Results Of Molecular Dynamics Simulations Research Articles

Designing Robust Superhydrophobic Materials for Inhibiting Nucleation of Clathrate Hydrates by Imitating Glass Sponges.

Superhydrophobic surfaces are suggested to deal with hydrate blockage because they can greatly reduce adhesion with the formed hydrates. However, they may promote the formation of fresh hydrate nuclei by inducing an orderly arrangement of water molecules, further aggravating hydrate blockage and meanwhile suffering from their fragile surfaces. Here, inspired by glass sponges, we report a robust anti-hydrate-nucleation superhydrophobic three-dimensional (3D) porous skeleton, perfectly resolving the conflict between inhibiting hydrate nucleation and superhydrophobicity. The high specific area of the 3D porous skeleton ensures an increase in terminal hydroxyl (inhibitory groups) content without damaging the superhydrophobicity, achieving the inhibition to fresh hydrates and antiadhesion to formed hydrates. Molecular dynamics simulation results indicate that terminal hydroxyls on a superhydrophobic surface can inhibit the formation of hydrate cages by disordering the arrangement of water molecules. And experimental data prove that the induction time of hydrate formation was prolonged by 84.4% and the hydrate adhesive force was reduced by 98.7%. Furthermore, this porous skeleton still maintains excellent inhibition and antiadhesion properties even after erosion for 4 h at 1500 rpm. Therefore, this research paves the way toward developing novel materials applied in the oil and gas industry, carbon capture and storage, etc.

Experimental and computational investigation on performances of the thermoplastic elastomer SEBS/Poly(lactic acid) blends

Poly(lactic acid) (PLA) was toughened by the thermoplastic elastomer of poly(styrene-ethylene-butadiene-styrene) (SEBS) and SEBS-grafted-maleic anhydride (SEBS-MAH). The toughening effect, the compatibility, as well as the corresponding mechanism with different content of SEBS or SEBS-MAH were investigated using experimental and simulation methods. As a result, the toughness effect became obvious with the increase of SEBS or SEBS-MAH content. Especially, for the PLA, SEBS/PLA(30/70), and SEBS-MAH/PLA(30/70) blends, the Shao D hardness decreased from 84.5 to 78.6 and 75, respectively. The tensile strength decreased from 51.0 MPa to 35.3 MPa and 31.3 MPa, while the breaking elongation increased from 13.0 % to 28.6 % and 31.9 %, the impact strength increased from 3.2 kJ/m2 to 4.0 kJ/m2 and 8.0 kJ/m2, respectively. Except that, the results of IR, DSC, and SEM revealed the addition of SEBS-MAH improved the toughness and compatibility more effectively than SEBS, on the basis of chemical bonding between SEBS-MAH and PLA molecular chains (SEBS-MAH-PLA). Moreover, according to molecular dynamics simulation results, the movement ability and flexibility of the molecular chains gradually increased with the increase of SEBS-MAH content, on the basis of Mean square displacement and Radius of gyration results. The compatibility between PLA and SEBS-MAH-PLA also got improved, as reflected by the solubility parameter, which increased from 13.982 ± 0.034 (J/cm3)0.5 for SEBS to 15.931 ± 0.087 (J/cm3)0.5 for SEBS-MAH-PLA. Further, the mechanical properties of each group of the sample were clarified from the characteristic parameters including E, B, G, B/G, as well as Poisson's ratio υ.

Phosphatidylcholine in the tear film of the eye: Enhanced topical delivery of fluorometholone to the eye

In this study, the ability of the phosphatidylcholine (PC) molecule, which is in the tear films in human eyes, to release the fluorometholone (FLU) drug from the sulfobutylether-β-cyclodextrin (SBE-β-CD) carrier, is investigated. The binding energy obtained from the density functional theory (DFT) calculations shows that the PC molecule affinity to bind with the SBE-β-CD is higher than that of the FLU molecule. In addition, the results of molecular dynamic (MD) simulations revealed that PC couldinteractwith the carrier through both coulombic and L-J interactions (Ecoul = ∼−206 and EL-J = ∼−190 kJ/mol), while FLU interaction with SBE-β-CD is mainly via van der Waals interactions (Ecoul = ∼−49 and EL-J = ∼−125 kJ/mol). The obtained results show that in both studied systems, H-bond formation is the driving force in stabilizing these structures. The results confirmed that the Phosphatidylcholine could replace the fluorometholone in the carrier cavity and release the drug in the target site. Overall, our findings demonstrate that SBE-β-CD&FLU complex can be a suitable alternative for treating inflammatory disorders of the eye over the conventional delivery systems.

Detecting Microstructural Criticality/Degeneracy through Hybrid Learning Strategies Trained by Molecular Dynamics Simulations.

Efficient microstructure design can strongly accelerate the development of materials. However, the complexity of the microstructure-behavior relation renders the criticalities and degeneracies within the microstructure space highly possible. Criticality means that a slight microstructural change can lead to a dramatic transition in material behavior, while degeneracy means that very different microstructures may lead to similar behaviors. To investigate these microstructural characteristics of the fiber/matrix interface within composite materials, we have proposed a hybrid deep-learning-based framework by integrating the supervised feed-forward neural network and the unsupervised autoencoder, which are trained by the molecular dynamics (MD) simulation results. The well-trained model continuously maps the elemental density images within the interfacial area into a low-dimensional latent space. Assisted by the extracted latent features, we can easily detect the criticalities and degeneracies within the original microstructure space of the composite's interface. The predicted microstructural criticalities and degeneracies are validated by investigating their atomistic origins through MD simulations. The proposed framework can be employed for the interfacial microstructure design of composite materials by identifying certain interfacial microstructures that might lead to undesirable behaviors.

Wettability of different clay mineral surfaces in shale: Implications from molecular dynamics simulations

Shale contains a lot of clay minerals. Clay minerals mainly exist in nano- and micro-meter sized particles, and the pore structure is complex, which leads to its extremely complex wettability. The surface wettability of clay minerals significantly affects the oil and gas-bearing capacity of shale reservoirs. Therefore, studying the wettability of common clay minerals in shale at the nanoscale is of great significance for shale hydrocarbon exploration and development. In this study, the wetting behavior of water in n-hexane and toluene on different clay mineral surfaces at the nanoscale was systematically studied using Molecular dynamics (MD) simulation. And the influencing factors of wettability were analyzed. Through the analysis of the morphological changes of water, relative concentration of water, RDF and interaction energy, it is concluded that the following order of water wettability on the surfaces of clay minerals: montmorillonite > chlorite > kaolinite > illite. Through the analysis of interaction energy, it is concluded that the hydrophilicity of four clay minerals is stronger than that of lipophilicity. And the main interactions between water and oil and the mineral surfaces were van der Waals force and electrostatic force. In addition, the temperature, liquid hydrocarbon type, and mineralization of water affected the wettability of clay minerals. The concentration of water on the surfaces of montmorillonite, kaolinite, and illite decreased with increasing temperature, and the water wettability decreased. At 298 K, the hydrophilicity of the surfaces of the clay minerals in toluene follows the order montmorillonite > chlorite > kaolinite > illite. The higher the NaHCO3 concentration in water, the weaker the wettability of the clay mineral surfaces to water. By comparing the previous experimental results with the MD simulation results, similar wetting characteristics were obtained, and the reliability of the simulation results was verified. MD simulation was used to explore the water wetting of the surfaces of four clay minerals in a shale reservoir from the micro level. This makes up for the lack of experimental means for clarifying the flow and production mechanisms of shale oil and gas and effectively improves the evaluation technology of shale.

Scaling Law for Impact Resistance of Amorphous Alloys Connecting Atomistic Molecular Dynamics with Macroscale Experiments.

Establishing scaling laws for amorphous alloys is of critical importance for describing their mechanical behavior at different size scales. In this paper, taking Ni2Ta amorphous metallic alloy as a prototype materials system, we derive the scaling law of impact resistance for amorphous alloys. We use laser-induced supersonic micro-ballistic impact experiments to measure for the first time the size-dependent impact response of amorphous alloys. We also report the results of molecular dynamics (MD) simulations for the same system but at much smaller scales. Comparing these results, we determined a law for scaling both length and time scales based on dimensional analysis. It connects the time and length scales of the experimental results on the impact resistance of amorphous alloys to that of the MD simulations, providing a method for bridging the gap in comparing the dynamic behavior of amorphous alloys at various scales and a guideline for the fabrication of new amorphous alloy materials with extraordinary impact resistance.

On the replacement behavior of CO2 in nanopores of shale oil reservoirs: Insights from wettability tests and molecular dynamics simulations

CO2 injection process has become one of the most effective development methods of shale oil reservoirs. Considering the widespread nanoscale pores in shale, the replacement dynamics of CO2 in such a small-scale pore can play a dominating role during the recovery process. In this study, combining the methods of static test and molecular dynamics (MD) simulation, the replacement mechanisms of CO2 in the nanopores of shale oil reservoirs are discussed. First, a series of static tests are performed to provide basic data for the molecular model development of shale oil and shale rock. Thus, from the test results, five different porewall molecular models are developed, include four inorganic porewall models (feldspar, calcite, montmorillonite, and quartz) and one organic porewall model (graphene). Simultaneously, two different shale oil molecular models (light shale oil model and heavy shale oil model) are also developed in this study. In order to confirm the accuracy of our MD simulation model, a series of wettability tests on the actual shale rocks are also carried out, and the results are compared against the results of MD simulations. Thereafter, a set of MD simulation runs are performed to address the replacement behavior of CO2 in nanopores. On the other hand, a concept of replacement efficiency (RE) is also proposed in this paper. Thus, the effect of shale oil composition, porewall mineral type and CO2 concentration on the replacement behavior can be analyzed. Results show that the CO2 replacement capacity of the inorganic porewall surfaces is the highest for calcite, followed by montmorillonite, and lowest for quartz and feldspar. In inorganic pores, RE increased significantly with the increase of CO2 concentration. And in organic pores, the change of CO2 concentration mainly affects the replacement effect of light oil. This study can provide some new insights to understand the replacement mechanisms of CO2 in shale oil reservoirs, which is important for the effective and efficient development of shale oil reservoirs.

Molecular Dynamics Simulation of Ti Metal Cutting Using a TiN:Ag Self-Lubricating Coated Tool.

Silver-ceramic nanocomposite coatings, such as TiN:Ag, are among the most interesting solutions to improve the machining and cutting process of hard-to-cut Ti alloys, since they combine the TiN matrix hardness with the lubricating and protective action of Ag nanoparticles. Therefore, it is important to understand how, when present, Ag distributes at the tool-workpiece interface and how it affects the tribolayer formation and the tool wear. Molecular dynamics simulation results, obtained using a MEAM-based force field, are presented here for the cutting process of a Ti workpiece with a TiN tool, with and without the presence of Ag at the interface, for different cutting speeds. Ag is shown to form a thin protective layer at the workpiece-tool interface that prevents a direct contact between the parts and greatly reduces the tool degradation. Our simulations confirm the importance of Ag in self-lubricating nanocomposite coatings to realize the machining of otherwise hard-to-cut materials.

Design of a multi-epitope vaccine against six Nocardia species based on reverse vaccinology combined with immunoinformatics.

Nocardia genus, a complex group of species classified to be aerobic actinomycete, can lead to severe concurrent infection as well as disseminated infection, typically in immunocompromised patients. With the expansion of the susceptible population, the incidence of Nocardia has been gradually growing, accompanied by increased resistance of the pathogen to existing therapeutics. However, there is no effective vaccine against this pathogen yet. In this study, a multi-epitope vaccine was designed against the Nocardia infection using reverse vaccinology combined with immunoinformatics approaches. First, the proteomes of 6 Nocardia subspecies Nocardia subspecies (Nocardia farcinica, Nocardia cyriacigeorgica, Nocardia abscessus, Nocardia otitidiscaviarum, Nocardia brasiliensis and Nocardia nova) were download NCBI (National Center for Biotechnology Information) database on May 1st, 2022 for the target proteins selection. The essential, virulent-associated or resistant-associated, surface-exposed, antigenic, non-toxic, and non-homologous with the human proteome proteins were selected for epitope identification. The shortlisted T-cell and B-cell epitopes were fused with appropriate adjuvants and linkers to construct vaccines. The physicochemical properties of the designed vaccine were predicted using multiple online servers. The Molecular docking and molecular dynamics (MD) simulation were performed to understand the binding pattern and binding stability between the vaccine candidate and Toll-like receptors (TLRs). The immunogenicity of the designed vaccines was evaluated via immune simulation. 3 proteins that are essential, virulent-associated or resistant-associated, surface-exposed, antigenic, non-toxic, and non-homologous with the human proteome were selected from 218 complete proteome sequences of the 6 Nocardia subspecies epitope identification. After screening, only 4 cytotoxic T lymphocyte (CTL) epitopes, 6 helper T lymphocyte (HTL) epitopes, and 8 B cell epitopes that were antigenic, non-allergenic, and non-toxic were included in the final vaccine construct. The results of molecular docking and MD simulation showed that the vaccine candidate has a strong affinity for TLR2 and TLR4 of the host and the vaccine-TLR complexes were dynamically stable in the natural environment. The results of the immune simulation indicated that the designed vaccine had the potential to induce strong protective immune responses in the host. The codon optimization and cloned analysis showed that the vaccine was available for mass production. The designed vaccine has the potential to stimulate long-lasting immunity in the host, but further studies are required to validate its safety and efficacy.

Predicting pathogenicity of variants in the cardiac thin filament using neural networks.

Single amino acid variations to the various proteins of the cardiac thin filament have been linked to a loss of functionality and have shown to result in genetic cardiomyopathies. Currently, there are significant difficulties in linking genotype to phenotype to determine pathogenicity of variants, limiting the ability of clinicians to intervene. Previously, we used molecular dynamics simulations of pathogenic variants on cardiac troponin T and tropomyosin to determine a baseline of pathogenic changes induced in computational observables. The pathogenic baseline was then used to predict the pathogenicity of several variants of unknown significance. In the current study, a convolutional neural network (CNN) is being created to predict the pathogenicity of variants of unknown significance using results of molecular dynamics simulations of the all-atom computational model of the full human cardiac thin filament. The neural network will be able to predict whether a new set of variants of unknown significance on cardiac troponin T, cardiac troponin I, or tropomyosin are benign or pathogenic and further split the pathogenic predictions into either hypertrophic or dilated cardiomyopathy inducing. The CNN will consist of several convolution and pooling layers to reduce the dimensionality of the molecular dynamics data followed by a fully dense network.

ThermalProGAN: A sequence-based thermally stable protein generator trained using unpaired data.

The synthesis of proteins with novel desired properties is challenging but sought after by the industry and academia. The dominating approach is based on trial-and-error inducing point mutations, assisted by structural information or predictive models built with paired data that are difficult to collect. This study proposes a sequence-based unpaired-sample of novel protein inventor (SUNI) to build ThermalProGAN for generating thermally stable proteins based on sequence information. The ThermalProGAN can strongly mutate the input sequence with a median number of 32 residues. A known normal protein, 1RG0, was used to generate a thermally stable form by mutating 51 residues. After superimposing the two structures, high similarity is shown, indicating that the basic function would be conserved. Eighty four molecular dynamics simulation results of 1RG0 and the COVID-19 vaccine candidates with a total simulation time of 840[Formula: see text]ns indicate that the thermal stability increased. This proof of concept demonstrated that transfer of a desired protein property from one set of proteins is feasible. Availability and implementation: The source code of ThermalProGAN can be freely accessed at https://github.com/markliou/ThermalProGAN/ with an MIT license. The website is https://thermalprogan.markliou.tw:433. Supplementary information: Supplementary data are available on Github.

Discovery, synthesis and in silico approach of pyrrolo [3,4-c]pyrroles as SARS-CoV-2 mpro inhibitors

A new coronavirus has been identified as the contributing agent of the severe acute respiratory syndrome (SARS). The main viral protease (Mpro), which controls the activities of the coronavirus replication complex, which is an essential target for the treatment of coronavirus disease. With the primary objective of targeting this receptor, we designed a new series of pyrrolo [3,2-c] pyrroles, synthesized and characterized using various analytical techniques including FT-IR, UV-Vis and NMR spectroscopic studies. The biological descriptors of the synthesized compounds were investigated using DFT calculation. The mode of binding and reactivity of the target compounds with SARS-CoV-2 main protease (Mpro) were studied using molecular docking and molecular dynamics (MD) simulation. Molecular docking of the compounds (4a and 5a) showed a promising binding affinity towards Mpro protein with the binding energy of −7.8 kcal/mol and −7.0 kcal/mol, respectively. The results of MD simulation and prime MM-GBSA calculation were consistent with molecular docking. The absorption, distribution, metabolism and excretion (ADME) properties of the compounds are in the acceptable range, as they are orally active and obey Lipinski’s rule of five without violation. In addition, in silico toxicity prediction using the Pro-Tox II revealed the non-toxic nature of the compounds. Hence the obtained results suggest that these compounds could be a possible anti-viral candidate and highlight this series of compounds for further drug design and development against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Insight into the glycerol extraction from biodiesel using deep eutectic solvents

The main challenge of large-scale biofuel production is related to the extraction of its undesired impurities including glycerol, water, methanol, soap/catalyst, free fatty acids, glycerides, and others. There are many ways to remove glycerol, and herein, the one alternative is the extraction of glycerol from biodiesel by deep eutectic solvents. In this regard, the mixture of a choline chloride (ChCl) and urea, methyltriphenylphosphonium chloride (MTPPCl), and ethylene glycol (EGL), as a deep eutectic solvent (DES), is effective in removing glycerol from biofuel. In this work, we have investigated the formation mechanism of ChCl and urea, and then MTPPCl and EGL, as a DES, and then extraction of glycerol from biofuel via DES implementing density functional theory (DFT)by Gaussian09 software, B3LYP basis set, and classical all-atom molecular dynamics (MD) simulationsby Gromacs software, GROMOS force field. DFT approximation demonstrates that Cl ion plays an important binding role in the formation of complexes ChCl/urea-based DES + biofuel and in MTPPCl/EGL-based DES + biofuel. We have also considered the formation and change of hydrogen bonds upon the formation of these systems using the DFT method. Large HOMO-LUMO gaps in ChCl/urea-based DES + biofuel and in MTPPCl/urea-based DES + biofuel demonstrate the stability of the complexes. The results of MD work have stated that the chloride ion formed bonding with the choline/ethylene glycol EGL, while still weakly intermolecular interacting with the urea/methyltriphenylphosphonium in ChCl/urea- and MTPPCl/EGL-based DESs. Further results of MD simulations stated that the DESs had a higher intermolecular interaction with glycerol in comparison with biofuel, thereby favoring the extraction process of glycerol from model biofuel. • Intermolecular interactions of choline chloride and urea, methyl triphenyl phosphonium chloride, and ethylene glycol-based DESs and their applications in the extraction of glycerol from biofuel studied by DFT calculations and classical all-atom molecular dynamics simulations. • Calculated outputs of DFT calculations and classical all-atom molecular dynamics simulations for DESs and their applications in the extraction of glycerol from biofuel were discussed in detail. • The molecular formation mechanism of choline and methyl triphenyl phosphonium-based DESs and their application in the extraction process of glycerol from biofuel were summarized.

Molecular-Level Insight of CP52/NBR Damping Composites through a Combination of Molecular Dynamics Simulation and Experimental Method.

To enhance the damping properties of nitrile butadiene rubber (NBR), the elastomer used was blended with chlorinated paraffin 52 (CP52) to prepare NBR/CP52 composites. The results showed that CP52 could significantly enhance the damping properties of NBR and shift the glass transition temperature (Tg) to lower temperatures. Molecular dynamics models of the CP52/NBR system were established, and the damping properties of the CP52-reinforced NBR were investigated using molecular dynamics (MD) simulations. Through the combination of MD simulations and the experimental results, the essential mechanism of the enhanced damping properties of the NBR was methodically expatiated and was ascribed to the Cl-CP-H····NC-NBR (type I) and CP-Cl····H-NBR-CN (type II) analogous hydrogen bonds formed between NBR and CP52. The higher the CP52 content, the higher the analogous hydrogen bond concentration, and the better the damping properties of the CP52/NBR composites. The experimental results were very consistent with the MD simulation results, meaning that the combination method can provide a new means to optimize the design of damping materials and broaden the application range of small polar molecules in the damping modification of polar rubber materials.

Thermal capillary waves on bounded nanoscale thin films.

The effect of confining walls on the fluctuation of a nanoscale thin film's free surface is studied using stochastic thin-film equations(STFEs). Two canonical boundary conditions are employed to reveal the influence of the confinement: (1) an imposed contact angle and (2) a pinned contact line. A linear stability analysis provides the wave eigenmodes, after which thermal-capillary-wave theory predicts the wave fluctuation amplitudes. Molecular dynamics (MD) simulations are performed to test the predictions, and a Langevin diffusion model is proposed to capture oscillations of the contact lines observed in MD simulations. Good agreement between the theoretical predictions and the MD simulation results is recovered, and it is discovered that confinement can influence the entire film. Notably, a constraint on the length scale of wave modes is found to affect fluctuation amplitudes from our theoretical model, especially for 3D films. This opens up challenges and future lines of inquiry.

Effect of oxygen-containing functional groups on the wettability of coal through DFT and MD simulation

To investigate the wettability of different oxygen-containing functional group (OFG) surfaces, graphite substrates were used as a model for coal adsorbents. The substrates were modified with COOH, OH, CO, and OCH3. The adsorption-diffusion behavior of H2O molecules/water droplets on different OFG surfaces was investigated using molecular dynamics (MD) simulations with frontier orbital energy difference as a metric for different surface wettability degrees in quantum chemical analysis. The results indicated that the frontier orbital energy difference of the H2O molecule was 3.480, 3.491, 3.631, and 3.680 eV for PhCOOH, PhOH, PhCO, and PhOCH3, respectively. In addition, the equilibrium contact angle, interaction energy, and number of hydrogen bonds after the adsorption equilibrium of water droplets for COOH, OH, CO, and OCH3 surfaces were 22.34°, −5.03 kcal/mol, and 652; –23.72°, −4.19 kcal/mol, and 450; 68.01°, −0.79 kcal/ mol, and 61; 90.51°, −0.50 kcal/mol, and 28, respectively. The smaller the energy difference between the frontier orbitals of the H2O molecule and the OFG, the smaller the equilibrium contact angle between the water droplet and the OFG surface, the more hydrogen bonds were formed, and the larger the absolute value of the interaction energy, the better the wettability of the surface of the OFG. The order of wettability of the different OFG surfaces was COOH > OH > CO > OCH3, which is consistent with the radial distribution function and the analysis results for the extended area, etc. The results of density functional theory (DFT) calculations and MD simulations exhibited identical patterns, indicating the reasonableness of the simulations. This study may serve as a reference for the suppression of hydrophilicity in low-order coal and the enhancement of the flotation effect.

The association between genetic variations and morphology-based brain networks changes in Alzheimer's disease.

Alzheimer's disease (AD) is a highly heritable disease. The morphological changes of cortical cortex (such as, cortical thickness and surface area) in AD always accompany by the change of the functional connectivity to other brain regions and influence the short- and long-range brain network connections, causing functional deficits of AD. In this study, the first hypothesis is that genetic variations might affect morphology-based brain networks, leading to functional deficits; the second hypothesis is that protein-protein interaction (PPI) between the candidate proteins and known interacting proteins to AD might exist and influence AD. 600 470 variants and structural magnetic resonance imaging scans from 175 AD patients and 214 healthy controls were obtained from the Alzheimer's Disease Neuroimaging Initiative-1 database. A co-sparse reduced-rank regression model was fit to study the relationship between non-synonymous mutations and morphology-based brain networks. After that, PPIs between selected genes and BACE1, an enzyme that was known to be related to AD, are explored by using molecular dynamics (MD) simulation and co-immunoprecipitation (Co-IP) experiments. Eight genes affecting morphology-based brain networks were identified. The results of MD simulation showed that the PPI between TGM4 and BACE1 was the strongest among them and its interaction was verified by Co-IP. Hence, gene variations influence morphology-based brain networks in AD, leading to functional deficits. This finding, validated by MD simulation and Co-IP, suggests that the effect is robust.

Deciphering the interactions of genistein with β-cyclodextrin derivatives through experimental and microsecond timescale umbrella sampling simulations

Genistein (GEN), an isoflavone, exhibits wide array of biological activities such as antioxidant, anti-inflammatory, cardioprotective and neuroprotective effects. However, despite of tremendous biological activities, its incorporation into functional foods and food supplements is limited due to its low aqueous solubility and instability. The present investigation unveils the molecular mechanism of inclusion of GEN inside the cyclodextrins (CDs) cavities with special emphasis on the correlation of experimental methods with molecular dynamics (MD) simulations. Herein, host – guest inclusion complexes (ICs) of GEN with two modified forms of β-cyclodextrins [Methyl-β-cyclodextrin (M-β-CD) & Hydroxypropyl-β-cyclodextrin (HP-β-CD)] were prepared using spray-drying to improve the aqueous solubility and the apparent stability of GEN. The ICs were characterized by fourier transform infra-red (FT-IR) spectroscopy, powder X-ray diffractometry (PXRD), scanning electron microscopy (SEM) and nuclear magnetic resonance spectroscopy (1H NMR and 2D-NOESY) providing appropriate evidences of the inclusion of GEN inside host cavities (CDs). The results of MD simulations demonstrated multiple conformations obtaining energy minimas of GEN/M-β-CD, whereas GEN/HP-β-CD only showed a single metastable structure. The results were further complemented by enhanced umbrella sampling simulations where GEN/M-β-CD demonstrated lower free energy of binding than GEN/HP-β-CD. Overall, this study presents basic mechanism behind GEN/CD inclusion complexes formation using experimental and computational approaches.

In silico design of a multi-epitope vaccine against the spike and the nucleocapsid proteins of the Omicron variant of SARS-CoV-2

Computational studies can comprise an effective approach to treating and preventing viral infections. Since 2019, the world has been dealing with the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The most important achievement in this short period of time in the effort to reduce morbidity and mortality was the production of vaccines and effective antiviral drugs. Although the virus has been significantly suppressed, it continues to evolve, spread, and evade the host’s immune system. Recently, researchers have turned to immunoinformatics tools to reduce side effects and save the time and cost of traditional vaccine production methods. In the present study, an attempt has been made to design a multi-epitope vaccine with humoral and cellular immune response stimulation against the Omicron variant of SARS-CoV-2 by investigating new mutations in spike (S) and nucleocapsid (N) proteins. The population coverage of the vaccine was evaluated as appropriate compared to other studies. The results of molecular dynamics simulation and molecular mechanics/generalized Born surface area (MM/GBSA) calculations predict the stability and proper interaction of the vaccine with Toll-like receptor 4 (TLR-4) as an innate immune receptor. The results of the immune simulation show a significant increase in the coordinated response of IgM and IgG after the third injection of the vaccine. Also, in the continuation of the research, spike proteins from BA.4 and BA.5 lineages were screened by immunoinformatics filters and effective epitopes were suggested for vaccine design. Despite the high precision of computational studies, in-vivo and in-vitro research is needed for final confirmation. Communicated by Ramaswamy H. Sarma

On the potentials of sialic acid derivatives as inhibitors for the mumps virus: A molecular dynamics and quantum chemistry investigation

Mumps virus is an infectious pathogen causing major health problems for humans such as encephalitis, orchitis, and parotitis. Therefore, designing an inhibitor for this virus is of great medical and public health importance. With this goal in mind, we investigate the affinity of different sialic acid-based compounds (ligands) against the hemagglutinin-neuraminidase (HN) protein of the mumps virus, using a combination of molecular dynamics (MD) simulations and quantum chemistry calculations. Our MD simulation results indicate that the ligands form stable complexes with the HN protein through a combination of electrostatic, van der Waals (vdW), and hydrogen bond (H-bond) interactions, which the electrostatic interactions play a more important role in the complexation process. Based on the obtained results from the structural analysis Arg381, Arg291, and Arg49 play a key role in the binding site interactions with the different ligands, in comparison with other residues. There are some candidates such as Neu5Acα2-6Galβ1-4GlcNAcβ, Neu5Acα2-3Galβ1-3GlcNacβ1-3Galβ1-4Glc, and Neu5Acα2-6Galβ1-4GlcNAcβ1-3Galβ1-4Glc that form more stable complexes with the HN than the α2-3-Sialyllactose confirmed by the calculated Gibbs binding energies (-39.65, -46.93, and -36.49 kcal.mol−1, respectively).To investigate the relationship between the molecular properties of the selected compounds and their affinity to the HN receptor, density functional theory dispersion corrected (DFT-D3) calculations were employed. According to our DFT-D3 results, neutral sialic acid-based compounds have lower reactivity to the mumps virus than the negativity charge structures. Moreover, by increasing the electronic chemical potential (μ) the vdW and H-bond interactions between drugs and the HN protein increase. In other words, by elevating the electron tendency of the selected ligands their affinity to the mumps virus increases. Our quantum chemistry calculations reveal that in addition to the structural features the molecular properties of the drugs can play important roles in their affinity and reactivity against the virus. The results of this study can provide useful details to design new compounds or improve their properties against the mumps virus.