Molecular dynamics applied to nucleic acids

In this Account, we focus on molecular dynamics (MD) simulations involving fully solvated nucleic acids. Historically, MD simulations were first applied to proteins and several years later to nucleic acids. The first MD simulations of DNA were carried out in vacuo, but nowadays fully solvated systems are common practice. Recently, technical improvements have made it possible to conduct accurate MD simulations of highly charged nucleic acids. The state-of-the-art of MD simulations and a number of applications on various nucleic acid systems are discussed.     

静电作用力算法对分子动力学模拟结果的影响分析

蛋白质分子和界面之间的作用在药物输送以及生物分离等领域至关重要。利用分子动力学模拟考察蛋白质分子在界面附近的行为是最近10年研究的热点。在早期的工作中,Wang等发现同电荷离子交换介质可用于辅助蛋白质复性,但其机理不甚明确。在利用分子动力学模拟研究其分子机理时发现,不同静电作用力参数对模拟结果有直接的影响。因此,通过全原子分子动力学模拟考察不同静电参数条件对模拟结果的影响,展示此过程的构象和能量变化,分析了造成结果差异的原因。研究结果揭示了不同静电参数对模拟结果的影响,为进一步研究蛋白质在界面表面的行为奠定了一定的理论基础。     

Coarse-Grained and Atomistic MD Simulations of RNA and DNA Folding

Although the main features of the protein folding problem are coming into clearer focus, the microscopic viewpoint of nucleic acid folding mechanisms is only just beginning to be addressed. Experiments, theory, and simulations are pointing to complex thermodynamic and kinetic mechanisms. As is the case for proteins, molecular dynamics (MD) simulations continue to be indispensable tools for providing a molecular basis for nucleic acid folding mechanisms. In this review, we provide an overview of biomolecular folding mechanisms focusing on nucleic acids. We outline the important interactions that are likely to be the main determinants of nucleic acid folding energy landscapes. We discuss recent MD simulation studies of empirical force field and Go-type MD simulations of RNA and DNA folding mechanisms to outline recent successes and the theoretical and computational challenges that lie ahead.     

Scaling properties in the molecular structure of three-dimensional, nanosized phenylene-based dendrimers as studied by atomistic molecular dynamics simulations

Three-dimensional polyphenylene dendrimers (PDs) can be prepared in ways that enable control of their shape. Their structures may be used as scaffolds with a wide variety of functionality, enabling them to be used as functional nanoparticles with a large range of possible applications, ranging from light emitting devices to biological sensors or drug delivery tools. As PDs have been synthesized only recently, their structural and chemico-physical characterization is still in its infancy. Accordingly, in this paper the shape and internal organization of three PD families based on three different cores were probed by accurate, atomistic molecular dynamics simulations (MD). Particular care was taken to ensure complete structural equilibration by implementing an MD simulated annealing protocol prior to evaluation of the molecular structure and dynamics. All dendrimer families were found to be characterized by molecular dimensions in the nano-range, and by a shape-persistent, non-spherical structure, of molecular fractal dimension around 2.5-2.6, and of surface fractal dimension practically constant and almost equal to 2 with increasing generations in all cases. The MD analysis revealed also that, for this type of dendrimers, the starburst limited generation is presumably located in correspondence of the third generation.     

The role and perspective of ab initio molecular dynamics in the study of biological systems

Ab initio molecular dynamics (MD) allows realistic simulations to be performed without adjustable parameters. In recent years, the technique has been used on an increasing number of applications to biochemical systems. Here we describe the principles on which ab initio MD is based. We focus on the most popular implementation, based on density functional theory and plane wave basis set. By a survey of recent applications, we show that despite the current limitations of size and time scale, ab initio MD (and hybrid ab initio MD/MM approaches) can play an important role for the modeling of biological systems. Finally, we provide a perspective for the advancement of methodological approaches which may further expand the scope of ab initio MD in biomolecular modeling.     

Self-Assembly of Diamondoid Molecules and Derivatives (MD Simulations and DFT Calculations)

We report self-assembly and phase transition behavior of lower diamondoid molecules and their primary derivatives using molecular dynamics (MD) simulation and density functional theory (DFT) calculations. Two lower diamondoids (adamantane and diamantane), three adamantane derivatives (amantadine, memantine and rimantadine) and two artificial molecules (ADM•Na and DIM•Na) are studied separately in 125-molecule simulation systems. We performed DFT calculations to optimize their molecular geometries and obtained atomic electronic charges for the corresponding MD simulation, by which we predicted self-assembly structures and simulation trajectories for the seven different diamondoids and derivatives. Our radial distribution function and structure factor studies showed clear phase transitions and self-assemblies for the seven diamondoids and derivatives.     

Molecular Modelling—an Enabling Technology for Chemical Engineers

This article briefly describes the basic concepts involved in the two most commonly used molecular modelling methods—molecular dynamics (MD) and Monte Carlo (MC). The methods are particularly useful for studying structures at the length scale of nanometre. Two examples (both are on the study of the miscibility of polyolefin blends) are used to illustrate the techniques. It is demonstrated that it is the nano‐scaled structures formed by the segments of the constituent polyolefins that prevent them from mixing with each other. The examples also show that selection of specific method (MD or MC) depends on the nature of the problem in hand. In general, MC is more efficient than MD in terms of generating equilibrated structure while MD can provide information about the dynamics of a system. This is simply because MD requires the solution of equations of motion (a set of second order differential equations) while MC does not. Nonetheless, both methods need a reasonably accurate force field.     

Development of RYUGA for three-dimensional dynamic visualization of molecular dynamics results

We have developed a new computer graphics (CG) code RYUGA for three-dimensional dynamic visualization of molecular dynamics (MD) results. The applicability of RYUGA for visualizing and analyzing the dynamics of atomic motions in various materials was demonstrated. RYUGA supports various functions, such as solid-modeling CG pictures (called the CPK model), CG animation of the MD results, Miller plane cutting of crystal structures, building graphs, etc., similar to other CG codes for MD simulation. In addition, RYUGA has a number of advantages as follows: (i) a perspective is employed for drawing CG pictures, (ii) three-dimensional trajectories of atoms can be constructed, (iii) an operator can travel inside the materials, (iv) graphic speed and animation speed are enhanced because of the specific algorithms, and (v) it works on any workstations, moreover even personal computers with a UNIX operating system and an X window system are available.     

Collective deformations in proteins determined by a mode analysis of molecular dynamics trajectories

A systematic method of representing and analyzing the intramolecular strains in proteins is proposed. For illustrative purposes, the method is applied to the N-terminal fragment of the human T-cell glycoprotein CD4. The method is based on the singular value decomposition (SVD) of molecular dynamics (MD) trajectories. The slowest three modes of motion that carry information along the protein molecule over large length scales are analyzed, so as to characterize the collective motions and the resulting strains along the three principal axes of the protein. Strong cooperative motions of different types, mainly wave-like, wagging, wiggling, breathing, bending and shearing motions, and rigid body rotations are distinguished. The mean-square fluctuations of C^α-atoms induced by the three dominant modes are found to exhibit a closer correlation with the experimental temperature factors in the presence of solvent.     

Thermodynamic Insight into the Effects of Water Displacement and Rearrangement upon Ligand Modifications using Molecular Dynamics Simulations

Computational methods, namely molecular dynamics (MD) simulations in combination with inhomogeneous fluid solvation theory (IFST) were used to retrospectively investigate various cases of ligand structure modifications that led to the displacement of binding site water molecules. Our findings are that water displacement per se is energetically unfavorable in the discussed examples, and that it is merely the fine balance between change in protein–ligand interaction energy, ligand solvation free energies, and binding site solvation free energies that determine if water displacement is favorable or not. We furthermore evaluated if we can reproduce experimental binding affinities by a computational approach combining changes in solvation free energies with changes in protein–ligand interaction energies and entropies. In two of the seven cases, this estimation led to large errors, implying that accurate predictions of relative binding free energies based on solvent thermodynamics is challenging. Nevertheless, MD simulations can provide insight regarding which water molecules can be targeted for displacement.     

Molecular dynamics simulations of the docking of substituted N5- deazapterins to dihydrofolate reductase

Orientations of the deazapterin ring and the conformational preferences of groups appended to the deazapterin ring in a set of 8-substituted deazapterin cations docked into the dihydrofolate reductase (DHFR) binding site have been investigated using a methodology based on the simulated annealing technique within molecular dynamics (MD) simulations. Of five possible binding pockets for the 8-substituents, identified from a preliminary manual docking study, one has been definitively eliminated after an analysis of MD trajectories, while another remains uncertain. Using a new method based on standard thermodynamic cycles and a linear approximation of polar and non-polar free energy contributions from MD averages, binding affinities of the different ligands in each binding site have been correlated with experimental dissociation constants. The study has provided insights into structure-activity relationships for use in the design of modified inhibitors of DHFR.      

Application of Molecular Dynamics Simulations in the Analysis of Cyclodextrin Complexes

Cyclodextrins (CDs) are highly respected for their ability to form inclusion complexes via host–guest noncovalent interactions and, thus, ensofance other molecular properties. Various molecular modeling methods have found their applications in the analysis of those complexes. However, as showed in this review, molecular dynamics (MD) simulations could provide the information unobtainable by any other means. It is therefore not surprising that published works on MD simulations used in this field have rapidly increased since the early 2010s. This review provides an overview of the successful applications of MD simulations in the studies on CD complexes. Information that is crucial for MD simulations, such as application of force fields, the length of the simulation, or solvent treatment method, are thoroughly discussed. Therefore, this work can serve as a guide to properly set up such calculations and analyze their results.     

化学工程中的分子动力学模拟

综述了计算机分子动力学（MD）模拟的原理及其在化学工程,尤其是化工新技术研究方面的应用．文中提及的实例涉及表面及界面、复杂流体、超临界流体和膜等领域．对MD模拟今后的发展,包括其在化工研究中的作用也进行了评述．     

用分子动力学模拟研究阳离子链长对离子液体输运特性的影响

阐述了用分子动力学（molecular dynamics,MD）模拟方法研究在T=303K条件下[mmim][TFSA]、[emim][TFSA]、[bmim][TFSA]、[C6 mim] [TFSA]和[C8mim] [TFSA]5种离子液体的输运特性.模拟力场采用修正后的OPLS力场.根据模拟轨迹计算得到5种离子液体的密度值.根据均方位移（MSD）的斜率计算得到的离子液体阴阳离子自扩散系数.采用Nernst-Einstein （NE）方程计算得到离子液体摩尔导电率.这些模拟结果与实验值很吻合.离子液体的自扩散系数和电导率随着阳离子链长的增长而变小,主要原因是阳离子链长增长使离子液体中的氢键作用和范德华作用变强.计算所得离子液体摩尔导电率略大于实验测量值则归因于离子关联运动的结果.     

A Review of Computational Methods in Materials Science: Examples from Shock-Wave and Polymer Physics

This review discusses several computational methods used on different length and time scales for the simulation of material behavior. First, the importance of physical modeling and its relation to computer simulation on multiscales is discussed. Then, computational methods used on different scales are shortly reviewed, before we focus on the molecular dynamics (MD) method. Here we survey in a tutorial-like fashion some key issues including several MD optimization techniques. Thereafter, computational examples for the capabilities of numerical simulations in materials research are discussed. We focus on recent results of shock wave simulations of a solid which are based on two different modeling approaches and we discuss their respective assets and drawbacks with a view to their application on multiscales. Then, the prospects of computer simulations on the molecular length scale using coarse-grained MD methods are covered by means of examples pertaining to complex topological polymer structures including star-polymers, biomacromolecules such as polyelectrolytes and polymers with intrinsic stiffness. This review ends by highlighting new emerging interdisciplinary applications of computational methods in the field of medical engineering where the application of concepts of polymer physics and of shock waves to biological systems holds a lot of promise for improving medical applications such as extracorporeal shock wave lithotripsy or tumor treatment.     

Composition-Dependent Dielectric Properties of DMF-Water Mixtures by Molecular Dynamics Simulations

In this paper, we study the dielectric properties of water-N,N dimethylformamide (DMF) mixtures over the whole composition range using a molecular dynamics (MD) simulation. The static and microwave frequency-dependent dielectric properties of the mixtures are calculated from MD trajectories of at least 2 ns length and compared to those of available measurements. We find that the short-ranged structural correlation between neighboring water and DMF molecules strongly influences the static dielectric properties of mixtures. In terms of the dynamics, we report time correlation functions for the dipole densities of mixtures and find that their long-time behavior can be reasonably described by biexponential decays, which means the dielectric relaxations of these mixtures are governed by complex multitimescale mechanisms of rotational diffusion. The dipole density relaxation time is a non-monotonic function of composition passing through a maximum around 0.5 mole fraction DMF, in agreement with the measured main dielectric relaxation time of mixtures.     

Parameterization of classical nonpolarizable force field for hydroxide toward the large-scale molecular dynamics simulation of cellulose in pre-cooled alkali/urea aqueous solution

The empirical force fields (FFs) based on molecular dynamics (MD) simulation studying the dissolution mechanism of cellulose in cold alkali solution suffers the lacking of reliable classical FFs for hydroxide. By a simple adjustment, we transferred one available polarizable force field (FF) of hydroxide into a nonpolarizable one and combined it with GORMOS FF. Simulation based on these parameters provided accurate hydration spheres and solution structure of hydroxide that is comparable to the polarizable one, providing an opportunity for the large-scale MD simulation of the long cellulose chain in alkali/urea system for the study of dissolution and regeneration as well as mercerization process.     

Time evolution of dynamic heterogeneity in a polymeric glass: a molecular dynamics simulation study

Dynamic heterogeneity, where it is noticed in molecular dynamics (MD) simulations that, for example, conformational transition rates vary greatly from bond to bond, is characteristic of polymeric glasses. The phenomenon can be attributed to the fact that certain local bond sequences are more capable of conformational rearrangement than others. These local sequences become fixed sites when the overall chain trajectory is frozen-in in the glass. Although this is no doubt the case, because of the relatively short times of MD trajectories and the relatively small numbers of transitions it is important to establish that the heterogeneity does evolve in time in the manner expected from the local site picture and is not an artifact of short simulations or small numbers. This is undertaken here using a polyethylene system that has been much studied previously. Long trajectories are generated where the time evolution of heterogeneity can be studied. It is found that both the standard deviation and the mean value of the transitions over the bonds evolve linearly in time. This is consistent with the local fixed site picture and not with a random process involving relatively small numbers of transitions.     

Multiscale Genome Modeling for Predicting the Thermal Conductivity of Silicon Carbide Ceramics

Silicon carbide (SiC) ceramics have been widely used in industry due to its high thermal conductivity. Understanding the relations between the microstructure and the thermal conductivity of SiC ceramics is critical for improving the efficiency of heat removal in heat sink applications. In this paper, a multiscale model is proposed to predict the thermal conductivity of SiC ceramics by bridging atomistic simulations and continuum model via a materials genome model. Interatomic potentials are developed using ab initio calculations to achieve more accurate molecular dynamics (MD) simulations. Interfacial thermal conductivities with various additive compositions are predicted by nonequilibrium MD simulations. A homogenized materials genome model with the calculated interfacial thermal properties is used in a continuum model to predict the effective thermal conductivity of SiC ceramics. The effects of grain size, additive compositions, and temperature are also studied. The good agreement found between prediction results and experimental measurements validates the capabilities of the proposed multiscale genome model in understanding and improving the thermal transport characteristics of SiC ceramics.