, the underlying molecular mechanism remains unclear. In this study, network pharmacology method was used to predict the potential mechanism of ZRC on hemostasis, based on the structures of the main compounds. Then, iTRAQ-based quantitative proteomics analysis was used for verification of the candidate target proteins and pathways to illustrate the underlying mechanisms. Furthermore, the differentially expressed proteins (DEPs) in the enriched pathways were validated by Enzyme-linked immunosorbent assay. The results showed that the hemostasis mechanism of ZRC may be related to Platelet activation, Rap1 signaling pathway and Complement and coagulation cascades. And 10 proteins (Fermt3, ACTB, Talin, αIIbβ3, Fga, Fgb, Fgg, FXIIIb, Kng and PLC-β were identified as the target DEPs) are considered as the key factors related to hemostatic efficacy of ZRC. Thus, integrated network pharmacology and quantitative proteomics technology were applied for the effective illuminating the molecular mechanisms of Chinese material medica.

Effects of maoto (ma-huang-tang) on host lipid mediator and transcriptome signature in influenza virus infection

Maoto, a traditional kampo medicine, has been clinically prescribed for influenza infection and is reported to relieve symptoms and tissue damage. In this study, we evaluated the effects of maoto as an herbal multi-compound medicine on host responses in a mouse model of influenza infection. On the fifth day of oral administration to mice intranasally infected with influenza virus [A/PR/8/34 (H1N1)], maoto significantly improved survival rate, decreased viral titer, and ameliorated the infection-induced phenotype as compared with control mice. Analysis of the lung and plasma transcriptome and lipid mediator metabolite profile showed that maoto altered the profile of lipid mediators derived from ω-6 and ω-3 fatty acids to restore a normal state, and significantly up-regulated the expression of macrophage- and T-cell-related genes. Collectively, these results suggest that maoto regulates the host’s inflammatory response by altering the lipid mediator profile and thereby ameliorating the symptoms of influenza.

Update on treatment and preventive interventions against COVID-19: an overview of potential pharmacological agents and vaccines

The outbreak of coronavirus disease 2019 (COVID-19) triggered by the new member of the coronaviridae family, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented challenge for global health. In addition to mild to moderate clinical manifestations such as fever, cough, and fatigue, severe cases often developed lethal complications including acute respiratory distress syndrome (ARDS) and acute lung injury. Given the alarming rate of infection and increasing trend of mortality, the development of underlying therapeutic and preventive treatment, as well as the verification of its effectiveness, are the top priorities. Current research mainly referred to and evaluated the application of the empirical treatment based on two precedents, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), including antiviral drugs targeting different stages of virus replication, immunotherapy modulating the overactivated inflammation response, and other therapies such as herbal medicine and mesenchymal stem cells. Besides, the ongoing development of inventing prophylactic interventions such as various vaccines by companies and institutions worldwide is crucial to decline morbidity and mortality. This review mainly focused on promising candidates for the treatment of COVID-19 and collected recently updated evidence relevant to its feasibility in clinical practice in the near future.

Scutellaria barbata and Hedyotis diffusa herb pair for breast cancer treatment: Potential mechanism based on network pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

The Scutellaria barbata and Hedyotis diffusa (SH) herb pair is extensively used in Traditional Chinese Medicine for efficacy enhancement in cancer treatment in China and Asian countries. Superior clinical efficacy observations based on high dosages (≥60 g) motivated us to explore appropriate dosages and the underlying mechanisms of action.

AIM OF THE STUDY

To explore the efficacy and potential mechanisms of actions of SH through in vitro and in vivo experiments and network pharmacology.

MATERIALS AND METHODS

SH lyophilized powder (SHLP) was prepared from decoctions and the active ingredients were identified using high performance liquid chromatography (HPLC). Proliferation and migration experiments in vitro and tumor growth in vivo were performed to evaluate the effects of SHLP on breast cancer. Corresponding potential target genes for SHLP components and breast cancer were extracted from established databases and the Protein-Protein Internetwork of shared genes were constructed using STRING database. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation clusters were acquired and the top 30 pathways were presented. At last, as one of pathways indicated by enriched results, apoptosis was validated with flow cytometric analysis and caspase-3, 8, 9 activities.

RESULTS

Seventy-five ingredients were identified from SHLP by HPLC. High SHLP doses inhibited proliferation and migration of three types of breast cancer cells in vitro and tumor growth in nude mice. After target genes extraction and intersection, the top 30 KEGG clusters were enriched, including PI3K-Akt, cell cycle and other related pathways like VEGF, Micro-RNAs and NF-κB, besides, key genes in apoptosis were mapped. In the last, apoptosis was validated by flow cytometric analysis and caspase-3, 8, 9 activities after SHLP treatment.

CONCLUSION

High SHLP dosages inhibited breast cancer in vitro and in vivo, enriched by network pharmacology and confirmed by flow cytometric analysis and caspase activation, with apoptosis was identified as one of the mechanisms of action of SHLP. SHLP administration with higher doses is recommended for clinical usage.

A Network Pharmacology Approach to Uncover the Molecular Mechanisms of Herbal Formula Ban-Xia-Xie-Xin-Tang

Ban-Xia-Xie-Xin-Tang (BXXXT) is a classical formula from Shang-Han-Lun which is one of the earliest books of TCM clinical practice. In this work, we investigated the therapeutic mechanisms of BXXXT for the treatment of multiple diseases using a network pharmacology approach. Here three BXXXT representative diseases (colitis, diabetes mellitus, and gastric cancer) were discussed, and we focus on in silico methods that integrate drug-likeness screening, target prioritizing, and multilayer network extending. A total of 140 core targets and 72 representative compounds were finally identified to elucidate the pharmacology of BXXXT formula. After constructing multilayer networks, a good overlap between BXXXT nodes and disease nodes was observed at each level, and the network-based proximity analysis shows that the relevance between the formula targets and disease genes was significant according to the shortest path distance (SPD) and a random walk with restart (RWR) based scores for each disease. We found that there were 22 key pathways significantly associated with BXXXT, and the therapeutic effects of BXXXT were likely addressed by regulating a combination of targets in a modular pattern. Furthermore, the synergistic effects among BXXXT herbs were highlighted by elucidating the molecular mechanisms of individual herbs, and the traditional theory of "Jun-Chen-Zuo-Shi" of TCM formula was effectively interpreted from a network perspective. The proposed approach provides an effective strategy to uncover the mechanisms of action and combinatorial rules of BXXXT formula in a holistic manner.

Predicting new indications of compounds with a network pharmacology approach: Liuwei Dihuang Wan as a case study

With the ever increasing cost and time required for drug development, new strategies for drug development are highly demanded, whereas repurposing old drugs has attracted much attention in drug discovery. In this paper, we introduce a new network pharmacology approach, namely PINA, to predict potential novel indications of old drugs based on the molecular networks affected by drugs and associated with diseases. Benchmark results on FDA approved drugs have shown the superiority of PINA over traditional computational approaches in identifying new indications of old drugs. We further extend PINA to predict the novel indications of Traditional Chinese Medicines (TCMs) with Liuwei Dihuang Wan (LDW) as a case study. The predicted indications, including immune system disorders and tumor, are validated by expert knowledge and evidences from literature, demonstrating the effectiveness of our proposed computational approach.

A metabolomics approach to studying the effects of Jinxin oral liquid on RSV-infected mice using UPLC/LTQ-Orbitrap mass spectrometry

ETHNOPHARMACOLOGICAL RELEVANCE

Jinxin oral liquid (JOL) is a traditional Chinese medicine (TCM) formula modified from ma-xing-shi-gan-tang, an ancient formula widely used in the treatment of respiratory diseases such as bronchitis, pneumonia, and asthma. In our previous studies, JOL was shown to safely and effectively treat viral pneumonia, especially that involving respiratory syncytial virus (RSV).

AIM OF THE STUDY

To investigate the mechanism of the effect of JOL in RSV infected mice, using a metabolomics approach based on ultra-performance liquid chromatography coupled with linear ion trap quadrupole-Orbitrap mass spectrometry (UPLC/LTQ-Orbitrap-MS).

MATERIALS AND METHODS

BALB/c mice were divided into four groups, the control group (saline inoculation/no treatment), RSV group (RSV inoculation/saline treatment), RSV+JOL group (RSV inoculation/JOL treatment), and RSV+Riba group (RSV inoculation/ribavirin treatment). Plasma and lung tissue samples were collected 7 days after the inoculation/treatment protocols, and UPLC/LTQ-Orbitrap-MS method based on metabolomics was developed. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were utilized to identify biomarkers potentially associated with the anti-RSV activity of JOL.

RESULTS

JOL was associated with reduced inflammatory responses in RSV-infected lung tissue. The combination of PCA and OPLS-DA revealed deviations in 11 biomarkers in plasma, and 16 biomarkers in lung tissue induced by RSV that were corrected with JOL treatment. These biomarkers were primarily components of metabolic pathways involving glycerophosphocholines, sphingolipids, and glycerolipids. JOL was able to restore the abnormal levels of these biomarkers detected in the plasma and lung tissue of RSV-infected mice to approximately normal levels.

CONCLUSIONS

This study suggested that JOL can treat RSV pneumonia effectively, partially by ameliorating the associated disturbances to lipid metabolism. The results provided insight into the anti-RSV mechanism of JOL, and also demonstrated that metabolomics is a valuable tool for investigating the efficacy of TCM treatment for RSV pneumonia, and the associated biomarkers involved.

Network pharmacological identification of active compounds and potential actions of Erxian decoction in alleviating menopause-related symptoms

BACKGROUND

Erxian decoction (EXD) is used to treat menopause-related symptoms in Chinese medicine. This study aims to identify the bioactive compounds and potential actions of EXD by network pharmacological analysis.

METHODS

Two databases, the Traditional Chinese Medicine Systems Pharmacology database and TCM Database@Taiwan, were used to retrieve literature of phytochemicals of EXD. STITCH 4.0 and the Comparative Toxicogenomics Database were used to search for compound-protein and compound-gene interactions, respectively. DAVID Bioinformatics Resources 6.7 and Cytoscape 3.01 with Jepetto plugin software were used to perform a network pharmacological analysis of EXD.

RESULTS

A total of 721 compounds were identified in EXD, of which 155 exhibited 2,656 compound-protein interactions with 1,963 associated proteins determined by STITCH4.0 database, and of which 210 had 14,893 compound-gene interactions with 8,536 associated genes determined by Comparative Toxicogenomics Database. Sixty three compounds of EXD followed the Lipinski's Rule with OB ≥30% and DL index ≥0.18, of which 20 related to 34 significant pathway- or 12 gene- associated with menopause.

CONCLUSIONS

Twenty compounds were identified by network pharmacology as potential effective ingredients of EXD for relieving menopause with acceptable oral bioavailability and druggability.

Traditional Chinese medicine network pharmacology: theory, methodology and application

Traditional Chinese medicine (TCM) has a long history of viewing an individual or patient as a system with different statuses, and has accumulated numerous herbal formulae. The holistic philosophy of TCM shares much with the key ideas of emerging network pharmacology and network biology, and meets the requirements of overcoming complex diseases, such as cancer, in a systematic manner. To discover TCM from a systems perspective and at the molecular level, a novel TCM network pharmacology approach was established by updating the research paradigm from the current "one target, one drug" mode to a new "network target, multi-components" mode. Subsequently, a set of TCM network pharmacology methods were created to prioritize disease-associated genes, to predict the target profiles and pharmacological actions of herbal compounds, to reveal drug-gene-disease co-module associations, to screen synergistic multi-compounds from herbal formulae in a high-throughput manner, and to interpret the combinatorial rules and network regulation effects of herbal formulae. The effectiveness of the network-based methods was demonstrated for the discovery of bioactive compounds and for the elucidation of the mechanisms of action of herbal formulae, such as Qing-Luo-Yin and the Liu-Wei-Di-Huang pill. The studies suggest that the TCM network pharmacology approach provides a new research paradigm for translating TCM from an experience-based medicine to an evidence-based medicine system, which will accelerate TCM drug discovery, and also improve current drug discovery strategies.

Navigating traditional chinese medicine network pharmacology and computational tools

The concept of "network target" has ushered in a new era in the field of traditional Chinese medicine (TCM). As a new research approach, network pharmacology is based on the analysis of network models and systems biology. Taking advantage of advancements in systems biology, a high degree of integration data analysis strategy and interpretable visualization provides deeper insights into the underlying mechanisms of TCM theories, including the principles of herb combination, biological foundations of herb or herbal formulae action, and molecular basis of TCM syndromes. In this study, we review several recent developments in TCM network pharmacology research and discuss their potential for bridging the gap between traditional and modern medicine. We briefly summarize the two main functional applications of TCM network models: understanding/uncovering and predicting/discovering. In particular, we focus on how TCM network pharmacology research is conducted and highlight different computational tools, such as network-based and machine learning algorithms, and sources that have been proposed and applied to the different steps involved in the research process. To make network pharmacology research commonplace, some basic network definitions and analysis methods are presented.

A two-level model for the analysis of syndrome of acute ischemic stroke: from diagnostic model to molecular mechanism

Prompt and accurate diagnosis of acute ischemic stroke is critical to seek acute therapy. In traditional Chinese medicine (TCM) science, there is a comprehensive system of diagnosis and medical care of acute ischemic stroke. Here we introduce a two-level model for the analysis of TCM syndrome of acute ischemic stroke. Owing to the limitation of sample size and imbalance, we focused on the analysis of wind-phlegm collateral obstruction syndrome (Feng Tan Yu Zu Zheng). Firstly, a Support-Vector-Machine- (SVM-) based diagnostic model was set up through selection of core symptoms. After pairwise undersampling, we improved the performance of prediction and generated the core symptoms-based diagnostic model of wind-phlegm collateral obstruction syndrome. Next, Pathway Pattern-based method and MetaDrug platform were used to shed light on the molecular basis of the significance of core symptoms in three complementary aspects: symptom-gene-pathway multilayer correlation network, enriched pathways, and most relevant interaction network. The integration of diagnostic model and molecular mechanism analysis creates an interesting perspective for better understanding the syndrome. The two-level model would provide a new opportunity for the study of TCM syndromes.