Molecular Dynamics Simulation Method Research Articles

Study on the Factors Affecting the Self-Healing Performance of Graphene-Modified Asphalt Based on Molecular Dynamics Simulation.

To comprehensively understand the impact of various environmental factors on the self-healing process of graphene-modified asphalt, this study employs molecular dynamics simulation methods to investigate the effects of aging degree (unaged, short-term aged, long-term aged), asphalt type (base asphalt, graphene-modified asphalt), healing temperature (20 °C, 25 °C, 30 °C), and damage degree (5 Å, 10 Å, 15 Å) on the self-healing performance of asphalt. The validity of the established asphalt molecular models was verified based on four physical quantities: density, radial distribution function analysis, glass transition temperature, and cohesive energy density. The simulated healing time for the asphalt crack model was set to 200 ps. The following conclusions were drawn based on the changes in density, mean square displacement, and diffusion coefficient during the simulated healing process under different influencing factors: Dehydrogenation and oxidation of asphalt molecules during the aging process hinder molecular migration within the asphalt crack model, resulting in poorer self-healing performance. As the service life increases, the decline in the healing performance of graphene-modified asphalt is slower than that of base asphalt, indicating that graphene-modified asphalt has stronger anti-aging properties. When the vacuum layer in the asphalt crack model is small, the changes in the diffusion coefficient are less pronounced. As the crack width increases, the influence of various factors on the diffusion coefficient of the asphalt crack model becomes more significant. When the crack width is large, the self-healing effect of asphalt is more dependent on these influencing factors. Damage degree and oxidative aging have a more significant impact on the healing ability of graphene-modified asphalt than healing temperature.

Interface dynamics in dewatering processes of high-water-content slurry flocculated with PAC

This study addresses the challenge of the reverse effect observed in the dewatering process of waste slurry as poly-aluminum chloride (PAC) dosages increase. It investigates the flocculation mechanism of PAC at varying dosages in a high-water-content slurry using molecular dynamics simulation methods. The results indicate that PAC molecules primarily adsorb montmorillonite particles while exerting negligible influence on quartz. Dewatering efficiency is influenced by the adsorption-repulsion interaction at the PAC-montmorillonite interface. Efficiency increases with PAC dosage up to an optimum level due to enhanced adsorption but decreases thereafter due to increasing repulsion. Within this optimal range, montmorillonite interfaces exhibit a higher negative charge, facilitating stable PAC adsorption and leading to increased aggregation of montmorillonite particles, thereby forming flocs. The adsorption capacity of PAC on montmorillonite particles escalates with dosage until achieving the optimal flocculation effect. However, surpassing this optimal dosage prompts repulsion among outer PAC molecules, gradually causing montmorillonite particles to separate due to repulsion, thereby weakening the flocculation effect. This research provides theoretical support for the flocculation and dewatering of PAC in high-water-content waste slurry, emphasizing the rational and cost-effective addition of PAC in practical applications.

Exploring Novel Quinoline-1,3,4-Oxadiazole Derivatives for Alzheimer's Disease: Their Design, Synthesis, and In-Vitro and In-Silico Investigations.

Alzheimer's Disease (AD) is a complicated and advanced neurodegenerative condition accompanied by gradual cholinergic neuronal death and higher levels of monoamine oxidase-B (MAO-B) enzyme. In this study, a series of novel hybrid compounds combining 1,3,4-oxadiazole and quinoline moieties were synthesized and evaluated for their potential as inhibitors of acetylcholinesterase (AChE), butyrylcholinesterase (BuChE), and MAO enzymes. The chemical structures of the synthesized compounds were confirmed using various analytical techniques, such as mass spectrometry, infrared spectroscopy (IR), proton nuclear magnetic resonance (1H-NMR), and carbon and nuclear magnetic resonance (13C-NMR). The final products were evaluated for anticholinesterase potential by applying modified Ellman's spectrometric method, whereas a fluorometric method was used to assess MAO inhibition properties. In-silico studies using molecular docking and molecular dynamics simulation (MDS) methods has been also conducted. Among the synthesized compounds, 5a, 5c, and 6a demonstrated substantial activity against AChE, with IC50 values of 0.033 μM, 0.096 μM, and 0.177 μM, respectively. A molecular docking study was performed to elucidate the binding modes and establish the structure-activity relationship (SAR) of the most active compounds (5a, 5c, and 6a). Molecular dynamics simulation (MDS) of the most potent compound, 5a, was also conducted to examine the stability of the interactions with the receptor. Moreover, the physicochemical properties of the active products were also studied. Overall, this research contributes to the development of 1,3,4-oxadiazole- quinoline hybrids as potential AChE inhibitors for the treatment of Alzheimer's disease.

Effect of chitooligosaccharide on the binding domain of the SARS-COV-2 receptor

The receptor-binding domain (RBD) is crucial for understanding how severe acute respiratory syndrome coronavirus (SARS-CoV-2) recognizes and infects host cells. Chitooligosaccharide (CS) exhibits diverse antiviral activities, with its derivatives showing remarkable efficacy in blocking SARS-CoV-2 infection. Thus, this study employed spectroscopy, virus-infected cell experiments, and molecular simulation to investigate the molecular interactions between CS and SARS-CoV-2 RBD, as well as their mechanisms. In spectroscopic experiments, all four CS variants with different molecular weights formed interactions with the RBD. These variants increased the resistance of HEK293ACE2 cells to SARS-CoV-2 invasion. Molecular docking revealed that the four CS variants could bind to the RBD through hydrogen bonding or salt-bridge interactions, forming stable complexes. Chitotetraose provided stronger protection to HEK293ACE2 cells compared to other CS variants and displayed higher molecular docking scores. Further investigation into the optimal docking conformation of chitotetraose was conducted through molecular dynamics simulation methods. This study lays a solid theoretical foundation and provides a scientific basis for the development of targeted RBD inhibitors, as well as drug screening and application against novel coronaviruses.

Molecular dynamics simulation on the variations in characteristics of aqueous solution with diverse additives: Inspirations for binary ice preparation

Ice slurry, as a novel energy storage medium, possesses the superiority of high energy storage density. The freezing point inhibitors are employed to regulate the supercooling phenomenon of water, while the macroscopic experiments are complicated to elucidate the action mechanism. Consequently, this paper adopts molecular dynamic simulation method to investigate the mean square displacement, radial distribution function, hydrogen bonds types, hydrogen bonds number and length of water at various concentrations of ethanol, NaCl, and SiO2 additives. The results indicate that the average number of hydrogen bonds of the system composed with 600 pure water molecules is 1127.24, and the average length of hydrogen bonds is 2.33 Å. Moreover, the addition of alcoholics and chlorides inhibits the hydrogen bonds between water and water molecules, and promotes the generation of hydrogen bonds, thus weakening the diffusion motion of water molecules. Whereas, it is observed that the addition of nanoparticles leads to agglomeration in pure water system, resulting an increase in the viscosity and a decrease in the diffusion rate of the system. The proposed microscopic model can effectively depict the potential interaction mechanisms of additives and water, which is contributing to develop effective freezing point inhibitors and improve the energy utilization efficiency.

Molecular interactions of the antioxidant in the coolant oil for energy transformers: Dielectric and simulation studies

This research paper presents experimental and theoretical findings concerning the blending of mineral oil and vegetable oils, both with and without antioxidants. The study analyses a variety of parameters for different blends of mineral and vegetable oils, including breakdown voltage, ageing resistance, dielectric constant, viscosity, dissipation factor, surface tension, flash point, and fire point. The study was further extended to investigate the effects of varying the amount of antioxidants added to mineral oil blends with different vegetable oils. The best transformer insulating solution is found by extensive analyses that include measurements of breakdown voltage, flash point, fire point, and surface tension. This blends’ properties with antioxidant are either better than pure mineral oil or comparable to mineral oil. Density functional theory (DFT) analyses the molecular structure and dipole moment of an antioxidant. Molecular dynamics simulation method (MD) analysis of the average water residual time – periods of an antioxidant will show the stability of H-bond interactions. The primary objective of this experiment is to unveil a novel liquid-insulating material that not only excels in dielectric performance but also aligns with environmentally friendly practices.

Effect of UEVC parameters on cutting surface quality and subsurface damage of single crystal γ-TiAl alloy via atomic simulation

TiAl alloys are favored by the aerospace industry due to its excellent mechanical properties. However, its intrinsic brittleness, the use of conventional cutting (CC) process leads to the problems of high cutting force and high cutting temperature, which in turn affects the machined surface quality. Ultrasonic elliptical vibratory cutting (UEVC) has been proved to be an effective method to improve the surface quality and reduce the subsurface damage of difficult-to-machine materials. This paper compares the effects of CC and UEVC processes on cutting forces and subsurface damage based on molecular dynamics simulation methods, and the effects of elliptical vibration frequencies and amplitude ratios (AR) on surface morphology, roughness, and subsurface damage are investigated. The results show that the cutting force and subsurface damage in the UEVC process are reduced compared with that in the CC. Due to the vibration frequency, the subsurface damage is mainly dominated by atomic clusters, and both surface and subsurface masses show an optimization trend as the vibration frequency decreases. In terms of the AR, the surface quality is better at an AR of 2/3, with less activation of immovable dislocations, and the degree of subsurface damage decreases as the AR increases, and a relatively stable defective structure emerges when the AR is 1/2. The simulation results facilitate an atomic-scale comprehension of the removal mechanism of UEVC and further provide a theoretical foundation for the surface mass and subsurface damage mechanism and optimization of vibrational parameters of UEVC single crystal γ-TiAl alloy.

How specific ion effects influence the mechanical behaviors of amide macromolecules? A cross-scale study.

The mechanisms of specific ion effects on the properties of amide macromolecules is essential to understanding the evolution of life. Because most biological macromolecules contain both complex hydrophilic and hydrophobic structures, it is challenging to accurately identify the contributions of molecular structure to macroscopic behaviors. Herein, we investigated the influence of specific ion effects on the mechanical behaviors of poly(N-isopropylacrylamide) and neutral polyacrylamide (i.e., PNIPAM and NPAM), through a cross-scale study that includes single-molecule force spectroscopy, molecular dynamics simulation and macro mechanical method. The results indicate that the molecular conformation can be markedly influenced by the hydrophilicity (or hydrophobicity) of both macromolecule chain and ions. An extended chain conformation can be obtained when the side groups and ions are relatively hydrophilic, which can also increase the elasticity of a macromolecule chain and film materials. The relatively hydrophobic components promote the collapse of macromolecule chains and reduce the molecular elasticity. It is believed that the hydrogen bonding intensity between a macromolecule chain and aquated ions controls the chain conformation and the elasticity of molecules and films. This study is not only helpful for understanding the self-assembly mechanism of organisms but also provides a way to associate the molecular properties with the macroscopic performance of materials.

Degradation pathways and product formation mechanisms of asphaltene in supercritical water

Asphaltene is the compound with the most complex structure and the most difficult degradation in oily sludge, which is the key to limit the efficiency of supercritical water oxidation treatment of oily sludge. In this paper, the supercritical water oxidation process of asphaltene was investigated in terms of free radical reaction, degradation pathway, and product generation mechanism using ReaxFF molecular dynamics simulation method. The results showed that increasing temperature, increasing O2, and increasing H2O have different effects on HO2·generation. Benzene rings undergo fusion and condensation through hydrogenation abstraction and oxygen addition reactions, subsequently breaking down into long-chain alkanes. Increasing O2 can effectively promote the ring-opening of nitrogen-containing heterocycles. -COOH is the most important intermediate fragment for CO and CO2 generation, and there is a reaction competition with -CHO3 and -CO3. When the number of oxygen molecules increases from 300 to 700, the reaction frequency of -CHO3 and -CO3 to generate CO and CO2 increases by 17.14 % and 12.77 %·H2O determines the production of H2 by controlling the number of H·radicals present. As the amount of H2O increases from 500 to 1500, the product ratio of H2 increases from 12.73 % to 21.31 %. Environmental implicationAsphaltene is the most structurally complex organic matter in oily sludge, and its presence makes it difficult for oily sludge to be completely degraded by conventional treatment methods such as pyrolysis and incineration. Polycyclic aromatic hydrocarbons (PAHs) represented by asphaltene increase the carcinogenicity and mutagenicity of oily sludge, and even irreversibly pollute soil and groundwater. Supercritical water oxidation, as an efficient organic waste treatment technology, can realize harmlessness in a green and efficient way. So the study on the mechanism of supercritical water oxidation of asphaltene is of great significance for environmental protection.

Rational Design of Non-Covalent Imprinted Polymers Based on the Combination of Molecular Dynamics Simulation and Quantum Mechanics Calculations.

Molecular imprinting is a promising approach for developing polymeric materials as artificial receptors. However, only a few types of molecularly imprinted polymers (MIPs) are commercially available, and most research on MIPS is still in the experimental phase. The significant limitation has been a challenge for screening imprinting systems, particularly for weak functional target molecules. Herein, a combined method of quantum mechanics (QM) computations and molecular dynamics (MD) simulations was employed to screen an appropriate 2,4-dichlorophenoxyacetic acid (2,4-D) imprinting system. QM calculations were performed using the Gaussian 09 software. MD simulations were conducted using the Gromacs2018.8 software suite. The QM computation results were consistent with those of the MD simulations. In the MD simulations, a realistic model of the 'actual' pre-polymerisation mixture was obtained by introducing numerous components in the simulations to thoroughly investigate all non-covalent interactions during imprinting. This study systematically examined MIP systems using computer simulations and established a theoretical prediction model for the affinity and selectivity of MIPs. The combined method of QM computations and MD simulations provides a robust foundation for the rational design of MIPs.

Reactant Discovery with an Ab Initio Nanoreactor: Exploration of Astrophysical N-Heterocycle Precursors and Formation Pathways.

The incorporation of nitrogen atoms into cyclic compounds is essential for terrestrial life; nitrogen-containing (N-)heterocycles make up DNA and RNA nucleobases, several amino acids, B vitamins, porphyrins, and other components of biomolecules. The discovery of these molecules on meteorites with non-terrestrial isotopic abundances supports the hypothesis of exogenous delivery of prebiotic material to early Earth; however, there has been no detection of these species in interstellar environments, indicating that there is a need for greater knowledge of their astrochemical formation and destruction pathways. Here, we present results of simulations of gas-phase pyrrole and pyridine formation from an ab initio nanoreactor, a first-principles molecular dynamics simulation method that accelerates reaction discovery by applying non-equilibrium forces that are agnostic to individual reaction coordinates. Using the nanoreactor in a retrosynthetic mode, starting with the N-heterocycle of interest and a radical leaving group, then considering the discovered reaction pathways in reverse, a rich landscape of N-heterocycle-forming reactivity can be found. Several of these reaction pathways, when mapped to their corresponding minimum energy paths, correspond to novel barrierless formation pathways for pyridine and pyrrole, starting from both detected and hypothesized astrochemical precursors. This study demonstrates how first-principles reaction discovery can build mechanistic knowledge in astrochemical environments as well as in early Earth models such as Titan's atmosphere where N-heterocycles have been tentatively detected.

Consolidation performance and mechanism of composite dust suppressant based on graft modification

AbstractTo solve the severe coal dust pollution and dust hazards in underground coal mines, this study utilized graft copolymerization modification technology and compound technology to develop a mining composite consolidation dust suppressant. On this basis, analysis of its consolidation wettability and dust suppression mechanism was conducted through characterization tests and molecular dynamics simulation methods. The results show that polyacrylamide (PAM) had been successfully grafted onto the soybean protein isolate (SPI) molecule, and form a SPI‐PAM complex. After the dust suppressant acted on the coal dust surface, it utilized its wealthy hydrophilic groups, for the adsorption of water molecules and the positive amide group for binding to produce a large area of agglomeration of coal dust particles at the interface, exhibiting good wetting and consolidation into a shell. At the same time, molecular dynamic simulation verified that the diffusivity of water molecules in the dust suppressant‐coal system was 0.30Å2/ps, decreased by 43.3%, and the interaction energy with coal molecules was −200.27 kcal/mol, absolute value increased by 41.35%, which made the dust suppressant molecules more easily adsorb and agglomerate on the surface, demonstrated an excellent solidification and dust suppression effect.

Mechanism study on the influence of wettability on CO2 displacement of shale oil in nanopores

A four-phase model of an oil–gas-water-wall system was constructed using the molecular dynamics simulation method. On this basis, the effect of shale reservoir wettability on the mechanism of CO2 flooding of oil will be investigated. The study found that in hydrophilic and mixed wetting systems, the front of the CO2 molecules had a semilunar shape. In lipophilic systems, however, it advanced as a whole. In addition, water molecules in the mixed wet system will form a water bridge, preventing the forward movement of CO2 molecules. CO2 molecules can easily displace oil molecules in pores of different wettability, but cannot remove the water molecules adsorbed on hydrophilic and mixed wetting systems. Oil molecules interact weakly with the hydroxyl group on the wall, but strongly with the methyl group on the wall. CO2 molecules interact strongly with both the methyl and hydroxyl groups on the wall. The difficulty of CO2 in displacing shale oil in different wetting systems is ranked in the following order: mixed wetting system (41.90 %), lipophilic system (91.51 %), hydrophilic system (98.77 %). Additionally, the storage efficiency of the three nanopores for CO2 was 50.53 %, 77.53 %, and 74.24 %, respectively. The research results can provide theoretical support for the development of CO2 in shale reservoirs.

Impact of surface-active ionic solutions on the structure and function of laccase from trametes versicolor: Insights from molecular dynamics simulations

Many protein-ionic liquid investigations have examined laccase interactions. Laccases are a class of poly-copper oxidoreductases that retain significant biotechnological relevance owing to their notable oxidative capabilities and their application in the elimination of synthetic dyes, phenolic compounds, insecticides, and various other substances. This study investigates the impact of surface active ionic liquids (SAILs), namely, decyltrimethylammonium bromide [N10111][Br] and 1-decyl-3-methylimidazolium chloride [C10mim][Cl] as cationic surfactant ionic liquids and cholinium decanoate [Chl][Dec], an anionic surfactant ionic liquid, on the structure and function of laccase from the fungus Trametes versicolor (TvL) by the molecular dynamics (MD) simulation method. In summary, this study showed that laccase solvent-accessible surface area increased in the ionic liquid [Chl][Dec] while it decreased in the other two ionic liquids. Interestingly, [Chl][Dec] ionic liquid components formed hydrogen bonds with laccase, while [N10111][Br] and [C10mim][Cl] components were unable to form hydrogen bonds with laccase. The quantity of hydrogen bonds formed between water molecules and the enzyme was also diminished in the presence of [Chl][Dec] in comparison to the other two ionic liquids. especially at a concentration of 250 mM. In 250 mM concentrations of [N10111][Br] and [C10mim][Cl], clusters of long-chain cations are likely to form near the copper T1 site. However, even at low [Chl][Dec] concentrations, long [Dec]- chains were observed to penetrate the enzyme near the copper T1 site, and at 250 mM [Chl][Dec], a large cluster of anions occupied the opening of the active site. The results of the analysis also show that the interaction between the [Dec]- anion and the enzyme is stronger than the interaction between [N10111]+ and [C10mim]+ with laccase; in addition, the [Dec]- anion, compared to [Br]- and [Cl]- has a much greater tendency to bind with the enzyme residues.

Effects of B2O3 on melting characteristic temperature and evaporation of CaF2-CaO-Al2O3 based ESR slag

The evaporation behaviors of ESR slag (CaF2-CaO-Al2O3-MgO-(B2O3)) for B-containing rack steel was laboratorially investigated to improve the stability of ESR process and the quality of ESR ingots. The thermogravimetric measurement, FactSage 8.3, kinetic analysis and molecular dynamics simulation methods were applied in this study. Additionally, the melting characteristic temperatures of the slag was tested by the hemisphere method. The results showed that B2O3 reduced the melting characteristic temperatures and mass loss of slag. Increasing the B2O3 content increased the vapor pressure of AlF3, OBF, and BF3, consequently promoting their evaporation. The main evaporating product in the slag was found to be CaF2, followed by minor amounts of MgF2, AlF3, OBF, AlOF, and BF3. Notably, the apparent activation energy for fluoride evaporation was calculated to fall within the range of 189.43–388.24 kJ mol−1, with the evaporation process following a nucleation and growth mechanism. The order of the self-diffusion coefficients of ions in the slag was determined to be F− > Mg2+>Ca2+>O2− ≈ B3+>Al3+. With the increase of B2O3 content in the slag, the self-diffusion coefficient of each ion underwent an initial decrease followed by a significant increase, illustrating that diffusion did not serve as the controlling step of the evaporation reaction.

In silico Identification of Fructose-1,6-biphosphatase Inhibitory Potentials of Xanthones Isolated from African Medicinal Plants: An Integrated Computational Approach

Background: Type 2 diabetes mellitus continues to pose a threat to the existence of the human race. The increasing number of diabetic subjects can be effectively controlled by targeting enzymes responsible for high blood glucose levels. Xanthones are a class of phytochemicals that possesses promising pharmacological potentials. Objective: This study identified fructose 1,6-biphosphatase (FBPase) inhibitors by exploring xanthones isolated from African medicinal plants through ensemble docking, molecular dynamics simulation and density functional theory methods. Methods: The study used ensemble docking, molecular dynamics simulation and density functional theory (B3LYP/6-3G (d,p) basis set) and ADMET methods to select lead compound that may be effective as fructose-I,6-biphosphatase inhibitor. Results: The ensemble docking results identified globulixanthone C (-10.0 kcal/mol), 1-Isomangostin (- 9.0 kcal/mol), laurentixanthone A (-9.0 kcal/mol), bangangxanthone A (-8.9 kcal/mol) and staudtiixanthone B (-8.8 kcal/mol) as potential inhibitors of fructose-1,6-biphosphatase. Molecular dynamics studies showed the xanthones established good binding mode and their binding energy ranged from -74.057 to 53.669 kJ/mol. Also, the electronic and ADMET studies of the xanthones elucidated their excellent pharmacological potential. Conclusion: The study identified xanthones as potential fructose-1,6-biphosphatase inhibitors. The ligands' binding energy and MMPBSA calculations supported their possible inhibitory property. Also, the ADMET properties estimated show the ligands as suitable drug candidates as fructose-1,6-biphosphatase inhibitors. Further in vitro and in vivo investigation of the hit molecules is necessary to develop new FBPase inhibitors.

Scale inhibition mechanism of itaconic acid-sodium methacrylate sulfonate on calcite: Quantum chemical calculation and molecular dynamics simulation

In order to explore the scale inhibition mechanism of green scale inhibitor-itaconic acid-sodium methacrylate sulfonate (IA-SMAS) on calcium carbonate (CaCO3), the scale inhibition characteristics of IA-SMAS were studied by quantum chemical calculation and molecular dynamics simulation. The charge distribution, electrostatic potential distribution, geometric matching degree and frontier molecular orbital energy of IA-SMAS were analyzed by quantum chemical calculation. It was found that IA-SMAS molecules have the ability to bind to Ca2+ at the micro level, occupy the growth active sites of crystal during the growth of calcite crystal planes, and inhibit the normal growth of crystal. Based on the molecular dynamics simulation method, the effects of IA-SMAS concentration on the adsorption configuration, radial distribution function and interaction energy in the binding process of IA-SMAS with calcite crystal planes were analyzed. The results show that the area of calcite crystal planes covered by IA-SMAS molecules, the peak value of radial distribution function and the binding energy increase with the increase of IA-SMAS concentration. However, the relative concentration of water molecules near the calcite crystal planes decreases, and the trend of water molecules moves away from the crystal planes of calcite. It indicates that the high concentration of IA-SMAS molecules can occupy the position of water molecules, and enhance the scale inhibition efficiency. Therefore, the scale inhibition performance of IA-SAMS increases with the increase of its concentration in a certain range, and an appropriate increase in IA-SMAS concentration can effectively inhibit the growth of scale.

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes

Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new computational framework to predict potent and stable NAbs against DENV-1 to DENV-4 using only antibody (CDR-H3) and epitope sequences as input. Specifically, our proposed computational framework employed sequence-based ML and molecular dynamic simulation (MD) methods to achieve more accurate identification. First, we built a novel dataset (n = 1108) by compiling the interactions of CDR-H3 and epitope sequences with the half maximum inhibitory concentration (IC50) values, which represent neutralizing activities. Second, we achieved an accurately predictive ML model that showed high AUC values of 0.879 and 0.885 by tenfold cross-validation and independent tests, respectively. Finally, our computational framework could be applied to filter approximately 2.5 million unseen antibodies into two final candidates that showed strong and stable binding to all four serotypes. In addition, the most potent and stable candidate (1B3B9_V21) was evaluated for its development potential as a therapeutic agent by molecular docking and MD simulations. This study provides an antibody computational approach to facilitate the high-throughput identification of NAbs and accelerate the development of therapeutic antibodies.

Alkaloid extract of seed Citrullus colocynthis as novel green inhibitor for mild steel corrosion in one molar HCl acid solution: DFT and MC/MD approaches

The study was designed to explore the corrosion prevention capabilities of Citrullus colocynthis seeds alkaloid-rich extract (CSEA) on MS in a 1 M HCl environment by use of electrochemical and theoretical methods. Notably, Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization were used to probe the impact of immersion time and temperature. Energy-dispersive X-ray spectroscopy (EDX) and spanning electron microscopy (SEM) were used to confirm the presence of a protective layer on the substrate surface. Density functional theory (DFT) method was used to optimize the investigated species by use of B3LYP/6–31 + G(d, p) level of theory. The global and local quantum chemical reactivity descriptors were calculated to explore the inhibition corrosion efficiency and to identify the most favorable sites for electrophilic and nucleophilic attacks. Monte Carlo (MC) and molecular dynamics simulation (MDS) methods were used to study the interactions between corrosion inhibitor and metal surface. Noteworthy, results showed that CSEA exhibited an impressive inhibition efficiency, which reached 94.3% with a concentration of 2 g/L at 298 K. Potentiodynamic polarization revealed that the extract acted as a mixed-type inhibitor. Nyquist graphs showed that charge-transfer resistance and dæouble-layer capacitance both rised with increasing CSEA concentration, suggesting better inhibition efficiency. Notably, the Langmuir adsorption isotherm is well-aligned with the adsorption of inhibitor compounds. Importantly, all aforementioned theoretical methods were in agreement with the experimental findings. The outcome of the present work supported using Citrullus colocynthis seeds alkaloid-rich extract as ecofriendly agents to prevent corrosion.

Design of multi-epitope vaccine against porcine rotavirus using computational biology and molecular dynamics simulation approaches

Porcine Rotavirus (PoRV) is a significant pathogen affecting swine-rearing regions globally, presenting a substantial threat to the economic development of the livestock sector. At present, no specific pharmaceuticals are available for this disease, and treatment options remain exceedingly limited. This study seeks to design a multi-epitope peptide vaccine for PoRV employing bioinformatics approaches to robustly activate T-cell and B-cell immune responses. Two antigenic proteins, VP7 and VP8*, were selected from PoRV, and potential immunogenic T-cell and B-cell epitopes were predicted using immunoinformatic tools. These epitopes were further screened according to non-toxicity, antigenicity, non-allergenicity, and immunogenicity criteria. The selected epitopes were linked with linkers to form a novel multi-epitope vaccine construct, with the PADRE sequence (AKFVAAWTLKAAA) and RS09 peptide attached at the N-terminus of the designed peptide chain to enhance the vaccine’s antigenicity. Protein-protein docking of the vaccine constructs with toll-like receptors (TLR3 and TLR4) was conducted using computational methods, with the lowest energy docking results selected as the optimal predictive model. Subsequently, molecular dynamics (MD) simulation methods were employed to assess the stability of the protein vaccine constructs and TLR3 and TLR4 receptors. The results indicated that the vaccine-TLR3 and vaccine-TLR4 docking models remained stable throughout the simulation period. Additionally, the C-IMMSIM tool was utilized to determine the immunogenic triggering capability of the vaccine protein, demonstrating that the constructed vaccine protein could induce both cell-mediated and humoral immune responses, thereby playing a role in eliciting host immune responses. In conclusion, this study successfully constructed a multi-epitope vaccine against PoRV and validated the stability and efficacy of the vaccine through computational analysis. However, as the study is purely computational, experimental evaluation is required to validate the safety and immunogenicity of the newly constructed vaccine protein.