About: Exploring the Active Compounds of Traditional Mongolian Medicine in Intervention of Novel Coronavirus (COVID-19) Based on Molecular Docking Method

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About: Exploring the Active Compounds of Traditional Mongolian Medicine in Intervention of Novel Coronavirus (COVID-19) Based on Molecular Docking Method Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Exploring the Active Compounds of Traditional Mongolian Medicine in Intervention of Novel Coronavirus (COVID-19) Based on Molecular Docking Method
Creator	Wang, Lu Bao, Li-Dao Wang#·, Lu Wang, J-W Yu#·, Jiu-Wang Yu, Jiu-Wang
Source	Elsevier; Medline; PMC
abstract	OBJECTIVE: This article intends to use molecular docking technology to find potential inhibitors that can respond to COVID-19 from active compounds in Mongolian medicine. METHODS: Mongolian medicine with anti-inflammatory and antiviral effects is selected from Mongolian medicine prescription preparations. TCMSP, ETCM database and document mining methods were used to collect active compounds. Swiss TargetPrediction and SuperPred server were used to find targets of compounds with smiles number. Drugbank and Genecard database were used to collect antiviral drug targets. Then the above targets were compared and analyzed to screen out antiviral targets of Mongolia medicine. Metascape database platform was used to enrich and analyze the GO (Gene ontology) annotation and KEGG pathway of the targets. In view of the high homology of gene sequences between SARS-CoV-2 S-protein RBD domain and SARS virus, as well as their similarities in pathogenesis and clinical manifestations, we established SARS-CoV-2 S-protein model using Swiss-Model. The ZDOCK protein docking software was applied to dock the S-protein with the human angiotensin ACE2 protein to find out the key amino acids of the binding site. Taking ACE2 as the receptor, the molecular docking between the active ingredients and the target protein was studied by AutoDock molecular docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-COVID-19 drugs. RESULTS: A total of 253 active components were predicted. Metascape analysis showed that key candidate targets were significantly enriched in multiple pathways related to different toxins. These key candidate targets were mainly derived from phillyrin and chlorogenic acid. Through the protein docking between S-protein and ACE2, it is found that Glu329/Gln325 and Gln42/Asp38 in ACE2 play an important role in the binding process of the two. The results of molecular docking virtual calculation showed that phillyrin and chlorogenic acid could stably combine with Gln325 and Gln42/Asp38 in ACE2, respectively, which hindered the combination between S- protein and ACE2. CONCLUSION: Phillyrin and chlorogenic acid can effectively prevent the combination of SARS-CoV-2 S-protein and ACE2 at the molecular level. Phillyrin and chlorogenic acid can be used as potential inhibitors of COVID-19 for further research and development.
has issue date	2020-05-15(xsd:dateTime)
bibo:doi	10.1016/j.jff.2020.104016
bibo:pmid	32421102
has license	no-cc
sha1sum (hex)	9f577bf9d30e119ba748f339b36df1e48810912f
schema:url	https://doi.org/10.1016/j.jff.2020.104016
resource representing a document's title	Exploring the Active Compounds of Traditional Mongolian Medicine in Intervention of Novel Coronavirus (COVID-19) Based on Molecular Docking Method
has PubMed Central identifier	PMC7225714
has PubMed identifier	32421102
schema:publication	J Funct Foods
resource representing a document's body	covid:9f577bf9d30e119ba748f339b36df1e48810912f#body_text
is schema:about of	named entity 'dock' named entity 'SARS-CoV-2' named entity 'angiotensin' named entity 'candidate' named entity 'active' named entity 'database' named entity 'enriched' named entity 'toxins' named entity 'antiviral' named entity 'Genecard' named entity 'Exploring' named entity 'ANALYZED' named entity 'MODEL' named entity 'TARGETS' named entity 'PATHWAY' named entity 'SARS-COV-2' named entity 'active ingredients' named entity 'platform' named entity 'Results' named entity 'prevent' named entity 'human' named entity 'targets' named entity 'RBD' named entity 'anti-inflammatory' named entity 'Swiss' named entity 'gene' named entity 'Method' named entity 'Traditional Mongolian Medicine' named entity 'molecular docking' named entity 'ACE2' named entity 'chlorogenic acid' named entity 'ACE2' named entity 'smiles' named entity 'ACE2' named entity 'homology' named entity 'molecular docking' named entity 'protein' named entity 'database' named entity 'KEGG' named entity 'protein' named entity 'research and development' named entity 'active ingredients' named entity 'anti-inflammatory' named entity 'chlorogenic acid' named entity 'protein' named entity 'molecular docking' named entity 'gene sequences' named entity 'RBD' named entity 'Coronavirus' named entity 'COVID' named entity 'Molecular Docking' named entity 'active' named entity 'acid' named entity 'ester' named entity 'honeysuckle' named entity 'toxic substance' named entity 'ligand' named entity 'patent medicines' named entity 'protein' named entity 'therapeutic index' named entity 'scrofula' named entity 'IL-17' named entity 'COVID' named entity 'toxin' named entity 'phillyrin' named entity 'Mongolia' named entity 'antioxidant' named entity 'categorical data' named entity 'rimantadine' named entity 'ACE2' named entity 'antipyretic' named entity 'antiinflammatory' named entity 'pharmacology' named entity 'pharmacology' named entity 'Phillyrin' named entity 'COVID-19'

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