Computational investigation of natural compounds as potential main protease (M<sup>pro</sup>) inhibitors for SARS-CoV-2 virus
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388955%3A_____%2F22%3A00564990" target="_blank" >RIV/61388955:_____/22:00564990 - isvavai.cz</a>
Result on the web
<a href="https://hdl.handle.net/11104/0336561" target="_blank" >https://hdl.handle.net/11104/0336561</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.compbiomed.2022.106318" target="_blank" >10.1016/j.compbiomed.2022.106318</a>
Alternative languages
Result language
angličtina
Original language name
Computational investigation of natural compounds as potential main protease (M<sup>pro</sup>) inhibitors for SARS-CoV-2 virus
Original language description
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significantly impacting human lives, overburdening the healthcare system and weakening global economies. Plant-derived natural compounds are being largely tested for their efficacy against COVID-19 targets to combat SARS-CoV-2 infection. The SARS-CoV-2 Main protease (Mpro) is considered an appealing target because of its role in replication in host cells. We curated a set of 7809 natural compounds by combining the collections of five databases viz Dr Duke's Phytochemical and Ethnobotanical database, IMPPAT, PhytoHub, AromaDb and Zinc. We applied a rigorous computational approach to identify lead molecules from our curated compound set using docking, dynamic simulations, the free energy of binding and DFT calculations. Theaflavin and ginkgetin have emerged as better molecules with a similar inhibition profile in both SARS-CoV-2 and Omicron variants.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10403 - Physical chemistry
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computers in Biology Medicine
ISSN
0010-4825
e-ISSN
1879-0534
Volume of the periodical
151
Issue of the periodical within the volume
DEC 2022
Country of publishing house
GB - UNITED KINGDOM
Number of pages
11
Pages from-to
106318
UT code for WoS article
000900239300004
EID of the result in the Scopus database
2-s2.0-85142318385