About: Molecular Modelling Investigation for Drugs and Nutraceuticals against Protease of SARS-CoV-2

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Molecular Modelling Investigation for Drugs and Nutraceuticals against Protease of SARS-CoV-2 Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Molecular Modelling Investigation for Drugs and Nutraceuticals against Protease of SARS-CoV-2
Creator	Poovorawan, Yong Suwannakarn, Kamol Kodchakorn, Kanchanok Kongtawelert, Kongtawelert, Prachya
Source	Elsevier; PMC
abstract	The widespread problem of a 2019-novel coronavirus (SARS-CoV-2) strain outbreak in Wuhan, China has prompted a search for new drugs to protect against and treat this disease. It is necessary to immediately investigate this due to the mutation of the viral genome and there being no current protective vaccines or therapeutic drugs. Molecular modelling and molecular docking based on in silico screening strategies were employed to determine the potential activities of seven HIV protease (HIV-PR) inhibitors, two flu drugs, and eight natural compounds. The computational approach was carried out to discover the structural modes with a high binding affinity for these drugs on the homology structure of the Wuhan coronavirus protease (SARS-CoV-2 PR). From the theoretical calculations, all the drugs and natural compounds demonstrated various favourable binding affinities. An interesting finding was that the natural compounds tested had a higher potential binding activity with the pocket sites of SARS-CoV-2 PR compared to the groups of HIV-PR inhibitors. The binding modes of each complex illustrated between the drugs and compounds interacted with the functional group of amino acids in the binding pocket via hydrophilic, hydrophobic, and hydrogen bond interactions using the molecular dynamics simulation technique. This result supports the idea that existing protease inhibitors and natural compounds could be used to treat the new coronavirus. This report sought to provide fundamental knowledge as preliminary experimental data to propose an existing nutraceutical material against viral infection. Collectively, it is suggested that molecular modelling and molecular docking are suitable tools to search and screen for new drugs and natural compounds that can be used as future treatments for viral diseases.
has issue date	2020-08-18(xsd:dateTime)
bibo:doi	10.1016/j.jmgm.2020.107717
has license	no-cc
sha1sum (hex)	c594ad6abca6c373c661930b1a7bc1d87596a906
schema:url	https://doi.org/10.1016/j.jmgm.2020.107717
resource representing a document's title	Molecular Modelling Investigation for Drugs and Nutraceuticals against Protease of SARS-CoV-2
has PubMed Central identifier	PMC7434411
schema:publication	J Mol Graph Model
resource representing a document's body	covid:c594ad6abca6c373c661930b1a7bc1d87596a906#body_text
is schema:about of	named entity '2019' named entity 'Center' named entity 'inhibitors' named entity 'Stem Cells' named entity 'free energy' named entity 'Nutraceuticals' named entity 'COMPLEXES' named entity 'Molecular dynamics' named entity 'Molecular dynamics' named entity 'complexes' named entity 'problem' named entity 'suggestions' named entity 'theoretical calculation' named entity 'Molecular dynamics simulation' named entity 'SARS-CoV-2' named entity 'free energy calculation' named entity 'SARS-CoV-2' named entity 'SARS-CoV-2' named entity 'Nutraceuticals' named entity 'SARS-CoV-2' named entity 'binding affinity' named entity 'essential amino acid' named entity 'herbal drugs' named entity 'free energy' named entity 'nutraceuticals' named entity 'protease inhibitor' named entity 'hesperidin' named entity 'free energy' named entity 'kcal' named entity 'protein-ligand' named entity 'therapeutic drugs' named entity 'amino acid' named entity 'flu' named entity 'natural products' named entity 'herbal drugs' named entity 'RNA polymerase' named entity 'antiviral activity' named entity 'low affinity' named entity 'non-polar' named entity 'kcal' named entity 'kcal' named entity 'molecular docking' named entity 'hesperidin' named entity 'vaccines' named entity 'viral genome' named entity 'lopinavir' named entity 'kcal' named entity 'binding affinity' named entity 'amino acid' named entity 'binding affinity' named entity 'therapeutic agents' named entity 'Sesamin' named entity 'kcal' named entity 'protein' named entity 'viral infections' named entity 'AutoDock Vina' named entity 'SARS-CoV' named entity 'SARS-CoV-2' named entity 'infection' named entity 'binding complex' named entity 'bioactive' named entity 'remdesivir' named entity 'Binding affinity' named entity 'HIV' named entity 'Wuhan' named entity 'Wuhan' named entity 'molecular docking' named entity 'remdesivir' named entity 'interact' named entity 'assay' named entity 'hesperidin' named entity 'molecular modelling' named entity 'herbal medicines' named entity 'protein' named entity 'genomes' named entity 'coronavirus' named entity 'van der Waals' named entity 'kcal' named entity 'lopinavir'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software