Revealing Potential Bioactive Compounds and Mechanisms of Lithospermum erythrorhizon against COVID-19 via Network Pharmacology Study

Lithospermum erythrorhizon (LE) is known in Korean traditional medicine for its potent therapeutic effect and antiviral activity. Currently, coronavirus (COVID-19) disease is a developing global pandemic that can cause pneumonia. A precise study of the infection and molecular pathway of COVID-19 is therefore obviously important. The compounds of LE were identified from the Natural Product Activity and Species Source (NPASS) database and screened by SwissADME. The targets interacted with the compounds and were selected using the Similarity Ensemble Approach (SEA) and Swiss Target Prediction (STP) methods. PubChem was used to classify targets linked to COVID-19. The protein–protein interaction (PPI) networks and signaling pathways–targets–bioactive compounds (STB) networks were constructed by RPackage. Lastly, we performed the molecular docking test (MDT) to verify the binding affinity between significant complexes through AutoDock 1.5.6. The Natural Product Activity and Species Source (NPASS) revealed a total of 82 compounds from LE, which interacted with 1262 targets (SEA and STP), and 249 overlapping targets were identified. The 19 final overlapping targets from the 249 targets and 356 COVID-19 targets were ultimately selected. A bubble chart exhibited that inhibition of the MAPK signaling pathway could be a key mechanism of LE on COVID-19. The three key targets (RELA, TNF, and VEGFA) directly related to the MAPK signaling pathway, and methyl 4-prenyloxycinnamate, tormentic acid, and eugenol were related to each target and had the most stable binding affinity. The three bioactive effects on the three key targets might be synergistic effects to alleviate symptoms of COVID-19 infection. Overall, this study shows that LE can play a role in alleviating COVID-19 symptoms, revealing that the three components (bioactive compounds, targets, and mechanism) are the most significant elements of LE against COVID-19. However, the promising mechanism of LE on COVID-19 is only predicted on the basis of mining data; the efficacy of the chemical compounds and the affinity between compounds and the targets in experiment was ignored, which should be further substantiated through clinical trials.     

Elucidating Drug-Like Compounds and Potential Mechanisms of Corn Silk (Stigma Maydis) against Obesity: A Network Pharmacology Study

Corn silk (Stigma Maydis) has been utilized as an important herb against obesity by Chinese, Korean, and Native Americans, but its phytochemicals and mechanisms(s) against obesity have not been deciphered completely. This study aimed to identify promising bioactive constituents and mechanism of action(s) of corn silk (CS) against obesity via network pharmacology. The compounds from CS were identified using Gas Chromatography Mass Spectrometry (GC-MS) and were confirmed ultimately by Lipinski’s rule via SwissADME. The relationships of the compound-targets or obesity-related targets were confirmed by public bioinformatics. The signaling pathways related to obesity, protein-protein interaction (PPI), and signaling pathways-targets-bioactives (STB) were constructed, visualized, and analyzed by RPackage. Lastly, Molecular Docking Test (MDT) was performed to validate affinity between ligand(s) and protein(s) on key signaling pathway(s). We identified a total of 36 compounds from CS via GC-MS, all accepted by Lipinski’s rule. The number of 36 compounds linked to 154 targets, 85 among 154 targets related directly to obesity-targets (3028 targets). Of the final 85 targets, we showed that the PPI network (79 edges, 357 edges), 12 signaling pathways on a bubble chart, and STB network (67 edges, 239 edges) are considered as therapeutic components. The MDT confirmed that two key activators (β-Amyrone, β-Stigmasterol) bound most stably to PPARA, PPARD, PPARG, FABP3, FABP4, and NR1H3 on the PPAR signaling pathway, also, three key inhibitors (Neotocopherol, Xanthosine, and β-Amyrone) bound most tightly to AKT1, IL6, FGF2, and PHLPP1 on the PI3K-Akt signaling pathway. Overall, we provided promising key signaling pathways, targets, and bioactives of CS against obesity, suggesting crucial pharmacological evidence for further clinical testing.     

Mechanisms of Gynostemma pentaphyllum against non‐alcoholic fibre liver disease based on network pharmacology and molecular docking

As a progressive chronic disease, the effective treatment for non‐alcoholic fibre liver disease (NAFLD) has not yet been thoroughly explored at the moment. The widespread use of Gynostemma pentaphyllum (Thunb) for its anti‐insulin resistance effect indicates that potential therapeutic value may be found in Thunb for NAFLD. Hence, this research aims to discover the latent mechanism of Thunb for NAFLD treatment. To achieve the goal of discovering the latent mechanism of Thunb for NAFLD treatment, molecular docking strategy integrated a network phamacology was adopted in the exploration. We acquire Thunb compounds with activeness from TCMSP database. We collect the putative targets of Thunb and NAFLD to generate the network. Key targets and mechanism are screened by PPI analysis, GO and KEGG pathway enrichment analyses. Molecular docking simulation is introduced into the study as assessment method. Through network analysis and virtual screening based on molecular docking, 2 targets (AKT 1 and GSK3B) are identified as key therapeutic targets with satisfying binding affinity. Main mechanism is believed to be the biological process and pathway related to insulin resistance according to the enrichment analyses outcomes. Particularly, the P13K–AKT signalling pathway is recognized as a key pathway of the mechanism. In conclusion, the study shows that Thunb could be a potential treatment against NAFLD and may suppress insulin resistance through the P13K–AKT signalling pathway. The result of the exploration provides a novel perspective for approaching experimental exploration.     

Network pharmacology and molecular docking analyses on Lianhua Qingwen capsule indicate Akt1 is a potential target to treat and prevent COVID‐19

ObjectivesCoronavirus disease 2019 (COVID‐19) is rapidly spreading worldwide. Lianhua Qingwen capsule (LQC) has shown therapeutic effects in patients with COVID‐19. This study is aimed to discover its molecular mechanism and provide potential drug targets.Materials and MethodsAn LQC target and COVID‐19–related gene set was established using the Traditional Chinese Medicine Systems Pharmacology database and seven disease‐gene databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein‐protein interaction (PPI) network were performed to discover the potential mechanism. Molecular docking was performed to visualize the patterns of interactions between the effective molecule and targeted protein.ResultsA gene set of 65 genes was generated. We then constructed a compound‐target network that contained 234 nodes of active compounds and 916 edges of compound‐target pairs. The GO and KEGG indicated that LQC can act by regulating immune response, apoptosis and virus infection. PPI network and subnetworks identified nine hub genes. The molecular docking was conducted on the most significant gene Akt1, which is involved in lung injury, lung fibrogenesis and virus infection. Six active compounds of LQC can enter the active pocket of Akt1, namely beta‐carotene, kaempferol, luteolin, naringenin, quercetin and wogonin, thereby exerting potential therapeutic effects in COVID‐19.ConclusionsThe network pharmacological strategy integrates molecular docking to unravel the molecular mechanism of LQC. Akt1 is a promising drug target to reduce tissue damage and help eliminate virus infection.     

Identification of Gut Microbiome Metabolites via Network Pharmacology Analysis in Treating Alcoholic Liver Disease

Alcoholic liver disease (ALD) is linked to a broad spectrum of diseases, including diabetes, hypertension, atherosclerosis, and even liver carcinoma. The ALD spectrum includes alcoholic fatty liver disease (AFLD), alcoholic hepatitis, and cirrhosis. Most recently, some reports demonstrated that the pathogenesis of ALD is strongly associated with metabolites of human microbiota. AFLD was the onset of disease among ALDs, the initial cause of which is alcohol consumption. Thus, we analyzed the significant metabolites of microbiota against AFLD via the network pharmacology concept. The metabolites from microbiota were retrieved by the gutMGene database; sequentially, AFLD targets were identified by public databases (DisGeNET, OMIM). The final targets were utilized for protein–protein interaction (PPI) networks and signaling pathway analyses. Then, we performed a molecular docking test (MDT) to verify the affinity between metabolite(s) and target(s) utilizing the Autodock 1.5.6 tool. From a holistic viewpoint, we integrated the relationships of microbiota-signaling pathways-targets-metabolites (MSTM) using the R Package. We identified the uppermost six key targets (TLR4, RELA, IL6, PPARG, COX-2, and CYP1A2) against AFLD. The PPI network analysis revealed that TLR4, RELA, IL6, PPARG, and COX-2 had equivalent degrees of value (4); however, CYP1A2 had no associations with the other targets. The bubble chart showed that the PI3K-Akt signaling pathway in nine signaling pathways might be the most significant mechanism with antagonistic functions in the treatment of AFLD. The MDT confirmed that Icaritin is a promising agent to bind stably to RELA (known as NF-Κb). In parallel, Bacterium MRG-PMF-1, the PI3K-Akt signaling pathway, RELA, and Icaritin were the most significant components against AFLD in MSTM networks. In conclusion, we showed that the Icaritin–RELA complex on the PI3K-Akt signaling pathway by bacterial MRG-PMF-1 might have promising therapeutic effects against AFLD, providing crucial evidence for further research.     

Exploring the mechanism of ellagic acid against gastric cancer based on bioinformatics analysis and network pharmacology

Ellagic acid (EA) is a natural polyphenolic compound. Recent studies have shown that EA has potential anticancer properties against gastric cancer (GC). This study aims to reveal the potential targets and mechanisms of EA against GC. This study adopted methods of bioinformatics analysis and network pharmacology, including the weighted gene co-expression network analysis (WGCNA), construction of protein–protein interaction (PPI) network, receiver operating characteristic (ROC) and Kaplan–Meier (KM) survival curve analysis, Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, molecular docking and molecular dynamics simulations (MDS). A total of 540 EA targets were obtained. Through WGCNA, we obtained a total of 2914 GC clinical module genes, combined with the disease database for screening, a total of 606 GC-related targets and 79 intersection targets of EA and GC were obtained by constructing Venn diagram. PPI network was constructed to identify 14 core candidate targets; TP53, JUN, CASP3, HSP90AA1, VEGFA, HRAS, CDH1, MAPK3, CDKN1A, SRC, CYCS, BCL2L1 and CDK4 were identified as the key targets of EA regulation of GC by ROC and KM curve analysis. The enrichment analysis of GO and KEGG pathways of key targets was performed, and they were mainly enriched in p53 signalling pathway, PI3K-Akt signalling pathway. The results of molecular docking and MDS showed that EA could effectively bind to 13 key targets to form stable protein–ligand complexes. This study revealed the key targets and molecular mechanisms of EA against GC and provided a theoretical basis for further study of the pharmacological mechanism of EA against GC.     

Anti–coronavirus disease 2019 (COVID-19) targets and mechanisms of puerarin

The present study aimed to uncover the pharmacological function and underlying mechanism of puerarin as a potential treatment for COVID-19, using an in silico methodology, including network pharmacology and molecular docking. The pivotal targets of puerarin to treat COVID-19 were identified and included the epidermal growth factor receptor (EGFR), tumour necrosis factor (TNF), tumour protein p53 (TP53), caspase 3 (CASP3), RELA proto-oncogene (RELA), Fos proto-oncogene (FOS), caspase 8 (CASP8), prostaglandin-endoperoxide synthase 2 (PTGS2), interleukin 2 (IL2), protein kinase CB (PRKCB), B cell lymphoma/leukaemia gene-2 (BCL2), protein kinase CA (PRKCA), nitric oxide synthase 3 (NOS3) and peroxisome proliferator–activated receptor gamma (PPARG). Functionally, the anti–COVID-19 action of puerarin was associated with the suppression of oxidative stress and inflammatory cascades, and cell apoptosis. The signalling pathways of puerarin to treat COVID-19 included modulation of the pathways of apoptosis, IL-17 signalling, mitogen-activated protein kinase (MAPK) signalling and TNF signalling. Molecular docking data illustrated the binding capacity of puerarin with COVID-19 and the effective anti–COVID-19 activity of puerarin. Taken together, our current network pharmacology–based findings revealed the pharmacological role of puerarin in the treatment of COVID-19. Furthermore, the bioinformatic findings elucidated that some of these pivotal targets might serve as potential molecular markers for detecting COVID-19.     

Effect of dapagliflozin on diabetic patients with cardiovascular disease via MAPK signalling pathway

Clinical studies have shown that dapagliflozin can reduce cardiovascular outcome in patients with type 2 diabetes mellitus (T2DM), but the exact mechanism is unclear. In this study, we used the molecular docking and network pharmacology methods to explore the potential mechanism of dapagliflozin on T2DM complicated with cardiovascular diseases (CVD). Dapagliflozin's potential targets were predicted via the Swiss Target Prediction platform. The pathogenic targets of T2DM and CVD were screened by the Online Mendelian Inheritance in Man (OMIM) and Gene Cards databases. The common targets of dapagliflozin, T2DM and CVD were used to establish a protein-protein interaction (PPI) network; the potential protein functional modules in the PPI network were found out by MCODE. Metascape tool was used for Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis. A potential protein functional module with the best score was obtained from the PPI network and 9 targets in the protein functional module all showed good binding properties when docking with dapagliflozin. The results of KEGG pathway enrichment analysis showed that the underlying mechanism mainly involved AGE-RAGE signalling pathway in diabetic complications, TNF signalling pathway and MAPK signalling pathway. Significantly, the MAPK signalling pathway was considered as the key pathway. In conclusion, we speculated that dapagliflozin played a therapeutic role in T2DM complicated with CVD mainly through MAPK signalling pathway. This study preliminarily reveals the possible mechanism of dapagliflozin in the treatment of T2DM complicated with CVD and provides a theoretical basis for future clinical research.     

New Insight into Drugs to Alleviate Atopic March via Network Pharmacology-Based Analysis

In the present study, a subject of atopic dermatitis (AD) is exposed progressively to allergic rhinitis (AR) and asthma (AS), which is defined as atopic march (AM). However, both the targets and compounds against AM are still largely unknown. Hence, we investigated the overlapping targets related directly to the occurrence and development of AD, AR, and AS through public databases (DisGeNET, and OMIM). The final overlapping targets were considered as key targets of AM, which were visualized by a Venn diagram. The protein–protein interaction (PPI) network was constructed using R package software. We retrieved the association between targets and ligands via scientific journals, and the ligands were filtered by physicochemical properties. Lastly, we performed a molecular docking test (MDT) to identify the significant ligand on each target. A total of 229 overlapping targets were considered as AM causal elements, and 210 out of them were interconnected with each other. We adopted 65 targets representing the top 30% highest in degree centrality among 210 targets. Then, we obtained 20 targets representing the top 30% greatest in betweenness centrality among 65 targets. The network analysis unveiled key targets against AM, and the MDT confirmed the affinity between significant compounds and targets. In this study, we described the significance of the eight uppermost targets (CCL2, CTLA4, CXCL8, ICAM1, IL10, IL17A, IL1B, and IL2) and eight ligands (Bindarit, CTLA-4 inhibitor, Danirixin, A-205804, AX-24 HCl, Y-320, T-5224, and Apilimod) against AM, providing a scientific basis for further experiments.     

基于网络药理学与分子对接技术的清瘟护肺颗粒防治新型冠状病毒肺炎(COVID-19)的潜在药效物质研究

本文通过网络药理学和分子对接技术探讨清瘟护肺颗粒防治新型冠状病毒肺炎(COVID-19)的潜在药效物质.首先,通过TCMSP数据库,BATMAN-TCM数据库及TCMIP数据库检索清瘟护肺颗粒中十六味药的化学成分及作用靶点,利用GeneCards和OMIM数据库检索COVID-19的相关疾病靶点.然后,通过venny2...     

Potential role of nicotinamide analogues against SARS-COV-2 target proteins

Background and objectiveCoronavirus 2019 (COVID-19) is caused by ‘severe acute respiratory syndrome coronavirus 2′ (SARS-CoV-2), first reported in Wuhan, China in December 2019, which eventually became a global disaster. Various key mediators have been reported in the pathogenesis of COVID-19. However, no effective pharmacological intervention has been available to combat COVID-19 complications. The present study screens nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN) as potential inhibitors of this present generation coronavirus infection using an in-silico approach.Materials and methodsThe SARS-CoV-2 proteins (nucleocapsid, proteases, post-fusion core, phosphatase, endoriboruclease) and ACE-2 protein were selected. The 2D structure of nicotinamide ribonucleoside and nicotinamide ribonucleotide was drawn using ChemDraw 14.0 and saved in .cdx format. The results were analyzed using two parameters: full fitness energy and binding free energy (ΔG).ResultsThe full fitness energy and estimated ΔG values from docking of NM, and NMN with selected SARS-CoV-2 target proteins, ADMET prediction and Target prediction indicate the interaction of NR and NMN in the treatment of COVID-19.ConclusionsBased on full fitness energy and estimated ΔG values from docking studies of NM and NAM with selected SARS-CoV-2 target proteins, ADME prediction, target prediction and toxicity prediction, we expect a possible therapeutic efficacy of NR in the treatment of COVID-19.Keyword: COVID-19, SARS-CoV-2, Molecular docking, Poly (ADP-ribose) polymerase enzyme, Nicotinamide     

Network pharmacology for the identification of phytochemicals in traditional Chinese medicine for COVID-19 that may regulate interleukin-6

Objective: ´Three formulas and three medicines,’ namely, Jinhua Qinggan Granule, Lianhua Qingwen Capsule, Xuebijing Injection, Qingfei Paidu Decoction, HuaShi BaiDu Formula, and XuanFei BaiDu Granule, were proven to be effective for coronavirus disease 2019 (COVID-19) treatment. The present study aimed to identify the active chemical constituents of this traditional Chinese medicine (TCM) and investigate their mechanisms through interleukin-6 (IL-6) integrating network pharmacological approaches.Methods: We collected the compounds from all herbal ingredients of the previously mentioned TCM, but those that could down-regulate IL-6 were screened through the network pharmacology approach. Then, we modeled molecular docking to evaluate the binding affinity between compounds and IL-6. Furthermore, we analyzed the biological processes and pathways of compounds. Finally, we screened out the core genes of compounds through the construction of the protein–protein interaction network and the excavation of gene clusters of compounds.Results: The network pharmacology research showed that TCM could decrease IL-6 using several compounds, such as quercetin, ursolic acid, luteolin, and rutin. Molecular docking results showed that the molecular binding affinity with IL-6 of all compounds except γ-aminobutyric acid was < −5.0 kJ/mol, indicating the potential of numerous active compounds in TCM to directly interact with IL-6, leading to an anti-inflammation effect. Finally, Cytoscape 3.7.2 was used to topologize the biological processes and pathways of compounds, revealing potential mechanisms for COVID-19 treatment.Conclusion: These results indicated the positive effect of TCM on the prevention and rehabilitation of COVID-19 in at-risk people. Quercetin, ursolic acid, luteolin, and rutin could inhibit COVID-19 by down-regulating IL-6.     

A proteomic atlas of ligand–receptor interactions at the ovine maternal–fetal interface reveals the role of histone lactylation in uterine remodeling

Well-orchestrated maternal–fetal cross talk occurs via secreted ligands, interacting receptors, and coupled intracellular pathways between the conceptus and endometrium and is essential for successful embryo implantation. However, previous studies mostly focus on either the conceptus or the endometrium in isolation. The lack of integrated analysis impedes our understanding of early maternal–fetal cross talk. Herein, focusing on ligand–receptor complexes and coupled pathways at the maternal–fetal interface in sheep, we provide the first comprehensive proteomic map of ligand–receptor pathway cascades essential for embryo implantation. We demonstrate that these cascades are associated with cell adhesion and invasion, redox homeostasis, and the immune response. Candidate interactions and their physiological roles were further validated by functional experiments. We reveal the physical interaction of albumin and claudin 4 and their roles in facilitating embryo attachment to endometrium. We also demonstrate a novel function of enhanced conceptus glycolysis in remodeling uterine receptivity by inducing endometrial histone lactylation, a newly identified histone modification. Results from in vitro and in vivo models supported the essential role of lactate in inducing endometrial H3K18 lactylation and in regulating redox homeostasis and apoptotic balance to ensure successful implantation. By reconstructing a map of potential ligand–receptor pathway cascades at the maternal–fetal interface, our study presents new concepts for understanding molecular and cellular mechanisms that fine-tune conceptus–endometrium cross talk during implantation. This provides more direct and accurate insights for developing potential clinical intervention strategies to improve pregnancy outcomes following both natural and assisted conception.     

SARS-CoV-2病毒感染潜在关键分子生物标志物及免疫浸润特征分析

应用生物信息学方法筛选新型冠状病毒肺炎（corona virus disease 2019,COVID-19）感染的潜在关键分子生物标志物并分析其免疫浸润特征。从GEO数据库下载GSE152418数据集,其中COVID-19患者17例,健康对照17例。用加权基因共表达网络分析（weighted gene co-expression network analysis,WGCNA）方法筛选出COVID-19最相关的模块基因。与差异基因取交集得到共同基因,进行功能及信号通路富集分析,构建蛋白互作网络筛选关键基因,构建关键基因的miRNATF-mRNA调控网络,用CIBERSORT算法预测样本免疫细胞浸润特征。差异分析得到2 049个差异基因。WGCNA分析7个模块中“土耳其蓝色”模块与COVID-19相关性最高（r=0.91,P<0.001）。模块中基因显著性和模块隶属度呈显著正相关（r=0.96,P<0.001）。得到共同基因766个,主要参与有丝分裂、微管结合、阳离子通道活性及卵母细胞减数分裂、细胞衰老等。蛋白互作网络筛选到前10位关键基因分别为CDK1、BUB1、CCNA2...     

基于网络药理学探讨丹参-丹皮配伍抗脑缺血损伤的作用机制

本文旨在通过网络药理学和分子对接方法探讨丹参-丹皮活性成分治疗脑卒中的潜在分子机制.首先基于中药系统药理学分析平台筛选丹参、丹皮的活性成分及其作用靶点,利用CTD、TTD和GeneCards数据库收集脑卒中相关靶点.然后将药物和疾病靶点取交集,借助STRING数据库获取靶点间相互作用关系,利用R语言的Cluster-P...     

Network Pharmacology and Molecular Docking Reveal the Mechanism of Corydalis saxicola Bunting Total Alkaloids in Treating Radiation-Induced Oral Mucositis

The study aims to explore the effect and mechanism of total alkaloids of Corydalis saxicola Bunting (CSBTA) in the treatment of radiation induced oral mucositis (RIOM) through network pharmacology and molecular docking. The components and corresponding targets of Corydalis saxicola Bunting were screened by literature review. RIOM related targets were obtained in GeneCards. Cytoscape software was used to construct the component-target-pathway network. Protein-Protein Interaction (PPI) networks was constructed by String database. GO and KEGG enrichment analyses were performed by Metascape. AutoDock Vina 4.2 software was used for molecular docking. There were 26 components of CSBTA targeting 61 genes related to RIOM. Through Cytoscape and PPI analysis, 15 core target genes of CSBTA for treating RIOM were identified. GO functional analysis indicated that CSBTA might play a role through kinase binding and protein kinase activation. KEGG pathway analysis showed that the core targets of CSBTA were mainly focused on cancer and reactive oxygen species (ROS) pathway. The results of molecular docking showed that CSBTA had strong binding energy with target protein including SRC, AKT and EGFR. The study demonstrates that CSBTA may treat RIOM by affecting SRC, AKT and EGFR through ROS pathway.     

Network Pharmacology and Molecular Docking Combined to Analyze the Molecular and Pharmacological Mechanism of Pinellia ternata in the Treatment of Hypertension

Hypertension is a cardiovascular disease that causes great harm to health and life, affecting the function of important organs and accompanied by a variety of secondary diseases, which need to be treated with drugs for a long time. P. ternata alone or combination with western medicine has played an important role in traditional Chinese medicine. Although P. ternata is used clinically to treat hypertension, its functional molecular mechanism and pharmacological mechanism have not been elucidated. Therefore, in this study, the potentially effective components, and targets of P. ternata in the treatment of hypertension were screened by the method of network pharmacology, and the mechanism of P. ternata in the treatment of hypertension was analyzed by constructing a component-target relationship network, PPI interaction network, targets’ function analysis, and molecular docking. In the study, 12 potentially effective components and 88 targets were screened, and 3 potential protein modules were found and analyzed after constructing a PPI network using targets. In addition, 10 targets were selected as core targets of the PPI network. After that, the targets were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the molecular docking method is used to study the interaction between the targets and the active components. The above evidence shows that the mechanism of P. ternata in the treatment of hypertension is complicated, as it acts in many ways, mainly by affecting nerve signal transmission, cell proliferation, and apoptosis, calcium channels, and so on. The binding between targets and active components mainly depends on Pi bonds and hydrogen bonds. Using the method of network pharmacology and molecular docking to analyze the mechanism of P. ternata in the treatment of hypertension will help to provide a better scientific basis for the combined use of traditional Chinese medicine and western medicine, and will better help to improve the quality of P. ternata and point out its direction.     

Network pharmacology analysis of the therapeutic mechanisms of the traditional Chinese herbal formula Lian Hua Qing Wen in Corona virus disease 2019 (COVID-19), gives fundamental support to the clinical use of LHQW

BackgroundThe traditional Chinese Medicine (TCM) herbal formula Lian Hua Qing Wen (LHQW) improves the results of COVID-19 treatment. Three very recent studies analyzed with network pharmacology some working mechanisms of LHQW. However, we used more techniques and also included Angiotensin converting enzyme 2 (ACE2) (a SARS-CoV receptor, possibly the viral entry point in alveolar lung cells) and the immune system, as cytokine storm is essential in the late phase.PurposeExtensive detailed Network Pharmacology analysis of the LHQW- treatment mechanism in COVID-19.MethodsTCM-herb-meridian and protein interaction network (PIN) of LHQW, based on LHQW herbs meridian information and the protein-protein interaction (PPI) information of the LHQW-component targets. Hub and topological property analyses to obtain crucial targets and construct the crucial LHQW-PIN. Functional modules determination using MCODE, GO and KEGG pathway analysis of biological processes and pathway enrichment. Intersection calculations between the LHQW-proteins and ACE2 co-expression-proteins.ResultsLHQW herbs have relationships to Stomach-, Heart-, Liver- and Spleen-systems, but most (10 of the 13 herbs) to the Lung system, indicating specific effects in lung diseases. The crucial LHQW PIN has the scale-free property, contains 2,480 targets, 160,266 PPIs and thirty functional modules. Six modules are enriched in leukocyte-mediated immunity, the interferon-gamma-mediated signaling pathway, immune response regulating signaling pathway, interleukin 23 mediated signaling pathway and Fc gamma receptor-mediated phagocytosis (GO analysis). These 6 are also enriched in cancer, immune system-, and viral infection diseases (KEGG). LHQW shared 189 proteins with ACE2 co-expression proteins.ConclusionsDetailed network analysis shows, that LHQW herbal TCM treatment modulates the inflammatory process, exerts antiviral effects and repairs lung injury. Moreover, it also relieves the “cytokine storm” and improves ACE2-expression-disorder-caused symptoms. These innovative findings give a rational pharmacological basis and support for treating COVID-19 and possibly other diseases with LHQW.