Supervisor(s): Central Station of Chinese Medicinal Materials Information Sponsor(s): Central Station of Chinese Medicinal Materials Information; State Food and Drug Administration CN：44-1286/R
Journal of Chinese Medicinal Materials is supervised by Central Station of Chinese Medicinal Materials Information and sponsored by Central Station of Chinese Medicinal Materials Information and State Food and Drug Administration. The journal covers research article of Chinese herbal medicine planting and raising technology, resource exploitation and utilization, concocted processing maintenance of medicinal herbs, identification, ingredient, pharmacology, preparations, and pharmacy.
The journal is included in CA, JST and CSCD.
Objective: To explore the potential active ingredients and action mechanism of Weixuening mixture in the prevention and treatment of novel coronavirus pneumonia (COVID-19) based on network pharmacology and molecular docking technology.
Methods: The main chemical components and targets in Weixuening mixture were collected using TCMSP database, and the overlay analysis of targets was performed by comparison with disease targets of coronavirus infection. The medicinal–compound–target network was constructed using Cytoscape software, and the DAVID database was used to perform gene ontology (GO) enrichment and KEGG pathway enrichment analysis. The molecular docking technology was used to virtually screen the Weixuening mixture active ingredients interacting with SARS-CoV-2 S protein, human ACE2 protein, and SARS-CoV-2 3CL hydrolase (3CLpro), and thus the potential anti-SARS-COV-2 components of Weixuening mixture were predicted.
Results: A total of 326 components and 555 related targets were combed out from Weixuening mixture. Among them, 35 targets corresponding to 101 components were closely related to COVID-19. The target pathway enrichment analysis showed that Weixuening mixture mainly acted on infectious diseases, inflammatory response, and immune regulation. The molecular docking results indicated that the 16 components showed good binding effects with S protein, ACE2, and 3CLpro. The components were mainly steroids, fatty acids, and phenols.
Conclusion: Weixuening mixture may play a potential role in preventing and treating COVID-19 via regulating the immune and inflammatory responses.
Objective To explore the pharmacodynamic basis and mechanism of Huashi Baidu Formula in the treatment of novel coronavirus pneumonia (COVID-19) by network pharmacology and molecular docking, so as to provide evidences for the treatment of COVID-19 with TCM.
Methods The chemical components and potential targets of Huashi Baidu Formula were screened by TCMSP database. The disease targets were screened by the GeneCards database; Cytoscape 3.7.2 software was used to construct the “drug-component-target-disease” interaction network of Huashi Baidu Formula and potential target interactions. GO and KEGG pathway analyses were carried out. At last, the main active components of Huashi Baidu Formula were verified by molecular docking with 3 CL hydrolase (Mpro) and angiotensin conversion enzyme Ⅱ (ACE2) of COVID-19.
Results Totally 138 active components in Huashi Baidu Formula were mainly involved in the treatment of this disease by regulating 59 key targets, such as IL6, MAPK3, MAPK8, CASP3, IL10, MAPK1, CCL2, and IL2, regarding a total of 1,751 biological processes, 27 cell components, 82 molecular functions and 153 signaling pathways, such as IL-17 signaling pathway, NF-κB signaling pathway, Toll-like receptor signaling pathway, and renin-angiotensin system. The results of molecular docking showed that baicalein was the best combination with Mpro in Huashi Baidu Formula and the best combination with ACE2 was glycyrol.
Conclusion Huashi Baidu Formula has the characteristics of comprehensive regulation of “multi-component-multi-target-multi-pathway” in the treatment of COVID-19, and the mechanism in the treatment of critically ill patients is mainly related to the intervention of “RAS pathway-cytokine storm-severe crisis”.
Objective To explore the mechanism of Shufeng Jiedu Capsule in the treatment of COVID-19 based on network pharmacology and molecular docking.
Methods The active components and action targets of Shufeng Jiedu Capsule were obtained from TCMSP platform. The drug’s nature, flavor and channel tropism were obtained from the 2015 edition of
Chinese Pharmacopoeia. The relevant target genes of COVID-19 were obtained from GeneCards database and the therapeutic target was obtained from the intersection of the obtained target genes and the action targets of Shufeng Jiedu Capsule. The protein–protein interaction (PPI) network was obtained by uploading the therapeutic target value to STRING database. Cytoscape was used to construct and analyze the network of medicinal materials–nature, flavor and channel tropism, the network of medicinal materials–active components–therapeutic targets and the PPI network. ClusterProfiler package in RStudio was adopted for GO and KEGG functional enrichment analysis.
Results The eight traditional Chinese medicinal materials in Shufeng Jiedu Capsule mainly attributed to the lung, liver and stomach meridians, bitter in flavor and cold in nature. The results showed that 179 active components corresponded to 272 targets, and there were 53 common target genes with COVID-19. MAPK14 and PTGS2 were the common key genes in the network of medicinal materials–active components–therapeutic targets and the PPI network. GO enrichment resulted in 1 408 biological processes, 60 molecular functions and 22 cell components. Totally 155 pathways were obtained by KEGG functional enrichment, and 11 of the top 20 pathways were related to viral, bacterial and parasitic infections, such as Chagas disease, hepatitis B, toxoplasmosis, leishmaniasis and influenza A. Three of them were related to inflammatory immunity, namely IL-17 signaling pathway, TNF signaling pathway and Th17 cell differentiation. Eighteen compounds with inhibitory activity against SARS-CoV-2 3CL and 158 compounds with inhibitory activity against ACE2 were screened by molecular docking.
Conclusion COVID-19 can be treated with Shufeng Jiedu Capsule through multiple components, multiple targets and multiple pathways, and its mechanism may be related to the regulation of immune–inflammatory response, antiviral infection, etc. Its active ingredients have the potential to resist SARS-CoV-2 and interfere with the possible binding of SARS-CoV-2 to ACE2.
ObjectiveTo investigate the potential active components and mechanism of Shengjiang Powder in the treatment of coronavirus disease 2019 (COVID-19) based on structural similarity, network pharmacology and molecular docking techniques.
Methods From the database, the active components and the predicted targets of Shengjiang Powder were obtained, and the key targets were obtained by docking with the COVID-19 gene set in the CTD database. The key protein-protein interaction (PPI) network was constructed and the core targets were screened. The key targets were enriched and analyzed to explore the mechanism of action, followed by verification using molecular docking.
Results There were 39 active ingredients and 95 key targets. A total of 1 844 entries were enriched in biological processes (BPs); 104 entries were enriched in molecular functions (MFs); 63 entries were enriched in cellular components (CCs); 160 entries were enriched in pathways. Molecular docking results showed that phenylalanine, bassianin, and beauverolide Ea had good affinities with ACE2 and 3CLpro.
Conclusion The core compounds of Shengjiang Powder can theoretically inhibit the cytokine storm caused by virus invasion through structural intervention and multi-target and multi-pathway regulation, which has provided the theoretical basis for further research.
Objective To predict the binding modes of the main active components (indigo and indirubin) of Indigo Naturalis to 2019-nCoV/ACE2 complex based on molecular docking technology and molecular dynamics simulation and explore the intervention effect of Indigo Naturalis on COVID-19.
Methods The crystal structures of receptors and 2D structures of small-molecule ligands were obtained from the protein crystal structure databank and the traditional Chinese medicine database. Autodock Vina 1.1.2 program was used for molecular docking and preliminary analysis of the binding situation, and the optimal conformation was obtained. AmberTools18.0 software was used to perform molecular dynamics simulation and complete free energy calculation, hydrogen bond analysis, etc., to further verify the binding mode.
Results The data results showed that indigo and indirubin could bind to 2019-nCoV/ACE2 complex, and both systems shared a similar binding mode.
Conclusion: This study predicts that Indigo Naturalis may have a therapeutic effect on COVID-19 by interfering with 2019-nCoV/ACE2 complex.
ObjectiveTo study the mechanism of corona virus disease 2019 (COVID-19) treated with Jinhua Qinggan Granule by network pharmacology.
Methods TCMSP, TCM Database@Taiwan, TCMID, and literature search were used to screen the main active ingredients. The potential therapeutic targets of Jinhua Qinggan Granule were searched by using Swiss Target Prediction and TCMSP database. The related disease genes of COVID-19 were searched by Genecards, and the drug targets and disease genes were mapped. The core genes were visualized and screened by Cytoscape 3.6.0 software and the potential therapeutic targets were analyzed by GO and KEGG pathways.
Results There were 300 main effective components of Jinhua Qinggan Granule, involving 414 target proteins. There were 346 disease targets related to COVID-19, 47 of which were potential targets for Jinhua Qinggan Granule to treat COVID-19. Through the GO and KEGG pathway enrichment analysis, it was found that the efficacy of Jinhua Qinggan Granule in the treatment of COVID-19 was achieved by antivirus, immunoinflammatory regulation, and apoptosis regulation via the PI3 K-Akt, HIF-1, TNF, MAPK, and NF-κB signaling pathways. The key genes of Jinhua Qinggan Granule in the treatment of COVID-19 were MAPK1, CASP3, TP53, ALB, TNF, IL6, MAPK8, and MAPK14.
Conclusion Based on network pharmacology, it was found that the mechanism of action of Jinhua Qinggan Granule in the treatment of COVID-19 involves multiple targets and multiple pathways, which may be related to its efficacy in inhibiting the virus, regulating immunity, inhibiting inflammation and regulating apoptosis.
Objective To explore the potential molecular biological mechanism of Maxing Yigan Decoction in the treatment of new coronavirus disease (COVID-19) based on network pharmacology.
Methods The active compounds of the four Chinese herbs in Maxing Yigan Decoction and their targets were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and a drug molecule-target network was constructed. The TTD and GeneCards databases were used to screen the COVID-19 targets, and the STRING platform was used to build a drug-disease target interaction network. Network topology analysis was carried out on the core targets. Based on David database, the core target proteins were subjected to GO and KEGG pathway enrichment analysis, and the multi-dimensional network diagram of active components, targets and pathways of Maxing Yigan Decoction was constructed.
Results With oral availability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 as the screening conditions, a total of 76 active ingredients and 1 159 potential drug targets were obtained. Quercetin, delphinidin, luteolin and sitosterol, the main active ingredients in Maxing Yigan Decoction, were involved in the airway inflammation. A total of 251 disease targets were collected from the disease database using the key word "novel coronavirus pneumonia". According to the (degree) value, the core target proteins of Maxing Yigan Decoction against COVID-19 were screened out. GO analysis and KEGG analysis were carried out on the 25 targets of Maxing Yigan Decoction acting on COVID-19, and 215 biological processes (BPs), 29 cell compositions (CCs) and 30 molecular functions (MFs) were obtained by GO analysis. KEGG analysis revealed 87 pathways such as HIF-1 signaling pathway and TNF signaling pathway.
Conclusion This study predicts the mechanism of Maxing Yigan Decoction in the treatment of COVID-19, which has provided references for further revealing of its mechanism of action and clinical use.
Objective: To investigate the targets and molecular mechanism of Rhizoma Atractylodis in treating corona virus disease 2019 (COVID-19) based on network pharmacology.
Methods The effective components and corresponding targets of Rhizoma Atractylodis were screened using TCMSP platform, and the relevant targets of COVID-19 were screened by NCBI and GenCards databases. The intersections of the two were taken as the core targets of Rhizoma Atractylodis for the treatment of COVID-19. The gene ontology (GO) functional enrichment analysis and KEGG pathway analysis were carried out on the intersection targets using DAVID database, and the network diagram of the active component-core target-action pathway of Rhizoma Atractylodis was constructed.
Results Nine active compounds and 59 corresponding targets in Rhizoma Atractylodis were obtained, and 251 related targets of COVID-19 were obtained. 19 core targets were obtained by mapping. Through KEGG analysis, 51 related pathways were identified, mainly involving pathways in cancer, sphingolipid signaling pathway, PI3K-Akt signaling pathway, neurotrophin signaling pathway, and TNF signaling pathway.
Conclusion The active compounds of Rhizoma Atractylodis act on RELA, PIK3CG, TNF, IL-6, BCL2, MAPK14, CASP3, CXCL8, TP53, BAX, and NOS2 through multiple pathways, thus exhibiting its therapeutic activities against COVID-19.
