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Naslov:Natural flavonoid pectolinarin computationally targeted as a promising drug candidate against SARS-CoV-2
Avtorji:ID Rani, Mukta (Avtor)
ID Chouhan, Raghuraj S., Institut "Jožef Stefan" (Avtor)
ID Singh, Rajesh K. (Avtor), et al.
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://www.sciencedirect.com/science/article/pii/S2665928X23000260?via%3Dihub
 
.pdf PDF - Predstavitvena datoteka, prenos (5,57 MB)
MD5: 8DFF7BB52BEA7B728D6D2BA95ABF3DCE
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo IJS - Institut Jožef Stefan
Povzetek:Coronavirus disease-2019 (COVID-19) has become a global pandemic, necessitating the development of new medicines. In this investigation, we identified potential natural flavonoids and compared their inhibitory activity against spike glycoprotein, which is a target of SARS-CoV-2 and SARS-CoV. The target site for the interaction of new inhibitors for the treatment of SARS-CoV-2 has 82% sequence identity and the remaining 18% dissimilarities in RBD S1-subunit, S2-subunit, and 2.5% others. Molecular docking was employed to analyse the various binding processes used by each ligand in a library of 85 natural flavonoids that act as anti-viral medications and FDA authorised treatments for COVID-19. In the binding pocket of the target active site, remdesivir has less binding interaction than pectolinarin, according to the docking analysis. Pectolinarin is a natural flavonoid isolated from Cirsiumsetidensas that has anti-cancer, vasorelaxant, anti-inflammatory, hepatoprotective, anti-diabetic, anti-microbial, and anti-oxidant properties. The S-glycoprotein RBD region (330–583) is inhibited by kaempferol, rhoifolin, and herbacetin, but the S2 subunit (686–1270) is inhibited by pectolinarin, morin, and remdesivir. MD simulation analysis of S-glycoprotein of SARS-CoV-2 with pectolinarin complex at 100ns based on high dock-score. Finally, ADMET analysis was used to validate the proposed compounds with the highest binding energy.
Ključne besede:coronaviruses, SARS-CoV-2, S-glycoproteins, computational analysis
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:19.09.2023
Datum sprejetja članka:11.12.2023
Datum objave:15.12.2023
Založnik:Elsevier
Leto izida:2024
Št. strani:str. 1-12
Številčenje:Vol. ,7 [article no.] 100120
Izvor:Nizozemska
PID:20.500.12556/DiRROS-24734 Novo okno
UDK:577
ISSN pri članku:2665-928X
DOI:10.1016/j.crstbi.2023.100120 Novo okno
COBISS.SI-ID:178467075 Novo okno
Avtorske pravice:© 2023 The Authors.
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 20. 12. 2023; Soavtor iz Slovenije: R. S. Chouhan;
Datum objave v DiRROS:16.12.2025
Število ogledov:13
Število prenosov:10
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Current research in structural biology
Založnik:Elsevier B.V.
ISSN:2665-928X
COBISS.SI-ID:56381955 Novo okno

Licence

Licenca:CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
Opis:Najbolj omejujoča licenca Creative Commons. Uporabniki lahko prenesejo in delijo delo v nekomercialne namene in ga ne smejo uporabiti za nobene druge namene.
Začetek licenciranja:15.12.2023
Vezano na:VoR

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:računalniška analiza


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