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Introduction Angong Niuhuang Pills (AGNH), a Chinese patent medicine recommended in the “Diagnosis and Treatment Plan for COVID-19 (8th Edition),” may be clinically effective in treating COVID-19. The active components and signal pathways of AGNH through network pharmacology have been examined, and its potential mechanisms determined. Methods We screened the components in the Traditional Chinese Medicine Systems Pharmacology (TCMSP) via Drug-like properties (DL) and Oral bioavailability (OB); PharmMapper and GeneCards databases were used to collect components and COVID-19 related targets; KEGG pathway annotation and GO bioinformatics analysis were based on KOBAS3.0 database; “herb-components-targets-pathways” (H-C-T-P) network and protein-protein interaction network (PPI) were constructed by Cytoscape 3.6.1 software and STRING 10.5 database; we utilized virtual molecular docking to predict the binding ability of the active components and key proteins. Results A total of 87 components and 40 targets were screened in AGNH. The molecular docking results showed that the docking scores of the top 3 active components and the targets were all greater than 90. Conclusion Through network pharmacology research, we found that moslosooflavone, oroxylin A, and salvigenin in AGNH can combine with ACE2 and 3CL, and then are involved in the MAPK and JAK-STAT signaling pathways. Finally, it is suggested that AGNH may have a role in the treatment of COVID-19.

Objective Jinhua Qinggan Granules (JQGs) have achieved certain results in the prevention and treatment of COVID-19 in China during this coronavirus storm. In this study, we aimed to analyze the common mechanisms of JQG in the treatment of coronavirus-induced diseases, such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19 via network pharmacology and molecular docking. Methods The active compounds of JQG were collected through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The common targets associated with these 3 diseases were screened from GeneCards database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of JQG’s core targets were analyzed using The Database for Annotation, Visualization, and Integrated Discovery and KOBAS 3.0 system. Further, the protein-protein interaction network was built using STRING database. The compound-target- signaling pathway network was constructed using Cytoscape 3.7.2. The core components of JQG were docked with core targets, COVID-19 coronavirus 3 Cl hydrolase, and angiotensin-converting enzyme 2 (ACE2) via Discovery Studio 2016 software. Results A total of 139 active compounds, 50 core targets, and 122 signaling pathways were screened out. The results of molecular docking showed that arctiin and linarin had a higher docking score with 3 Cl, ACE2, and core targets of JQH for antiviral effect. Conclusion The potential mechanism of action of JHQ in the treatment of MERS, SARS, and COVID-19 may be associated with the regulation of genes co-expressed with ACE2 and immune- related signaling pathways.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), is often accompanied by injury to pulmonary function and pulmonary fibrosis. Feiluoning (FLN) is a new Chinese medicine prescription which is available for the treatment of severe and critical convalescence of COVID-19 patients. FLN also has a positive effect on pulmonary function injury and pulmonary fibrosis. We explored the potential mechanism of FLN’s effect on the convalescent treatment of COVID-19. According to the pharmacodynamic activity parameters, we screened the active chemical constituents of FLN by comparing the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The Uniprot database was used to querying the corresponding target genes, and Cytoscape 3.6.1 was used to construct a herb-compound-target network. Protein interaction analysis, target gene function enrichment analysis, and signal pathway analysis were performed using the STRING, DAVID, and Kyoto Encyclopedia of Genes and Genomes pathway databases. Molecular docking was used to predict the binding capacity of the core compound with COVID-19 hydrolase 3 Cl and angiotensin-converting enzyme 2 (ACE2). The herb-compound-target network was successfully constructed and key targets identified, including prostaglandin G/H synthase 2, estrogen receptor 1, heat shock protein HSP 90, and androgen receptor. The major affected metabolic pathways were pathways in cancer, pancreatic cancer, nonsmall cell lung cancer, and toll-like receptor signaling. The core compounds of FLN, including quercetin, luteolin, kaempferol, and stigmasterol, could strongly bind to COVID-19 3 Cl hydrolase, and other compounds, including 7-O-methylisomucronulatol and medicocarpin, could strongly bind to ACE2. Thus, it is predicted that FLN has the characteristics of a multicomponent, multitarget, and multichannel overall control compound. FLN’s mechanism of action in the treatment of COVID-19 may be associated with the regulation of inflammation and immune-related signaling pathways, and the influence of COVID-19 3 Cl hydrolase binding ability.

In the process of fighting against COVID-19 in China, Xingnaojing injection has been recommended for its clinical treatment, but the information about its active components and mechanism is still lacking. Therefore, in this work, using network pharmacology and molecular docking, we studied the active components of Xingnaojing injection having anti-COVID-19 properties. Using the DL parameter, TCMSP and CNKI databases were used to screen the active components of the Xingnaojing injection. Then, the SwissTargetPrediction webserver was used to collect the corresponding gene targets, and the gene targets related to COVID-19 were searched in the Genecards database. The DAVID database was used to enrich the function of gene targets, and the KOBAS3.0 database for the annotation of related KEGG pathways. The “components–targets–pathways” network of Xingnaojing injection was constructed with Cytoscape 3.6.1 software. The protein–protein interaction networks were analyzed using the String database. Specific proteins, SARS-COV-2 3 Cl, ACE2, and the active components were imported into Discovery Studio 2016 Client for molecular docking studies. From the Xingnaojing injection, a total of 58 active components, including Divanillalaceton and Q27139023, were screened. These were linked to 53 gene targets including mitogen-activated protein kinase 1 (MAPK1), tumor necrosis factorTNF, epidermal growth factor receptor, MAPK3, and 196 signaling pathways related to COVID-19, such as apoptosis, C-type lectin receptor signaling pathway, and hypoxia-inducible factor 1 signaling pathway. Furthermore, molecular docking studies were performed to study potential binding between the key targets and selected active components. Xingnaojing injection exhibits anti-COVID-19 effects via multiple components, multiple targets, and multiple pathways. These results set a scientific basis for further elucidation of the anti-COVID-19 mechanism of Xingnaojing injection.

Shu-Feng-Jie-Du Capsules (SFJDCs) have been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanisms of SFJDC in the treatment of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19 via network pharmacology and molecular docking. We further explored the potential application value of SFJDC in the treatment of coronavirus infection. All components of SFJDC were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The viral associated targets of the active components were forecast using the Pharmmapper database and GeneCards. The Database for Annotation, Visualization, and Integrated Discovery and KOBAS 3.0 system were used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of SFJDC’s core targets. Further, the protein–protein interaction network was built using STRING database. The herb–component network and component–target–pathway network were constructed using Cytoscape 3.7.2. The core active components of SFJDC were docked with core targets and COVID-19 coronavirus 3 Cl hydrolase and angiotensin-converting enzyme 2 (ACE2) via Discovery Studio 2016 software. A total of 110 active components were filtered from SFJDC, with 47 core targets, including epidermal growth factor receptor, mitogen-activated protein kinase 1, mitogen-activated protein kinase 3, and interleukin 6. There were 416 GO items in the GO enrichment analysis ( P < .05) and 57 signaling pathways ( P < .05) in KEGG, mainly including pathways in cancer, pancreatic cancer, colorectal cancer, apoptosis, and neurotrophin signaling pathway, among others. The results of molecular docking showed that luteolin and rhein had a higher docking score with 3 Cl, ACE2, and core targets of SFJDC for antiviral effect. SFJDC is characterized by multicomponent, multitarget, and multisignaling pathways for the treatment of coronavirus infection. The mechanism of action of SFJDC in the treatment of MERS, SARS, and COVID-19 may be associated with the regulation of genes coexpressed with ACE2 and immune- related signaling pathways.

Juechuang, a traditional Chinese herbal medicine, is originated from Rostellularia procumbens (L.) Nees. Many studies have shown that the ethyl acetate extract from Juechaung may inhibit platelet aggregation. However, the antiplatelet aggregation mechanism of Juechuang requires more systematic research. In this article, network pharmacology was used to explore the antiplatelet aggregation components and its antiplatelet aggregation mechanism. Different components were evaluated and screened by pharmacokinetic characteristics. The potential targets of active ingredients were predicted by a reverse pharmacophore matching method, and the targets were screened according to targets related to antiplatelet aggregation in the GeneCards database. Thus, an interaction network of component-target-pathway of Juechuang was generated using Cytoscape 3.2.1. software. Furthermore, the binding energy of relevant active components with key targets was calculated using a Lamarck genetic algorithm in the molecular docking calculations. Finally, the study identified 28 potentially active ingredients in Juechuang, providing further evidence that the active ingredients act on 277 targets, and 38 protein targets related to antiplatelet aggregation were screened. Through the Kyoto encyclopedia of genes and genome pathway enrichment analysis, we found that the mechanism of antiplatelet aggregation may be related to the Ras signaling pathway, platelet activation signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, etc. Via molecular docking of 2 targets, non-receptor tyrosine kinases(SRC) and MAPK were selected for molecular docking. By comparing the molecular docking results of Chinensinaphthol, Taiwanin E, Tuberculatin, Cycloeucalenol, and Justicidin B to the control drug, we found that those test molecules combined with targets and lead to high binding activity. These molecular docking results were also consistent with the literature values, and they helped identify the active ingredients and assured the reliability of the network analysis. This study may further provide a reference for the systematic study of the pharmacodynamic effect and the antiplatelet aggregation mechanism of Juechuang.

Coronavirus disease (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a highly infectious viral disease. Clinical observations have shown that Qing-Fei-Da-Yuan (QFDY) granules have good anti-COVID-19 effects, but the underlying molecular mechanisms are unclear. In this study, we explored the potential mechanism of QFDY with regard to its anti-COVID-19 effect. We first screened the active chemical constituents of QFDY based on the pharmacodynamic activity parameters, followed by screening with the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The Uniprot database was used for querying the corresponding genes of the target, and Cyoscape 3.6.1 software was used to construct the network of herb-compound-target. Protein interaction analysis, target gene function enrichment analysis, and signal pathway analysis were performed via STRING database, Database for Annotation, Visualization, and Integrated Discovery, and KEGG Pathway database. Molecular docking was used to predict the binding capacity of the core compound with COVID-19 hydrolase 3CL and angiotensin converting enzyme 2 (ACE2). The results showed that a network of herb-compound-target was successfully constructed, with key targets involving PTGS2, HSP90AA1, CAMKK2, NCOA2, and ESR1. Major metabolic pathways affected were those in cancer, procancer, nonsmall cell lung cancer, and apoptosis. The core compounds, such as quercetin, luteolin, and naringenin, showed a strong binding ability with COVID-19 3CL hydrolase; compounds such as anemasaponin C and medicocarpin showed a strong binding ability with ACE2. Thus, it is predicted that QFDY has the characteristics for multicomponent, multitarget, and multichannel overall control. The mechanism of action of QFDY in the treatment of COVID-19 may be associated with the regulation of genes co-expressed with ACE2, the regulation of inflammation and immune-related signaling pathways, and the influence of COVID-19 3CL hydrolase and ACE2 binding ability.

Mesangial proliferative glomerulonephritis (MsPGN) is characterized by mesangial cell proliferation, inflammation, and extracellular matrix deposition in the mesangial area, which develops into glomerulosclerosis and contributes to end-stage renal disease. Justicidin B is a bioactive compound isolated from Justicia procumbens L., a traditional herbal remedy that reduces proteinuria in nephritis. However, the mechanism of Justicidin B’s therapeutic effect on MsPGN remains unclear. This study was aimed to explore the positive effect of Justicidin B on MsPGN. The results showed that Justicidin B attenuated the proliferation induced by platelet-derived growth factor-BB (PDGF-BB) in MCs and blocked cell cycle progression. Likewise, inflammatory factors, including monocyte chemotactic protein 1 (MCP-1) and tumor necrosis factor alpha (TNF-α), in MCs were decreased after treatment with Justicidin B. In addition, Justicidin B exhibited antioxidant activity in PDGF-BB-induced MCs, shown by the decreased production of malondialdehyde and T-AOC, and increased the expression of superoxide dismutase. Besides, Justicidin B suppressed extracellular matrix (ECM) deposition by reducing the protein levels of collagen IV and fibronectin. Furthermore, we found that Justicidin B significantly inhibited activation of the Akt/mammalian target of rapamycin (mTOR) signaling pathway in MCs induced by PDGF-BB, but enhanced the levels of proteins in the nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase 1 (HO-1) pathway. Taken together, Justicidin B prevented PDGF-BB-induced proliferation, inflammation, oxidative stress, and ECM accumulation via regulating the activation of the Nrf2/HO-1 pathway and the Akt/mTOR signaling pathway.

Gegen Qinlian decoction (GQD) is a traditional Chinese medicine that is used to treat non-alcoholic fatty liver disease (NAFLD) in the clinic. The pharmacodynamics and cellular pathways governing the effects of GQD on NAFLD remain undefined. In this study, we investigated GQD pharmacology through assessment of its chemical constituents and evaluated and screened its components using drug likeness, pharmacokinetic characteristics (absorption, distribution, metabolism, excretion, and toxicity), and appropriate compensation mechanisms. We performed predictions of the active GQD ingredients based on reverse pharmacophore matching and compared multiple NAFLD-related genes to determine potential GQD targets. Molecular docking experiments of the active components were performed to reveal cellular targets. Annotation analysis of both target genes and related pathways were assessed through the DAVID database. Cytoscape software was used to construct a “component-target-path” network for the treatment of NAFLD by GQD. Through data analysis, 9 active GQD substances and 10 targets related to NAFLD encompassing 4 cellular pathways were identified. Data were verified through enzyme-linked immunosorbent assay and Western blot analysis. These findings provide new references for the network pharmacology of Chinese medicinal compounds and NAFLD treatment.

Yanhusuo (Corydalis Rhizoma) extracts are widely used for the treatment of pain and inflammation. The effects of Yanhusuo in pain assays were assessed in a few studies. However, there are few studies on its analgesic mechanism. In this paper, network pharmacology was used to explore the analgesic components of Yanhusuo and its analgesic mechanism. The active components of Yanhusuo were screened by TCMSP database, combined with literature data. PharmMapper and GeneCards databases were used for screening the analgesic targets of the components. The protein interaction network diagram was drawn by String database and Cytoscape software, the gene ontology and KEGG pathway analyses of the target were performed by DAVID database, and the component–target–pathway interaction network diagram was further drawn by Cytoscape3.6.1 software. System Dock Web Site verified the molecular docking among components and targets. Finally, an interaction network of the component–target–pathway of Yanhusuo was constructed, and the functions and pathways were analyzed for preliminarily investigating the mechanism of Yanhusuo in analgesia. The results showed that the active components of analgesic in Yanhusuo were Corynoline, 13-methylpalmatrubine, dehydrocorydaline, saulatine, 2,3,9,10-tetramethoxy-13-methyl-5,6-dihydroisoquinolino[2,1-b]isoquinolin-8-on-e, and Capaurine. The mechanisms were involved in metabolic pathways, PI3k-Akt signaling pathway, pathways in cancer, and so on. The top 3 targets were NOS3, glucose-6-phosphate dehydrogenase, and glucose-6-phosphate isomerase in components-target-pathways network, and they were all enriched in metabolic pathways. Meanwhile the molecular docking showed that there was a high binding activity between the 6 components and the important target proteins, as a further certification for the subsequent network analysis. This study reveals the relationship of the components, targets, and pathways of active components in Yanhusuo, and provides new ideas and methods for further research on the analgesic mechanism of Yanhusuo.