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10.21037/apm-20-1759 http://scihub22266oqcxt.onion/10.21037/apm-20-1759 33691446!ä!33691446 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Ann+Palliat+Med 2021 ; 10 (4): 3864-3895 Nephropedia Template TP {{tp|p=33691446|t=2021. The pharmacological mechanism of Huashi Baidu Formula for the treatment of COVID-19 by combined network pharmacology and molecular docking |pdf=|usr=}}{{33691446}} gab.com Text The pharmacological mechanism of Huashi Baidu Formula for the treatment of COVID-19 by combined network pharmacology and molecular docking JO: Ann Palliat Med http://www.kidney.de/pget.php?&tw=1&pmid=33691446 #FOAvip BACKGROUND: Huashi Baidu Formula (HSBDF) is a traditional Chinese medicine formula consisting of fourteen parts, which has been proven effective for treating coronavirus disease 2019 (COVID-19) clinically. However, the therapeutic mechanism of the effect of HSBDF on COVID-19 remains unclear. METHODS: The components and action targets of HSBDF were searched in the TCMSP, YaTCM, PubChem, and TargetNet databases. Disease targets related to ACE2 were screened in single-cell sequence data of colon epithelial cells from other reports. The therapeutic targets of HSBDF for COVID-19 were obtained by integrated analysis, and the protein-protein interaction was analyzed using the STRING database. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) processes were analyzed using the OmicsBean and Metascape databases. The communication between networks [component-target (C-T) network, component-target-pathway (C-T-P) network, herb-target (H-T) network, target-pathway (T-P) network, and meridian-tropism (M-T) network] was constructed by Cytoscape software. The Cloud computing molecular docking platform was used to verify the molecular docking. RESULTS: The obtained 223 active ingredients and 358 targets of HSBDF. The 5,555 COVID-19 disease targets related to ACE2 were extracted, and 84 compound-disease common targets were found, of which the principal targets included ACE, ESR1, ADRA1A, and HDAC1. A total of 3,946 items were seized by GO enrichment analysis, mainly related to metabolism, protein binding, cellular response to the stimulus, and receptor activity. The enriched KEGG pathways screened 46 signaling pathways, including the renin-angiotensin system, the renin secretion, NF-kappa B pathway, the arachidonic acid metabolism, and the AMPK signaling pathway. The molecular docking results showed that the bioactive components of HSBDF have an excellent binding ability with main proteins related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). CONCLUSIONS: HSBDF might act on SARS-CoV-2 through multiple components, targets, and pathways. Here we reveal preliminary results of the mechanism of action of HSBDF on SARS-CoV-2, providing a theoretical basis for future clinical applications. Twit Text FOAVip The pharmacological mechanism of Huashi Baidu Formula for the treatment of COVID-19 by combined network pharmacology and molecular docking ????Ann Palliat Med http://www.kidney.de/pget.php?&tw=1&pmid=33691446 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33691446 #FOAvip English Wikipedia <ref>{{Cite pmid|33691446}}</ref> The pharmacological mechanism of Huashi Baidu Formula for the treatment of COVID-19 by combined network pharmacology and molecular docking #MMPMID33691446 Cai Y; Zeng M; Chen YZ Ann Palliat Med 2021[Apr]; 10 (4): 3864-3895 PMID33691446show ga BACKGROUND: Huashi Baidu Formula (HSBDF) is a traditional Chinese medicine formula consisting of fourteen parts, which has been proven effective for treating coronavirus disease 2019 (COVID-19) clinically. However, the therapeutic mechanism of the effect of HSBDF on COVID-19 remains unclear. METHODS: The components and action targets of HSBDF were searched in the TCMSP, YaTCM, PubChem, and TargetNet databases. Disease targets related to ACE2 were screened in single-cell sequence data of colon epithelial cells from other reports. The therapeutic targets of HSBDF for COVID-19 were obtained by integrated analysis, and the protein-protein interaction was analyzed using the STRING database. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) processes were analyzed using the OmicsBean and Metascape databases. The communication between networks [component-target (C-T) network, component-target-pathway (C-T-P) network, herb-target (H-T) network, target-pathway (T-P) network, and meridian-tropism (M-T) network] was constructed by Cytoscape software. The Cloud computing molecular docking platform was used to verify the molecular docking. RESULTS: The obtained 223 active ingredients and 358 targets of HSBDF. The 5,555 COVID-19 disease targets related to ACE2 were extracted, and 84 compound-disease common targets were found, of which the principal targets included ACE, ESR1, ADRA1A, and HDAC1. A total of 3,946 items were seized by GO enrichment analysis, mainly related to metabolism, protein binding, cellular response to the stimulus, and receptor activity. The enriched KEGG pathways screened 46 signaling pathways, including the renin-angiotensin system, the renin secretion, NF-kappa B pathway, the arachidonic acid metabolism, and the AMPK signaling pathway. The molecular docking results showed that the bioactive components of HSBDF have an excellent binding ability with main proteins related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). CONCLUSIONS: HSBDF might act on SARS-CoV-2 through multiple components, targets, and pathways. Here we reveal preliminary results of the mechanism of action of HSBDF on SARS-CoV-2, providing a theoretical basis for future clinical applications. |*COVID-19[MESH] |*Drugs, Chinese Herbal/pharmacology/therapeutic use[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH]The pharmacological mechanism of Huashi Baidu Formula for the treatmen(epmc).pdf DeepDyve Pubget Overpricing