Evidence map›Paper›PMID 38858279›Full record

ArticleJournal of molecular modeling2024

Molecular interactions of the Omicron, Kappa, and Delta SARS-CoV-2 spike proteins with quantum dots of graphene oxide.

Tiago da Silva Arouche, Julio Cesar Mendes Lobato, Rosivaldo Dos Santos Borges, Mozaniel Santana de Oliveira, Antonio Maia de Jesus Chaves Neto

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Article in Journal of molecular modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Tiago da Silva AroucheLaboratory of Preparation and Computing of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belém, PA, 66075-110, Brazil.
Julio Cesar Mendes LobatoLaboratory of Preparation and Computing of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belém, PA, 66075-110, Brazil.
Rosivaldo Dos Santos BorgesUniversidade Federal do Pará, Departamento de Farmácia/Laboratório de Química Farmacêutica, Belem, PA, 66075-110, Brazil.
Mozaniel Santana de OliveiraMuseu Paraense Emílio Goeldi. Av. Gov Magalhães Barata, 376 - São Braz, Belém, PA, 66040-170, Brazil.
Antonio Maia de Jesus Chaves NetoLaboratory of Preparation and Computing of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belém, PA, 66075-110, Brazil. amchaves@ufpa.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextThe Omicron, Kappa, and Delta variants are different strains of the SARS-CoV-2 virus. Graphene oxide quantum dots (GOQDs) represent a burgeoning class of oxygen-enriched, zero-dimensional materials characterized by their sub-20-nm dimensions. Exhibiting pronounced quantum confinement and edge effects, GOQDs manifest exceptional physical-chemical attributes. This study delves into the potential of graphene oxide quantum dots, elucidating their inherent properties pertinent to the surface structures of SARS-CoV-2, employing an integrated computational approach for the repositioning of inhibitory agents.

methodsFollowing rigorous adjustment tests, a spectrum of divergent bonding conformations emerged, with particular emphasis placed on identifying the conformation exhibiting optimal adjustment scores and interactions. The investigation employed molecular docking simulations integrating affinity energy evaluations, electrostatic potential clouds, molecular dynamics encompassing average square root calculations, and the computation of Gibbs-free energy. These values quantify the strength of interaction between GOQDs and SARS-CoV-2 spike protein variants. The receptor structures were optimized using the CHARM-GUI server employing force field AMBERFF14SB. The algorithm embedded in CHARMM offers an efficient interpolation scheme and automatic step size selection, enhancing the efficiency of the optimization process. The 3D structures of the ligands are constructed and optimized with density functional theory (DFT) method based on the most stable conformer of each binder. Autodock Vina Software (ADV) was utilized, where essential parameters were specified. Electrostatic potential maps (MEPs) provide a visual depiction of molecules' charge distributions and related properties. After this, molecular dynamics simulations employing the CHARM36 force field in Gromacs 2022.2 were conducted to investigate GOs' interactions with surface macromolecules of SARS-CoV-2 in an explicit aqueous environment. Furthermore, our investigation suggests that lower values indicate stronger binding. Notably, GO-E consistently showed the most negative values across interactions with different variants, suggesting a higher affinity compared to other GOQDs (GO-A to GO-D).

Indexed as

GraphiteMolecular Docking SimulationMolecular Dynamics SimulationQuantum DotsSARS-CoV-2Spike Glycoprotein, CoronavirusCOVID-19HumansProtein BindingStatic Electricitygraphene oxideGraphiteSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2COVID-19Molecular dockingMolecular dynamicsQuantum dotsSARS-CoV-2

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.