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Molecular interactions of the Omicron, Kappa, and Delta SARS-CoV-2 spike proteins with quantum dots of graphene oxide.
da Silva Arouche, Tiago; Lobato, Julio Cesar Mendes; Dos Santos Borges, Rosivaldo; de Oliveira, Mozaniel Santana; de Jesus Chaves Neto, Antonio Maia.
Afiliación
  • da Silva Arouche T; Laboratory of Preparation and Computing of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belém, PA, 66075-110, Brazil.
  • Lobato JCM; Laboratory of Preparation and Computing of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belém, PA, 66075-110, Brazil.
  • Dos Santos Borges R; Graduate Program in Natural Resources Engineering of the Amazon, ITEC, Federal University of Pará, C. P. 2626, Belém, PA, 66050-540, Brazil.
  • de Oliveira MS; Universidade Federal do Pará, Departamento de Farmácia/Laboratório de Química Farmacêutica, Belem, PA, 66075-110, Brazil.
  • de Jesus Chaves Neto AM; Museu Paraense Emílio Goeldi. Av. Gov Magalhães Barata, 376 - São Braz, Belém, PA, 66040-170, Brazil.
J Mol Model ; 30(7): 203, 2024 Jun 11.
Article en En | MEDLINE | ID: mdl-38858279
ABSTRACT
CONTEXT The 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.

METHODS:

Following 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).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Puntos Cuánticos / Simulación de Dinámica Molecular / Simulación del Acoplamiento Molecular / Glicoproteína de la Espiga del Coronavirus / SARS-CoV-2 / Grafito Límite: Humans Idioma: En Revista: J Mol Model Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Puntos Cuánticos / Simulación de Dinámica Molecular / Simulación del Acoplamiento Molecular / Glicoproteína de la Espiga del Coronavirus / SARS-CoV-2 / Grafito Límite: Humans Idioma: En Revista: J Mol Model Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Alemania