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dc.contributor.authorMuhammad, S.
dc.contributor.authorMaqbool, M. F.
dc.contributor.authorAl-Sehemi, A. G.
dc.contributor.authorIqbal, A.
dc.contributor.authorKhan, M.
dc.contributor.authorUllah, S.
dc.contributor.authorKhan, M. T.
dc.date.accessioned2021-09-07T06:38:10Z
dc.date.available2021-09-07T06:38:10Z
dc.date.issued2021-09-03
dc.identifier.citationMuhammad, S., Maqbool, M. F., Al-Sehemi, A. G., Iqbal, A., Khan, M., Ullah, S., & Khan, M. T. (2023). A threefold approach including quantum chemical, molecular docking and molecular dynamic studies to explore the natural compounds from Centaurea jacea as the potential inhibitors for COVID-19. Brazilian Journal of Biology, 83. doi:10.1590/1519-6984.247604
dc.identifier.issn1678-4375
dc.identifier.issn1519-6984
dc.identifier.doi10.1590/1519-6984.247604
dc.identifier.urihttp://hdl.handle.net/10754/670972
dc.description.abstractAbstract In the current report, we studied the possible inhibitors of COVID-19 from bioactive constituents of Centaurea jacea using a threefold approach consisting of quantum chemical, molecular docking and molecular dynamic techniques. Centaurea jacea is a perennial herb often used in folk medicines of dermatological complaints and fever. Moreover, anticancer, antioxidant, antibacterial and antiviral properties of its bioactive compounds are also reported. The Mpro (Main proteases) was docked with different compounds of Centaurea jacea through molecular docking. All the studied compounds including apigenin, axillarin, Centaureidin, Cirsiliol, Eupatorin and Isokaempferide, show suitable binding affinities to the binding site of SARS-CoV-2 main protease with their binding energies -6.7 kcal/mol, -7.4 kcal/mol, -7.0 kcal/mol, -5.8 kcal/mol, -6.2 kcal/mol and -6.8 kcal/mol, respectively. Among all studied compounds, axillarin was found to have maximum inhibitor efficiency followed by Centaureidin, Isokaempferide, Apigenin, Eupatorin and Cirsiliol. Our results suggested that axillarin binds with the most crucial catalytic residues CYS145 and HIS41 of the Mpro, moreover axillarin shows 5 hydrogen bond interactions and 5 hydrophobic interactions with various residues of Mpro. Furthermore, the molecular dynamic calculations over 60 ns (6×106 femtosecond) time scale also shown significant insights into the binding effects of axillarin with Mpro of SARS-CoV-2 by imitating protein like aqueous environment. From molecular dynamic calculations, the RMSD and RMSF computations indicate the stability and dynamics of the best docked complex in aqueous environment. The ADME properties and toxicity prediction analysis of axillarin also recommended it as safe drug candidate. Further, in vivo and in vitro investigations are essential to ensure the anti SARS-CoV-2 activity of all bioactive compounds particularly axillarin to encourage preventive use of Centaurea jacea against COVID-19 infections.
dc.description.sponsorshipThe authors extend their appreciation to the Institute of Research and Consulting Studies at King Khalid University for supporting this research through grant number 2-N-20/22 and the support of Research Center for Advanced Materials Science is highly acknowledged. For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia.
dc.publisherFapUNIFESP (SciELO)
dc.relation.urlhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842023000100219&tlng=en
dc.rightsArchived with thanks to Brazilian Journal of Biology
dc.titleA threefold approach including quantum chemical, molecular docking and molecular dynamic studies to explore the natural compounds from Centaurea jacea as the potential inhibitors for COVID-19
dc.typeArticle
dc.identifier.journalBrazilian Journal of Biology
dc.eprint.versionPost-print
dc.contributor.institutionKing Khalid University, Saudi Arabia
dc.contributor.institutionUniversity of the Punjab, Pakistan
dc.contributor.institutionKing Khalid University, Saudi Arabia; King Khalid University, Saudi Arabia
dc.contributor.institutionUniversity of Veterinary and Animal Sciences, Pakistan
dc.contributor.institutionThe University of Lahore, Pakistan
dc.identifier.volume83
kaust.acknowledged.supportUnitSupercomputing Laboratory at King Abdullah University of Science and Technology (KAUST)


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