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

• Published in: Journal of molecular modeling Vol. 30; no. 7; p. 203
• Main Authors: da Silva Arouche, Tiago, Lobato, Julio Cesar Mendes, dos Santos Borges, Rosivaldo, de Oliveira, Mozaniel Santana, de Jesus Chaves Neto, Antonio Maia
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-07-2024; Springer Nature B.V
• Subjects: Affinity; Algorithms; Aqueous environments; Bonding agents; Characterization and Evaluation of Materials; Charge distribution; Chemistry; Chemistry and Materials Science; Computer Appl. in Life Sciences; Computer Applications in Chemistry; COVID-19 - virology; Density functional theory; Edge effect; Free energy; Graphene; Graphite - chemistry; Humans; Inhibitors; Molecular docking; Molecular Docking Simulation; Molecular dynamics; Molecular Dynamics Simulation; Molecular interactions; Molecular Medicine; Original Paper; Oxygen enrichment; Protein Binding; Proteins; Quantum confinement; Quantum dots; Quantum Dots - chemistry; SARS-CoV-2 - chemistry; Severe acute respiratory syndrome coronavirus 2; Spike Glycoprotein, Coronavirus - chemistry; Spike Glycoprotein, Coronavirus - metabolism; Static Electricity; Theoretical and Computational Chemistry; COVID-19; Molecular dynamics; SARS-CoV-2; Quantum dots; Molecular docking
• ISSN: 1610-2940; 0948-5023; 0948-5023
• DOI: 10.1007/s00894-024-05996-z

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).