Anthraquinolone and quinolizine derivatives as an alley of future treatment for COVID-19: an in silico machine learning hypothesis.
Sci Rep
; 11(1): 17915, 2021 09 09.
Article
in English
| MEDLINE | ID: covidwho-1402117
ABSTRACT
Coronavirus disease 2019 (Covid-19), caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), has come to the fore in Wuhan, China in December 2019 and has been spreading expeditiously all over the world due to its high transmissibility and pathogenicity. From the outbreak of COVID-19, many efforts are being made to find a way to fight this pandemic. More than 300 clinical trials are ongoing to investigate the potential therapeutic option for preventing/treating COVID-19. Considering the critical role of SARS-CoV-2 main protease (Mpro) in pathogenesis being primarily involved in polyprotein processing and virus maturation, it makes SARS-CoV-2 main protease (Mpro) as an attractive and promising antiviral target. Thus, in our study, we focused on SARS-CoV-2 main protease (Mpro), used machine learning algorithms and virtually screened small derivatives of anthraquinolone and quinolizine from PubChem that may act as potential inhibitor. Prioritisation of cavity atoms obtained through pharmacophore mapping and other physicochemical descriptors of the derivatives helped mapped important chemical features for ligand binding interaction and also for synergistic studies with molecular docking. Subsequently, these studies outcome were supported through simulation trajectories that further proved anthraquinolone and quinolizine derivatives as potential small molecules to be tested experimentally in treating COVID-19 patients.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Antiviral Agents
/
Quinolizines
/
Anthraquinones
/
SARS-CoV-2
/
COVID-19 Drug Treatment
Type of study:
Prognostic study
Limits:
Humans
Language:
English
Journal:
Sci Rep
Year:
2021
Document Type:
Article
Affiliation country:
S41598-021-97031-x
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