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

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).

Interactions of Co, Cu, and non-metal phthalocyanines with external structures of SARS-CoV-2 using docking and molecular dynamics.

The new coronavirus, SARS-CoV-2, caused the COVID-19 pandemic, characterized by its high rate of contamination, propagation capacity, and lethality rate. In this work, we approach the use of phthalocyanines as an inhibitor of SARS-CoV-2, as they present several interactive properties of the phthalocyanines (Pc) of Cobalt (CoPc), Copper (CuPc) and without a metal group (NoPc) can interact with SARS-CoV-2, showing potential be used as filtering by adsorption on paints on walls, masks, clothes, and air conditioning filters. Molecular modeling techniques through Molecular Docking and Molecular Dynamics were used, where the target was the external structures of the virus, but specifically the envelope protein, main protease, and Spike glycoprotein proteases. Using the g_MM-GBSA module and with it, the molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics provided information on the root-mean-square deviation of the atomic positions provided values between 1 and 2.5. The generalized Born implicit solvation model, Gibbs free energy, and solvent accessible surface area approach were used. Among the results obtained through molecular dynamics, it was noticed that interactions occur since Pc could bind to residues of the active site of macromolecules, demonstrating good interactions; in particular with CoPc. Molecular couplings and free energy showed that S-gly active site residues interacted strongly with phthalocyanines with values ​​of - 182.443 kJ/mol (CoPc), 158.954 kJ/mol (CuPc), and - 129.963 kJ/mol (NoPc). The interactions of Pc's with SARS-CoV-2 may predict some promising candidates for antagonists to the virus, which if confirmed through experimental approaches, may contribute to resolving the global crisis of the COVID-19 pandemic.

Hormones Nanofiltration in Carbon Nanotubes and Boron Nitride Nanotubes Using Uniform External Electric Field Through Molecular Dynamics.

Hormones are a dangerous group of molecules that can cause harm to humans. This study based on classical molecular dynamics proposes the nanofiltration of wastewater contaminated by hormones from a computer simulation study, in which the water and the hormone were filtered in two single-walled nanotube compositions. The calculations were carried out by changing the intensities of the electric field that acted as a force exerting pressure on the filtration along the nanotube, in the simulation time of 100 ps. The hormones studied were estrone, estradiol, estriol, progesterone, ethinylestradiol, diethylbestrol, and levonorgestrel in carbon nanotubes (CNTs) and boron nitride (BNNTs). The most efficient nanofiltrations were for fields with low intensities in the order of 10-8 au and 10-7 au. The studied nanotubes can be used in membranes for nanofiltration in water treatment plants due to the evanescent field potential caused by the action of the electric field inside. Our data showed that the action of EF in conjunction with the van der Walls forces of the nanotubes is sufficient to generate the attractive potential. Evaluating the transport of water molecules in CNTs and BNNTs, under the influence of the electric field, a sequence of simulations with the same boundary conditions was carried out, seeking to know the percentage of water molecules filtered in the nanotubes.

Density functional theory for the thermodynamic gas-phase investigation of butanol biofuel and its isomers mixed with gasoline and ethanol.

Herein, we present the results of our study on the thermodynamic properties of the isomers of butanol (n-butanol, 2-butanol, i-butanol, and t-butanol) to evaluate their thermodynamic potential as a complementary biofuel and/or substitute for ethanol and gasoline. The Gaussian09W software was used to perform molecular geometry optimization calculations using density functional theory with the B3lyp hybrid function using the base set 6-311++g(d,p) and the compound methods G3, G4, and CBS-QB3. Calculations of the fundamental frequency of the molecules were performed to obtain the molecular vibration modes for the respective frequencies. These calculations provided thermodynamic parameters such as the entropy, enthalpy, and specific molar heat at constant pressure, all as a function of the temperature. The parameter values obtained by each method were compared to the experimental values available in the literature. The results showed good accuracy, especially those obtained at the B3lyp/6-311++g(d,p) level for n-butanol. The error between the theoretical and experimental values for the combustion enthalpy of n-butanol was less than 4% at 298.15 K; due to the good prediction of its thermodynamic properties, we used n-butanol as a model for the prediction of other thermodynamic properties. We started a molecular docking study of four ligands, namely, n-butanol, ethanol, propanol, heptane, isooctane, and methanol interacting with butanol isomers. The highest values of affinity energy found were for N-butanol. The possible formation of hydrogen bonds, associations by means of London forces, hydrogen, and alkyl interactions were analyzed. n-Butanol was added to ethanol-gasoline mixtures in the temperature range of 298.15 to 600 K and the results suggest that n-butanol has a higher calorific value than gasoline-ethanol mixtures in G30E, G40E, G50E, G60E, G70E, G80E, G90E, and E100 blends. As such, n-butanol releases greater amounts of heat during combustion and is thus a viable alternative to biofuels.