2021
DOI: 10.1016/j.compbiomed.2021.104692
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Tracking the interaction between single-wall carbon nanotube and SARS-Cov-2 spike glycoprotein: A molecular dynamics simulations study

Abstract: COVID-19, a newly discovered type of coronavirus, is the cause of the pandemic infection that was first reported in Wuhan, China, in December 2019. One of the most critical problems in this regard is to identify innovative drugs that may reduce or manage this global health concern. Nanoparticles have shown a pivotal role in drug delivery systems in recent decades. The surface of nanoparticles could be covered by a layer composed of different biomolecules (e.g., proteins and macromolecules) following the incuba… Show more

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Cited by 32 publications
(21 citation statements)
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“…Therefore, it is evident that the carbon nanoparticles employed in this study exhibited better binding energy towards the prioritized SARS-CoV-2 targets. There are several studies recently published on the binding potential of carbon-based nanomaterials towards viruses and helps in the detection of viral pathogens or as antiviral agents to viral pandemics including COVID19 ( Reina et al, 2020 ; Shao et al, 2021 ; Serrano-Aroca et al, 2021 ; Jomhori et al, 2021 ; Riley and Narayan, 2021 ).…”
Section: Resultsmentioning
confidence: 99%
“…Therefore, it is evident that the carbon nanoparticles employed in this study exhibited better binding energy towards the prioritized SARS-CoV-2 targets. There are several studies recently published on the binding potential of carbon-based nanomaterials towards viruses and helps in the detection of viral pathogens or as antiviral agents to viral pandemics including COVID19 ( Reina et al, 2020 ; Shao et al, 2021 ; Serrano-Aroca et al, 2021 ; Jomhori et al, 2021 ; Riley and Narayan, 2021 ).…”
Section: Resultsmentioning
confidence: 99%
“…It has a wide range of applications i.e. used to estimate the binding energy for proteins in different studies including SARS-CoV-2 and neurological disorders [ [38] , [39] , [40] , [41] , [42] , [43] ].…”
Section: Methodsmentioning
confidence: 99%
“…All MD trajectories were analyzed using UCSF Chimera, PyMol ( http://www.pymol.org ) and GROMACS. GROMACS modules such as g_rmsd, g_rmsf, g_hbond, g_energy, g_gyrate, and g_sasa were utilized to analyze the stability and behavior of each system [ [53] , [54] , [55] ].…”
Section: Methodsmentioning
confidence: 99%