MD Simulation Method Research Articles

Mechanical and electrochemical characterization of CuAlNi alloys

The effect of copper composition on the structure and mechanical properties of CuxAlNi alloys was investigated using MD simulation and characterization methods. It was found that the structure of CuxAlNi alloys markedly resembles Cu composition, which alterations from the initial single (FCC) to (BCC) structure and then to a duplex BCC structure as the Cu content is raised. Nanoindentation measurements show that the hardness of CuAlNi alloys increases with Cu content. When there are more Al elements, the surface of the material is first combined with ions in seawater so that the corrosion potential is significantly reduced. This research seeks to identify CuAlNi alloys with improved properties through molecular dynamics simulations and experimental analyses, highlighting the connections between microstructure and mechanical behavior.

Impact of mixing low-reactivity gases on the mechanism of hydrogen spontaneous combustion: A ReaxFF MD study

The phenomenon of spontaneous combustion during the release of high-pressure H2 is critical to the safe storage and transportation. Besides physical methods to suppress self-ignition, the approach of mixing low-reactivity gases has gained increasing attention. Previous work has mainly focused on the flow, physical heating effects, and boundary conditions of self-ignition in mixed gases, while the intrinsic chemical reaction mechanisms of spontaneous combustion remain underexplored. To clear this issue, this work uses the ReaxFF MD simulation method to study the spontaneous combustion process of H2/CO and H2/CH4 mixtures with various concentrations. The results indicate that: (1) in pure H2, H2/CO, and H2/CH4 systems, the primary initial reaction mechanism is H2+O2HO2+H. Additionally, in some mixed systems, CO + O2CO2+O and CH4+O2CH3+HO2 may also serve as initial reaction mechanisms. (2) Under fuel-lean combustion conditions, the RIDTs of the systems decrease, supporting the viewpoint that self-ignition typically occurs first in fuel-lean regions. The addition of CO and CH4 increases the RIDTs, which helps inhibit the development of self-ignition. (3) In H2-rich environments, CO combusts to CO2 through the formation of HOCO, while CH4 undergoes dehydrogenation and oxidation processes through intermediates such as CH3, CH3O, and HCHO, leading to the formation of CO and CO2. The combustion of H2 is also influenced by these processes. (4) The addition of CO and CH4 increases the activation energy of H2 combustion, raising the reaction energy barrier that must be overcome for spontaneous combustion. This effectively helps to suppress the occurrence and development of self-ignition during the release of high-pressure gases.

Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials

Efficiently creating a concise but comprehensive data set for training machine-learned interatomic potentials (MLIPs) is an under-explored problem. Active learning, which uses biased or unbiased molecular dynamics (MD) to generate candidate pools, aims to address this objective. Existing biased and unbiased MD-simulation methods, however, are prone to miss either rare events or extrapolative regions—areas of the configurational space where unreliable predictions are made. This work demonstrates that MD, when biased by the MLIP’s energy uncertainty, simultaneously captures extrapolative regions and rare events, which is crucial for developing uniformly accurate MLIPs. Furthermore, exploiting automatic differentiation, we enhance bias-forces-driven MD with the concept of bias stress. We employ calibrated gradient-based uncertainties to yield MLIPs with similar or, sometimes, better accuracy than ensemble-based methods at a lower computational cost. Finally, we apply uncertainty-biased MD to alanine dipeptide and MIL-53(Al), generating MLIPs that represent both configurational spaces more accurately than models trained with conventional MD.

Spectroscopy combined with spatiotemporal multiscale strategy to study the adsorption mechanism of soybean protein isolate with meat flavor compounds (furan): Differences in position and quantity of the methyl

The interaction mechanism between soybean protein isolate (SPI) and furan flavor compounds with different structures is studied using spectroscopy, molecular docking, and MD simulation methods. The order of binding ability between SPI and furan flavor compounds is 2-acetylfuran>furfural>5-methylfurfural. The structural differences (position and quantity of methyl groups) of three furan flavor compounds are key factors leading to the different adsorption abilities of SPI for furan flavor compounds. The findings from spectroscopy analyses suggest that the interaction between SPI and furan flavor compounds involves both static and dynamic quenching mechanisms, with static quenching being the main factor. Molecular docking and MD simulations reveal the atomic-level mechanisms underlying the stable binding for SPI and furan flavor compounds at spatiotemporal multiscale. This study provides a theoretical framework for the production and adjustment of meat essence formula in the production of soybean protein-based meat products.

Mechanical and viscoelastic characterization of Al2O3 based polymer nanocomposites: An experimental and molecular dynamics simulation approach

Polymer nanocomposites (PNCs) being revolutionary materials, comprises polymer matrix phase and nanoparticles (NPs) phase. This study focuses on incorporating alumina (Al2O3) into poly-dimethyl siloxane (PDMS) matrix to analyze viscoelastic behavior and damping in response to dynamic mechanical loading. The experiments were performed using nano-DMA for comparing how Al2O3 reinforcement influences structural conformations and dynamic properties of PNCs. At 100 Hz, the storage modulus (E′) increases by 150%, 20%, and 74% for 1.0 wt% NPs with average particle sizes of 25 nm, 80 nm, and 200 nm, respectively. The significant changes in storage modulus and hardness values occur during variable frequencies (10 to 50 Hz) for 1.0 wt%, 9.0 wt%, and 7.0 wt% with reinforcements of 25 nm, 80 nm, and 200 nm, respectively. Adhesion factor and reinforcement efficiency factor highlight complementary effects of reinforcements at different frequencies. Further, an all-atom MD simulation method characterizes static and dynamic properties, predicting comprehensive dynamical and structural–property relationships. This quantifies damping capacity and reveals insights into how Al2O3 alters the material’s behavior. In summary, the study provides a precise comparative analysis of overall PNC performance, emphasizing the intrinsic effect on mechanical properties. It recognizes deformation mechanisms driving energy storage and dissipation for developing PNCs with enhanced mechanical performance.

Identification of Dual-Target Inhibitors for Epidermal Growth Factor Receptor and AKT: Virtual Screening Based on Structure and Molecular Dynamics Study.

Epidermal growth factor EGFR is an important target for non-small cell lung (NSCL) cancer, and inhibitors of the AKT protein have been used in many cancer treatments, including those for NSCL cancer. Therefore, searching small molecular inhibitors which can target both EGFR and AKT may help cancer treatment. In this study, we applied a ligand-based pharmacophore model, molecular docking, and MD simulation methods to search for potential inhibitors of EGFR and then studied dual-target inhibitors of EGFR and AKT by screening the immune-oncology Chinese medicine (TCMIO) database and the human endogenous database (HMDB). It was found that TCMIO89212, TCMIO90156, and TCMIO98874 had large binding free energies with EGFR and AKT, and HMDB0012243 also has the ability to bind to EGFR and AKT. These results may provide valuable information for further experimental study.

Hydrodynamic radius of dendrimers in solvents.

The diffusion properties and hydrodynamic radius, Rh, of macromolecules are important for theoretical studies and practical application. Moreover, comparison of Rh values obtained from simulation and experimental data is used to check the correctness of simulation results. Here, we study the translation mobility of poly(butylcarbosilane) dendrimers in chloroform solution using molecular dynamics simulations and consider simulation details that may influence the accuracy of the result. Different methods to estimate Rh for a dendrimer are discussed with comparison to our experimental data. It was shown that the traditional MD simulation method for extraction of the diffusion coefficient (and calculation of Rh) of dendrimers as a rule faces difficulties and requires simulation resources several times greater than, for example, the same for a linear analogue. In the majority of MD simulation papers, the diffusion coefficient and/or Rh are calculated incorrectly. Also, we establish that correction of Rh according to the simulation box or estimation of Rh by using the gyration radius does not give values close to experimental data. To avoid the mentioned problems, we found an alternative way: to consider rotational diffusion, which gives an Rh similar to that from experiment and is practically independent of the size of the simulation box and other simulation parameters.

In Silico Study of the Influences of Cooling Rates on the Phase Transition of Water Inside the Carbon Nanotube under Different Ambient Pressures

By using MD simulation method, this study shows the influences of cooling rates on the solidifying temperature of water inside a single-wall-carbon-nanotube under different ambient pressures when cooling the systems from 300 K down to 200 K. Our results showed that the more rapid cooling rate of the systems creates more disruptive and dramatic phase transitions. Moreover, we also found that the lower of pressures correlates to the more dramatic phase transitions of water, regardless of cooling rate. This study generally provides more insight into water behavior in the SWCNT with variations in ambient conditions.

Regulation mechanism of coal gasification in supercritical water for hydrogen production: A ReaxFF-MD simulation

The regulation study on coal gasification process in supercritical water (SCW) can promote the hydrogen production and upgrading of coal utilization. ReaxFF molecular dynamics simulation integration with representative coal model was first introduced to investigate the regulation mechanism of liquid organics on coal gasification in SCW. Hongliulin coal model was constructed and verified its rationality and accuracy. Among the liquid organics, phenols exhibit a positive effect with the H2 number increasing above 34%. The regulation mechanism is dug deeper into from the perspective of the intermolecular interaction and reactive sites. EvdWaals is the main driving force and a maximum of reaction capability of coal molecules reaches 11.01 kJ/mol. The key reaction process in which the hydrogen is greatly improved is the degradation of heavy components under the regulatory effect of phenol. Moreover, the reactive sites of aromatic structure also change from the side chain to conjugated rings. Degradation mechanism of heavy components in the SCWG of coal is summarized. The experimental results verify that H2 yield is increased by 59% and the solid mass is reduced to 0.72 mg with phenol. This conclusion demonstrated the feasibility of the ReaxFF MD simulation method to guide the clean utilization and industrial application of coal gasification in SCW.

The role of Acinetobacter baumannii CarO outer membrane protein in carbapenems influx

The gram-negative strain Acinetobacter baumannii is a cocobacillus, non-motile and aerobic organism that is often found in nosocomial infections. Many institutions worldwide such as WHO are grappling with antibiotic resistance A. baumannii. Therefore, in recent years, there have been many studies in the literature about antibiotic resistance mechanisms. We studied the specificity of carbapenems for CarO, an outer membrane protein associated with imipenem-resistance that was strongly related to a decrease in CarO expression level or changes in protein structure. The specificity of five different carbapenems, imipenem, biapenem, ertapenem, faropenem, and meropenem, against the A. baumannii ATCC-17978 CarO protein, as well as the specificity of imipenem for five different types Type-1, Type-2, Type-3, Type-4, and ATCC-17978 CarO protein, were investigated using computational methods. In this study, homology modeling, molecular docking, membrane–protein complex building, and 800 ns long MD simulation methods were followed. The interactions of imipenem with the extracellular region of five different forms of CarO protein were investigated in this study, as well as five different antibiotic binding profiles to the model organism ATCC-17978 CarO protein. The mechanism of CarO influx has been revealed with this study at the molecular level and this data is intended to be used in future research, mutagenesis, and clinical trials.

Structural Insights into the IL12:IL12 Receptor Complex Assembly by Molecular Modeling, Docking, and Molecular Dynamics Simulation

Background: Interleukin-12 receptor (IL12R) is a type I cytokine receptor that can promote hematopoiesis and regulate innate and adaptive immunity. It binds with the IL12 ligand, which activates the IL-12 signaling pathway that triggers hematopoietic progenitor cell proliferation and differentiation process. The structure of IL12:IL12R complex is not known. Objective: The present work describes a de novo computational method for rational protein designing to elucidate the structure of IL12:IL12R complex. Methods: Homology modeling, docking, and MD simulation methods were used to design mimics of the interaction of IL12 and IL12R. Results: 3D structure prediction and validation confirms the accurate structure of IL12R protein that contains immunoglobin domain, fibronectin type three domain, cytokine-binding domain, and WSXWS motif. Molecular docking and MD simulation revealed that IL12R bound tightly with IL12 ligand at their interface. The estimated binding energy of the docked complex was -26.7 kcal/mol, and the interface area was 281.4 Å2. Hotspot prediction suggested that ARG34, SER58, GLU61, CYS62, LEU63, SER73, ASP142, GLN146, LYS168, THR169 ARG181, ARG183, ARG189, and TYR193 residues in IL12 ligand interacted with SER175, ALA176, CYS177, PRO178, ALA179, ALA180, GLU181, GLU182, ALA192, VAL193, HIS194, ARG208, TYR246, GLN289, ASP290, ARG291, TYR292, TYR293 and SER294 residues in IL12 receptor. Conclusion: The results of the study provides a simulated molecular structure of IL12:IL12R complex that could offer a promising target complex to substantiate IL12 based drug-designing approaches.

Influence of external electric field on polymerization of Fe (III) flocculant in water: A reactive molecular dynamics and experiment study

In the present study, a novel method of electrochemically enhancing hydrolysis of Fe (III) was proposed. The influence of an external electric field (EEF) on initial polymerization of Fe(III) was investigated by using reactive MD simulation method. It is examined in term of the structural property (radial distribution function), bond order, electrostatic energy, polymerization products, and kinetic characteristic (self-diffusion coefficient) in the hydrolysis system. Then an experimental study was carried out to verify the MD simulation conclusions. The results show that EEF can shorten the distance between Fe3+ ions, enhance the bonding strength between Fe3+ ions, enhance the activity of particles, thus promote the formation of dimer [Fe2(OH)2(H2O)8]4+, and further produce particles with larger size and surface area, which is beneficial to enhance the ability of particles to adsorb impurities. Then the experimental results of particle size distribution of FeCl3 flocculating particles and the Zeta potential of the FeCl3 solution under different EEF meet well with the MD simulation conclusions. The method of electrochemically enhancing hydrolysis proposed in this paper is expected to effectively improve the flocculation performance of ferric chloride, and then reduce the dosage of ferric chloride in practical application.

CHARMM-GUI high-throughput simulator

Structure-based virtual screening is a computational approach widely used in the early-stage drug discovery workflow to develop novel therapeutic agents against certain drug target. In our previous study, we presented a high-throughput protein-ligand complex MD simulation method to improve docking results in discriminating small molecule binders from nonbinders. In this work, we present CHARMM-GUI High-Throughput Simulator (HTS) that is an intuitive web-based tool to improve docking results of protein-ligand complex structures in a high-throughput manner using MD simulations.

Affinity enhancement of CR3022 binding to RBD; in silico site directed mutagenesis using molecular dynamics simulation approaches

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a disease which caused by a novel beta coronavirus. Structural and non-structural proteins are expressed by the virus gene fragments. The RBD of the S1 protein of the virus has the ability to interact with potent antibodies including CR3022, which was characterized to target the S protein of the virus which can efficiently neutralize the SARS-CoV in vitro and in vivo. In current study, we aimed to design CR3022 based antibody with high affinity compared with wild-type CR3022 using MD simulation method. Two variants were designed based on the amino acid binding conformation and the free binding energy of the critical amino acids which involved in CR3022-RBD interactions were evaluated. In this study three complexes were evaluated; CR3022-RBD, V1-RBD and V2-RBD using molecular dynamics simulations carried out for 100 ns in each case. Then, all the complexes were simulated for 100 ns. In the next step, to calculate the free binding affinity of the wild CR3022 and mutant antibody (V1 and V2) with RBD, the PMF method was performed. The RMSD profile demonstrated that all three complexes were equilibrated after 85 ns. Furthermore, the free binding energy results indicated that the V2-RBD complex has the higher binding affinity than V1-RBD and CR3022-RBD complexes. It should be noted that in above variants, the electrostatic energy and the number of H-bonds between the antibody and RBD increased. Thus, it is suggested that both designed antibodies could be considered as appropriate candidates for covid-19 disease treatment. Communicated by Ramaswamy H. Sarma

Molecular dynamics simulation of thermodynamic properties and local structure of Na2CO3-K2CO3 eutectic salt during phase transition

In this paper, the thermodynamic properties and local structure of Na2CO3-K2CO3 eutectic salt were simulated by using Born Mayer potential function. The phase transition temperature, solid specific heat capacity (Cp), liquid Cp and density of Na2CO3-K2CO3 eutectic salt were obtained by molecular dynamics calculation. Compared with the experimental results, the error of phase transition temperature, solid Cp(550K-650 K) were 6.32% and 1.61% respectively, which verified the accuracy and reliability of MD simulation method. Moreover, the local microstructure of Na2CO3-K2CO3 eutectic salt was characterized by radial distribution functions (RDF) and angular distribution functions (ADF), combined with the simulated results of the thermodynamic properties, revealed the variation of Cp, density, coefficient of thermal expansion and viscosity with the increasing temperature. Furthermore, the change of ions during the solid-liquid phase transition of Na2CO3-K2CO3 eutectic salt was analyzed from the microscopic point of view, and the microstructure of Na2CO3-K2CO3 eutectic salt in the solid-liquid phase was obtained.

ReaxFF Molecular Dynamics Simulations of Thermal Reactivity of Various Fuels in Pyrolysis and Combustion

The methodology development and applications of ReaxFF molecular dynamics (ReaxFF MD) in unraveling the complex reactions and kinetics for pyrolysis and oxidation of organic systems are reviewed. Particular attention is given to the large-scale ReaxFF MD simulation method of similar to 10,000 atoms and practical simulation strategies to overcome the temporal-spatial limits as much as possible. High-performance computing codes running on CPU cluster/supercomputers and on GPU were overviewed. GPU-enabled code like GMD-Reax is revolutionizing large-scale ReaxFF MD simulations to run mainly on a single GPU. A step-forward for reaction analysis was achieved in the code of VARxMD to reveal detailed reactions based on the identification of bond types and unique species that allows for categorization of reaction species and pathways through structure searching of reaction sites and reactants/products. Efforts for extracting rate constants and kinetics modeling from unperturbed kinetics of ReaxFF MD simulations are reviewed, and challenges remain. The important factors of model scale effects, elevated simulation temperature, and possible validation of ReaxFF MD reaction simulation results theoretically and experimentally are illustrated and discussed. The novel hybrid simulation strategies proposed recently that may expand applications of ReaxFF MD to connect with realistic scenarios of engine combustion and relevant chemical effects on aerospace vehicle materials are briefed. The simulation practices of large-scale ReaxFF MD in understanding the similarities and differences of reactivity and reaction mechanisms in pyrolysis of liquid hydrocarbon fuels, solid fuels (coal, biomass, polymer), and energetic materials of CL-20 and its cocrystals are briefly described, which indicates that large-scale ReaxFF MD simulations are a feasible and straight means to capture the dynamics of an almost entire reaction process and to evaluate reactivity of organic systems computationally. There is still a great deal of work to be done to push the boundaries of ReaxFF MD simulations forward. With the constant improvement of the ReaxFF force field and reaction analysis capability, ReaxFF MD playing a key role in understanding reaction mechanisms and its potential in kinetics modeling of pyrolysis and oxidation of various fuels can be expected.

Elucidating multiple-scale reaction behaviors of phenolic resin pyrolysis via TG-FTIR and ReaxFF molecular dynamics simulations

Phenolic resin is a matrix material widely used in ablative thermal protection systems (TPS) and its pyrolysis behavior is crucial for the analysis and prediction of TPS thermal response. However, it still remains a huge challenge to elucidate the involved reaction mechanisms due to the process complexity and unpredictability. Herein, a combination of TG-FTIR and ReaxFF MD simulation method was adapted to explore phenolic resin pyrolysis mechanism. Experiment results indicate that the pyrolysis process of phenolic resin can be divided into three stages, and the activation energy of each stage increases gradually. Heating rate affects the initial pyrolysis temperature of phenolic resin, but has no obvious effect on the types of pyrolysis products. Additionally, an accurate and reasonable decomposition kinetic model is established based on 30 kinds of kinetic function models, involving diffusion, random nucleation and nuclei growth, phase interface reaction and chemical reaction. The cook-off simulations results suggest that the major pyrolysis products of phenolic resin at high temperature include H2, CO, C2H2, and H2O, which formation mechanisms are also discussed according to the simulation trajectories. The reaction model and the activation energy of phenolic resin pyrolysis based on simulations are in good agreement with the experimental results, contributing to the deep understanding of phenolic resin pyrolysis behaviors at atom scale. This study may provide theoretical data basis for the establishment of thermal response calculation model of resin-based composite thermal protection materials.

Probing Protein-protein Interactions and Druggable Site Identification: Mechanistic Binding Events Between Ubiquitin and Zinc Finger with UFM1-specific Peptidase Domain Protein (ZUFSP).

Deubiquitinating enzymes (DUBs) protein family have been implicated in some deregulated pathways involved in carcinogeneses, such as cell cycle, gene expression, and DNA damage response (DDR). Zinc finger with UFM1-specific peptidase domain protein (ZUFSP) is one of the recently discovered members of the DUBs. To identify and cross-validate the ZUFSP binding site using the bioinformatic tools, including SiteMap&Metapocket, respectively. To understand the molecular basis of complementary ZUFSP-Ub interaction and associated structural events using MD Simulation. In this study, four binding pockets were predicted, characterized, and cross-validated based on physiochemical features such as site score, druggability score, site volume, and site size. Also, a molecular dynamics simulation technique was employed to determine the impact of ubiquitin-binding on ZUFSP. Site 1 with a site score 1.065, Size 102, D scores 1.00, and size volume 261 was predicted to be the most druggable site. Structural studies revealed that upon ubiquitin-binding, the motional movement of ZUFSP was reduced when compared to the unbound ZUFSP. Also, the ZUFSP helical arm (ZHA) domain orient in such a way that it moves closer to the Ub; this orientation enables the formation of a UBD which is very peculiar to ZUFSP. The impact of ubiquitin on ZUFSP movement and the characterization of its predicted druggable site can be targeted in the development of therapeutics.

Water distillation modeling by disjoint CNT-based channels under the influence of external electric fields.

Using molecular dynamics method, the ion rejection and water flow inside flexible disjoint carbon-based channels were examined in the presence of electric fields. The effects of the carbon nanotube diameters and field magnitude on the nano-channel efficiency were investigated. It was observed that water flow through the filter was modified by increasing the radius of nanotubes, while the salt rejection was reduced. The particles' behaviors inside the channel were described in view of Van der Waals interactions between the water molecules, ions, and carbon atoms. Furthermore, the results indicated that the ion rejection and water flow were increased under the application of proper magnitude of electric fields. Graphical abstract Using MD simulation method, a disjoint CNT-based filter was designed to produce freshwater from a NaCl solution by the aid of external electric field. It was observed that the filter operation was significantly affected by channel structural parameters and amount of applied electric fields.

Quantitative structure-properties relationship and molecular design of some anti-wear lubricant additives

In-silico QSPR and MD simulation methods were adopted to effectively design new lubricant anti-wear additive compounds as an alternative to zinc dialkyl dithiophosphate (ZDDP) which was reported to contribute to environmental pollution. Some QSPR linear models were developed out of which the best model (With statistical analysis R2 = 0.990, R2pred. = 0.818, R2adj = 0.979, R2cv = 0.748) was used to design three new additive structures with an improved anti-wear lubricant properties. Three lubricant additives such as 2-(hept‑1-en-2 ylthio)benzo[d]oxazole, 2-((5-methylhex-5-en-1-yl)thio)benzo[d]oxazole and 2-((5-methyl-2-methylenehex-5-en-1-yl)thio)benzo[d]oxazole were designed and revealed to have anti-wear properties of 0.593, 0.512, and 0.367 mm respectively. These anti-wear lubricant properties of all the designed additives were found to be better than the bench-mark anti-wear additive, ZDDP (3.284 mm) and what other researchers proposed. Moreover, The dynamic binding energies of all the designed anti-wear lubricant additives were found to be bound better than the one calculated by other researchers and was found to be excellently bound also than the commercially sold (benchmark additive) additive (ZDDP) 24,365.405. The addition of acceptor substituent like =CH2 groups to the hydrocarbon chain structures of all the newly designed additives was noticed to have improved lubricant wear-reduction properties and binding dynamic energies of the new additives on the simulated steel coated surface. Therefore, these QSPR and MD methods could be used to provide a theoretical framework for researchers and industrialists to design an improved anti-wear additive properties and save resources before expensive laboratory trial and error method.