Role Of Molecular Dynamics Simulations Research Articles

The Role of Molecular Dynamics Simulations in Elucidating Interactions between Antimicrobial Peptides and Model Biological Membranes

In addressing the global problem of antimicrobial resistance, an emerging class of molecules called antimicrobial peptides (AMPs) are being widely studied. Their interactions with cell membranes are instrumental in their killing action, usually by forming pores or translocating to act on an internal target. Molecular dynamics (MD) simulations have played an essential role in understanding the atomistic mechanisms of such interactions. This review will highlight key findings from various MD studies, such as the formation of nanoaggregates and different types of pores. We will also discuss the role of selecting the membrane model composition, the level of detail in the simulation, and the choice of force field. It is evident in this review that our understanding of the interactions of AMPs and membranes has grown over the recent years through the help of MD simulations. Still, remaining concerns in MD studies of such systems must be addressed to gain more information.

Molecular dynamics simulations reveal methylation in Me-GDGTs as a microbial low-temperature adaptation

Tetraether membrane lipid glycerol dialkyl glycerol tetraether (GDGT) is a characteristic lipid of archaea that contributes to adaptation to a variety of environments and has been widely used in ecological and geochemical studies. Alkyl-chain methyl-modified GDGTs (Me-GDGTs) as one important component have been detected in both environmental and culture samples. However, the effect of methyl modification on archaeal membrane lipids remains unclear, hampering the development of environmental proxies based on the exact understanding of the underlying mechanism. Here, we reveal the perturbation of molecular order by methyl modification through molecular dynamics simulations, showing that methyl modification can increase membrane fluidity, explaining that this is a form of low-temperature acclimation. This hypothesis was also validated in environmental samples. This study reveals the role of methyl modifications in low-temperature adaptation in archaea, expanding that hydrophobic carbon chain methylation has unified physiological significance in three domain life. Our study highlights the role of molecular dynamics simulations in the development of lipid biomarkers, provides new insights into the mechanisms of temperature adaptation in microorganisms, and lays the groundwork for the development of new environmental proxies.

Molecularly imprinted polymer-based sensors for identification volatile compounds in pharmaceutical products: in silico rational design

The present study aimed to strategically design a Molecularly Imprinted Polymer (MIP) with selective extraction capabilities for volatile compounds found in pork. These specific volatile compounds, such as 3-methyl-1-butanol, 1-nonanal, octanal, hexanal, 2-pentyl-furan, 1-penten-3-one, N-morpholinomethyl-isopropyl-sulfide, methyl butyrate, and (E,E)-2,4-decadienal, are primarily responsible for the distinctive aroma and flavor characteristics associated with pork. Molecular dynamics simulations were employed to investigate the stability of the pre-polymerization system, simulating the interactions between the volatile compounds as templates, 4-hydroxyethyl methacrylate (HEMA) as monomers, and ethylene glycol dimethacrylate (EGDMA) as crosslinkers. Computational simulations revealed that the optimal mole ratio of 1:4:20 for templates, monomers, and crosslinkers resulted in the most favorable functional radial distribution and exhibited the strongest interactions. To validate the computational findings, additional analyses were performed utilizing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), radial distribution function (RDF), and hydrogen bond (HBond) occupancy. The calculated binding free energy demonstrated that all template molecules were capable to bind with both the monomers and crosslinkers, including 1-penten-3-one and N-morpholinomethyl-isopropyl-sulfide displaying the strongest interactions, with values of −12,674 kJ/mol and −11,646 kJ/mol, respectively. The congruence between the results obtained from the molecular simulation analyses highlights the crucial role of molecular dynamics simulations in the study and development of MIP for the analysis of marker compounds present in pork. Communicated by Ramaswamy H. Sarma

Quantum-based machine learning and AI models to generate force field parameters for drug-like small molecules.

Force fields for drug-like small molecules play an essential role in molecular dynamics simulations and binding free energy calculations. In particular, the accurate generation of partial charges on small molecules is critical to understanding the interactions between proteins and drug-like molecules. However, it is a time-consuming process. Thus, we generated a force field for small molecules and employed a machine learning (ML) model to rapidly predict partial charges on molecules in less than a minute of time. We performed density functional theory (DFT) calculation for 31770 small molecules that covered the chemical space of drug-like molecules. The partial charges for the atoms in a molecule were predicted using an ML model trained on DFT-based atomic charges. The predicted values were comparable to the charges obtained from DFT calculations. The ML model showed high accuracy in the prediction of atomic charges for external test data sets. We also developed neural network (NN) models to assign atom types, phase angles and periodicities. All the models performed with high accuracy on test data sets. Our code calculated all the descriptors that were needed for the prediction of force field parameters and produced topologies for small molecules by combining results from ML and NN models. To assess the accuracy of the predicted force field parameters, we calculated solvation free energies for small molecules, and the results were in close agreement with experimental free energies. The AI-generated force field was effective in the fast and accurate generation of partial charges and other force field parameters for small drug-like molecules.

Molecular dynamics simulation the effect of initial pressure on the phase transition performance of coated AlH3 nanoparticles in the presence of an oxygenated medium

In this study, molecular dynamics (MD) simulation is used to study the combustion behavior of coated aluminium hydride (CAH) nanoparticles with ethanol in the presence of an oxygenated medium. The present research investigates the change in the physical quantities such as penetrating oxygen atoms into aluminium hydride (AlH3) nanoparticles, temperature (T) changes, and potential energy (Pe). Lennard-Jones and EAM potential functions are used in this study. The results show that the Pe in the presence of an ethanol atomic coating is −569 eV, the maximum (Max) T is 1322 K, and the number of penetrating oxygen atoms reaches 175. On the other hand, the combustion process in the simulated structure is investigated by increasing initial pressure (P) to the ethanol-coated sample. The results show that with increasing P, the max T decreases from 1102 to 1066 K, and the max Pe increases from −412 eV to −388 eV. The number of penetrated atoms (N) is reduced from 162 to 150, respectively. As a result, the combustion process of CAH nanoparticles is reduced by increasing the P. Since the potential function plays an essential role in MD simulations, the max T and number of penetrated oxygen atoms are investigated with the ReaxFF potential function for a better investigation of the combustion process in the simulated structure. The numerical results show that the max T decreases to 1041 K and the N-oxygen in the simulated structure decreases to 148 atoms with increasing P. The results of MD simulations are sufficiently valid and can be generalized to experimental cases.

Molecular Dynamics Simulation of Glycans

Three-dimensional structural diversity (conformational diversity) of glycans is essential for their biological functions. Molecular dynamics (MD) simulations provide insight into the three-dimensional (3D-) structures of biomolecules in atomic resolution which are difficult to obtain by experiment. However, their highly complex and flexible structures make glycans difficult to simulate. This minireview summarizes recent challenges in MD simulations of glycans using enhanced sampling techniques. Using MD simulations, various 3D-structures are revealed at atomic resolution, not only for isolated glycans but also for glycoconjugates and glycan-bound complexes. The role of MD simulations is not limited for interpretation of experimental results. The simulations are used to predict experiments, leading the integrated computational and experimental studies on the structure-function relationship of glycans. We hope that this article will help prompt various integrated studies of glycans in the future.

Viscosity, Shear Waves, and Atomic-Level Stress-Stress Correlations

The Green-Kubo equation relates the macroscopic stress-stress correlation function to a liquid's viscosity. The concept of the atomic-level stresses allows the macroscopic stress-stress correlation function in the equation to be expressed in terms of the space-time correlations among the atomic-level stresses. Molecular dynamics studies show surprisingly long spatial extension of stress-stress correlations and also longitudinal and transverse waves propagating in liquids over ranges which could exceed the system size. The results reveal that the range of propagation of shear waves corresponds to the range of distances relevant for viscosity. Thus our results show that viscosity is a fundamentally nonlocal quantity. We also show that the periodic boundary conditions play a nontrivial role in molecular dynamics simulations, effectively masking the long-range nature of viscosity.

Tilt and Azimuthal Angles of a Transmembrane Peptide: A Comparison between Molecular Dynamics Calculations and Solid-State NMR Data of Sarcolipin in Lipid Membranes

We report molecular dynamics simulations in the explicit membrane environment of a small membrane-embedded protein, sarcolipin, which regulates the sarcoplasmic reticulum Ca-ATPase activity in both cardiac and skeletal muscle. In its monomeric form, we found that sarcolipin adopts a helical conformation, with a computed average tilt angle of 28 ± 6° and azymuthal angles of 66 ± 22°, in reasonable accord with angles determined experimentally (23 ± 2° and 50 ± 4°, respectively) using solid-state NMR with separated-local-field experiments. The effects of time and spatial averaging on both 15N chemical shift anisotropy and 1H/ 15N dipolar couplings have been analyzed using short-time averages of fast amide out-of-plane motions and following principal component dynamic trajectories. We found that it is possible to reproduce the regular oscillatory patterns observed for the anisotropic NMR parameters (i.e., PISA wheels) employing average amide vectors. This work highlights the role of molecular dynamics simulations as a tool for the analysis and interpretation of solid-state NMR data.

Comment on “Excitations in photoactive molecules from quantum Monte Carlo” [J. Chem. Phys. 121, 5836 (2004)

It is shown that the qualitative differences between high-level ab initio calculations and restricted open-shell Kohn-Sham (ROKS) results for the lowest singlet excited electronic state of formaldimine along a particular isomerization path found by Schautz, Buda, and Filippi [J. Chem. Phys.121, 5836 (2004)] play a minor role in molecular dynamics simulations of photoisomerization at room temperature. In fact, ROKS yields, within its well-known limitations, a good representation of the physically relevant isomerization pathway.

Sequence-dependent elastic properties of DNA

Harmonic elastic constants of 3–11 bp duplex DNA fragments were evaluated using four 5 ns unrestrained molecular dynamics simulation trajectories of 17 bp duplexes with explicit inclusion of solvent and counterions. All simulations were carried out with the Cornell et al. force-field and particle mesh Ewald method for long-range electrostatic interactions. The elastic constants including anisotropic bending and all coupling terms were derived by analyzing the correlations of fluctuations of structural properties along the trajectories. The following sequences have been considered: homopolymer d(ApA)n and d(GpG)n, and alternating d(GPC)n and d(APT)n. The calculated values of elastic constants are in very good overall agreement with experimental values for random sequences. The atomic-resolution molecular dynamics approach, however, reveals a pronounced sequence-dependence of the stretching and torsional rigidity of DNA, while sequence-dependence of the bending rigidity is smaller for the sequences considered. The earlier predicted twist-bend coupling emerged as the most important cross-term for fragments shorter than one helical turn. The calculated hydrodynamic relaxation times suggest that damping of bending motions may play a role in molecular dynamics simulations of long DNA fragments. A comparison of elasticity calculations using global and local helicoidal analyses is reported. The calculations reveal the importance of the fragment length definition. The present work shows that large-scale molecular dynamics simulations represent a unique source of data to study various aspects of DNA elasticity including its sequence-dependence.

Molecular dynamics simulations of particle-surface interactions

The role of molecular dynamics simulations as a tool for understanding the interaction of energetic particles with crystal surfaces is discussed. The simulations can be used to describe the physical state of the surface after such interactions and the dynamic development of the resulting surface damage can be examined. The results of particle impacts depend on the energy, incidence angle of the projectile and the projectile and substrate species. We demonstrate that single impact craters can form on silicon while bumps are formed on graphite.

Molecular Dynamics Studies of Bacteriorhodopsin's Photocycles

AbstractThe availability of the structure of bacteriorhodopsin from electron microscopy studies has opened up the possibility of exploring the proton pump mechanism of this protein by means of molecular dynamics simulations. In this review we summarize earlier theoretical investigations of the photocycle of bacteriorhodopsin including relevant quantum chemistry studies of retinal, structure refinement, molecular dynamics simulations, and evaluation of pKa values. We then review a series of recent modeling efforts which refined the structure of bacteriorhodopsin adding internal water, and which studied the nature of the J intermediate and the likely geometry of the K590 and L550 intermediates (strongly distorted 13‐cis) as well as the sequence of retinal geometry and protein conformational transitions which are conventionally summarized as the M412 intermediate. We also review simulations of the photocycle of light‐adapted bacteriorhodopsin at T=77 K and of the photocycle of dark‐adapted bacteriorhodopsin, both cycles differing from the conventional photocycle through a nonfunctional (pure 13‐cis) retinal geometry of the corresponding K590 and L550 states. The simulations demonstrate a potentially critical role of water and of minute reorientations of retinal's Schiff base nitrogen in controlling proton pumping in bR568; the simulations also indicate the existence of heterogeneous photocycles. The results exemplify the important role of molecular dynamics simulations in extending investigations on bacteriorhodopsin to a level of detail which is presently beyond experimental resolution, but which needs to be known to resolve the pump mechanism of bacteriorhodopsin. Finally, we outline the major existing challenges in the field of bacteriorhodopsin modeling.

The Role of Molecular Dynamics Simulations for the Study of Slow Dynamics

Abstract A two step strategy is proposed to study dynamical properties of a physical system much slower than the time scales accessible by molecular dynamics simulations. The strategy is applied to investigate the slow dynamics of supercooled liquids.