分子模拟方法及其在分子生物学中的应用

常用的分子模拟方法有 :量子力学法、分子力学方法、蒙特卡洛法和分子动力学法。四种方法各有优势 ,共同成为分子模拟的组成部分。综述了分子模拟法在分子生物学中的应用 ,最后介绍了分子模拟的发展方向 ,并预测了其未来的发展趋势。常用的分子模拟方法有 :量子力学法、分子力学方法、蒙特卡洛法和分子动力学法。四种方法各有优势 ,共同成为分子模拟的组成部分。综述了分子模拟法在分子生物学中的应用 ,最后介绍了分子模拟的发展方向 ,并预测了其未来的发展趋势。     

Mass-weighted molecular dynamics simulation and conformational analysis of polypeptide.

Atomic motions in protein molecules have been studied by molecular dynamics (MD) simulations; dynamics simulation methods have also been employed in conformational studies of polypeptide molecules. It was found that when atomic masses are weighted, the molecular dynamics method can significantly increase the sampling of dihedral conformation space in such studies, compared to a conventional MD simulation of the same total simulation time length. Herein the theoretical study of molecular conformation sampling by the molecular dynamics-based simulation method in which atomic masses are weighted is reported in detail; moreover, a numerical scheme for analyzing the extensive conformational sampling in the simulation of a tetrapeptide amide molecule is presented. From numerical analyses of the mass-weighted molecular dynamics trajectories of backbone dihedral angles, low-resolution structures covering the entire backbone dihedral conformation space of the molecule were determined, and the distribution of rotationally stable conformations in this space were analyzed quantitatively. The theoretical analyses based on the computer simulation and numerical analytical methods suggest that distinctive regimes in the conformational space of the peptide molecule can be identified.     

Grand canonical ensemble Monte Carlo simulation of the dCpG/proflavine crystal hydrate.

The grand canonical ensemble Monte Carlo molecular simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical ensemble simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed molecular simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand ensemble simulations can be far more advantageous than the comparable canonical ensemble simulations.     

Gibbs-Ensemble Molecular Dynamics: A New Method for Simulations Involving Particle Exchange

We discuss a novel simulation method suitable for simulating phenomena involving particle exchange. The method is a molecular dynamics version of the Gibbs-Ensemble Monte Carlo technique, which has been developed some years ago for the direct simulation of phase equilibria in fluid systems. The idea is to have two separate simulation boxes, which can exchange particles or molecules in a thermodynamically consistent fashion. We discuss the general idea of the Gibbs-Ensemble Molecular Dynamics technique and present examples for different simple atomic and molecular fluids. Specifically we will discuss Gibbs-Ensemble Molecular Dynamics simulations of gas-liquid and liquid-solid equilibria in Lennard-Jones systems and in hexane as well as an application of the method to adsorption.     

A steered molecular dynamics method with direction optimization and its applications on ligand molecule dissociation

In this paper, a steered molecular dynamics method with pulling direction optimization is proposed to dissociate ligand molecule from receptor. A multi-population genetic algorithm based on the information entropy is developed to search the optimal pulling direction. By imposing an optimization phase in the conventional steered molecular dynamics simulation, a better substrate-exit channel for the buried active site can be found. The novel simulation method has been used to dissociate the substrate-bound complex structure of cytochrome P450 3A4-metyrapone. The results show that the new pathway obtained by the proposed method has advantages such as lower energy barrier, less dissociation time and shorter motion trajectory than that by the conventional steered molecular dynamics.     

Visualization of energetics and conformations from molecular computer simulations

The quantity of data generated from molecular dynamics simulations and energy minimizations of macromolecules is overwhelming. It is an arduous task to extract the relevant and interesting information from the numerous coordinate sets produced. To help solve this problem, the authors have developed a method to aid the visualization of the relevant information from the simulations. This approach combines animation of the results on a high performance graphics device, such as the PS300, with colour-coded atoms based on changes in energy or conformation. The method will be illustrated using as examples: the molecular mechanics minimization of a nonapeptide, the molecular dynamics simulation of the protein myoglobin, including the analysis of the motion of helices during a 300ps trajectory, and changes in sugar puckering that occur during the molecular dynamics simulation of a DNA oligomer. The method is also applicable for analysing energy components and conformational properties of a fixed conformation.     

Hybrid simulation of cellular behavior

MOTIVATION: To be valuable to biological or biomedical research, in silico methods must be scaled to complex pathways and large numbers of interacting molecular species. The correct method for performing such simulations, discrete event simulation by Monte Carlo generation, is computationally costly for large complex systems. Approximation of molecular behavior by continuous models fails to capture stochastic behavior that is essential to many biological phenomena. RESULTS: We present a novel approach to building hybrid simulations in which some processes are simulated discretely, while other processes are handled in a continuous simulation by differential equations. This approach preserves the stochastic behavior of cellular pathways, yet enables scaling to large populations of molecules. We present an algorithm for synchronizing data in a hybrid simulation and discuss the trade-offs in such simulation. We have implemented the hybrid simulation algorithm and have validated it by simulating the statistical behavior of the well-known lambda phage switch. Hybrid simulation provides a new method for exploring the sources and nature of stochastic behavior in cells.     

Reliable prediction of adsorption isotherms via genetic algorithm molecular simulation

Conventional molecular simulation techniques such as grand canonical Monte Carlo (GCMC) strictly rely on purely random search inside the simulation box for predicting the adsorption isotherms. This blind search is usually extremely time demanding for providing a faithful approximation of the real isotherm and in some cases may lead to non-optimal solutions. A novel approach is presented in this article which does not use any of the classical steps of the standard GCMC method, such as displacement, insertation, and removal. The new approach is based on the well-known genetic algorithm to find the optimal configuration for adsorption of any adsorbate on a structured adsorbent under prevailing pressure and temperature. The proposed approach considers the molecular simulation problem as a global optimization challenge. A detailed flow chart of our so-called genetic algorithm molecular simulation (GAMS) method is presented, which is entirely different from traditions molecular simulation approaches. Three real case studies (for adsorption of CO₂ and H₂ over various zeolites) are borrowed from literature to clearly illustrate the superior performances of the proposed method over the standard GCMC technique. For the present method, the average absolute values of percentage errors are around 11% (RHO-H₂), 5% (CHA-CO₂), and 16% (BEA-CO₂), while they were about 70%, 15%, and 40% for the standard GCMC technique, respectively.     

Simulation-based fitting of protein-protein interaction potentials to SAXS experiments

We present a new method for computing interaction potentials of solvated proteins directly from small-angle x-ray scattering data. An ensemble of proteins is modeled by Monte Carlo or molecular dynamics simulation. The global x-ray scattering of the whole model ensemble is then computed at each snapshot of the simulation, and averaged to obtain the x-ray scattering intensity. Finally, the interaction potential parameters are adjusted by an optimization algorithm, and the procedure is iterated until the best agreement between simulation and experiment is obtained. This new approach obviates the need for approximations that must be made in simplified analytical models. We apply the method to lambda repressor fragment 6-85 and fyn-SH3. With the increased availability of fast computer clusters, Monte Carlo and molecular dynamics analysis using residue-level or even atomistic potentials may soon become feasible.     

Fast and reliable analysis of molecular motion using proximity relations and dimensionality reduction

The analysis of molecular motion starting from extensive sampling of molecular configurations remains an important and challenging task in computational biology. Existing methods require a significant amount of time to extract the most relevant motion information from such data sets. In this work, we provide a practical tool for molecular motion analysis. The proposed method builds upon the recent ScIMAP (Scalable Isomap) method, which, by using proximity relations and dimensionality reduction, has been shown to reliably extract from simulation data a few parameters that capture the main, linear and/or nonlinear, modes of motion of a molecular system. The results we present in the context of protein folding reveal that the proposed method characterizes the folding process essentially as well as ScIMAP. At the same time, by projecting the simulation data and computing proximity relations in a low-dimensional Euclidean space, it renders such analysis computationally practical. In many instances, the proposed method reduces the computational cost from several CPU months to just a few CPU hours, making it possible to analyze extensive simulation data in a matter of a few hours using only a single processor. These results establish the proposed method as a reliable and practical tool for analyzing motions of considerably large molecular systems and proteins with complex folding mechanisms.     

Viscosity of heptane-toluene mixtures. Comparison of molecular dynamics and group contribution methods

Three methods of molecular dynamics simulation [Green–Kubo (G–K), non-equilibrium molecular dynamics (NEMD) and reversed non-equilibrium molecular dynamics (RNEMD)], and two group contribution methods [UNIFAC–VISCO and Grunberg–Nissan (G–N)] were used to calculate the viscosity of mixtures of n-heptane and toluene (known as heptol). The results obtained for the viscosity and density of heptol were compared with reported experimental data, and the advantages and disadvantages of each method are discussed. Overall, the five methods showed good agreement between calculated and experimental viscosities. In all cases, the deviation was lower than 9%. It was found that, as the concentration of toluene increases, the deviation of the density of the mixture (as calculated with molecular dynamics methods) also increases, which directly affects the viscosity result obtained. Among the molecular simulation techniques evaluated here, G–K produced the best results, and represents the optimal balance between quality of result and time required for simulation. The NEMD method produced acceptable results for the viscosity of the system but required more simulation time as well as the determination of an appropriate shear rate. The RNEMD method was fast and eliminated the need to determine a set of values for shear rate, but introduced large fluctuations in measurements of shear rate and viscosity. The two group contribution methods were accurate and fast when used to calculate viscosity, but require knowledge of the viscosity of the pure compounds, which is a serious limitation for applications in complex multicomponent systems.     

Virtual rigid body dynamics

An important direction in biological simulations is the development of methods that permit the study of larger systems and/or longer simulation time scales than is currently feasible by molecular dynamics. One such method designed with this objective in mind is stochastic boundary molecular dynamics (SBMD). SBMD was developed for the characterization of spatially localized processes in proteins, and has been shown to successfully reproduce structural and dynamical properties of these macromolecules, as compared to a molecular dynamics control simulation, when concerted or global motions are not present. The virtual rigid body dynamics method presented in this work extends the range of applicability of the SBMD method, by providing a framework to include these important long time scale conformational transitions. In this paper we describe the two-step implementation of the virtual rigid body model: first, the reduction of the full atomic representation to a reduced particle (virtual bond) model, and second, the propagation of the dynamics of flexibly connected rigid bodies containing virtual atom sites.     

The Application of the Reaction-Field Method to the Calculation of Dielectric Constants

Abstract

The behaviour of the popular TIP3P water model has been investigated using both molecular dynamics and Monte Carlo simulation procedures. Long-range electrostatic interactions were included through a reaction-field treatment, and the nonbonded interactions were either truncated at the cutoff distance, or smoothly scaled to zero using a switching function. The thermodynamic observables, and in particular the dipole-dipole correlation functions, are found to differ between the two simulation techniques if a rigid nonbonded cutoff is applied. However, use of a switching function gives exact agreement between the simulation methodologies. This difference is ascribed to the effect of energy pumping in the molecular dynamics simulations, and suggests that dielectric constants calculated using this simulation method with the fluctuation procedure in conjunction with a reaction field should be reappraised. Thus the Monte Carlo simulation procedure offers a number of intrinsic advantages over molecular dynamics for the calculation of dielectric constants with a reaction field. The most precise value for the dielectric constant of TIP3P is calculated to be 102 ± 3 at 298 K.     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

Adaptive torsion-angle quasi-statics: a general simulation method with applications to protein structure analysis and design

MOTIVATION: The cost of molecular quasi-statics or dynamics simulations increases with the size of the simulated systems, which is a problem when studying biological phenomena that involve large molecules over long time scales. To address this problem, one has often to either increase the processing power (which might be expensive), or make arbitrary simplifications to the system (which might bias the study). RESULTS: We introduce adaptive torsion-angle quasi-statics, a general simulation method able to rigorously and automatically predict the most mobile regions in a simulated system, under user-defined precision or time constraints. By predicting and simulating only these most important regions, the adaptive method provides the user with complete control on the balance between precision and computational cost, without requiring him or her to perform a priori, arbitrary simplifications. We build on our previous research on adaptive articulated-body simulation and show how, by taking advantage of the partial rigidification of a molecule, we are able to propose novel data structures and algorithms for adaptive update of molecular forces and energies. This results in a globally adaptive molecular quasi-statics simulation method. We demonstrate our approach on several examples and show how adaptive quasi-statics allows a user to interactively design, modify and study potentially complex protein structures.     

Sedimentation of generalized systems of interacting particles. III. Concentration-dependent sedimentation and extension to other transport methods

The simulation method presented in the previous papers is related to the concentration-dependent sedimentation–diffusion. It can be shown that the efficiency of the program described previously is maintained. A simulation of a system exhibiting the Johnston–Ogston effect is presented. Through the similarity of their continuity equations with the Lamm equation, electrophoresis, molecular sieve, and chromatography are treated. A general simulation of transport for systems of many interacting components is thus presented, which is able to take into account kinetically controlled chemical reactions and nonideal phenomena.     

The use of Balasubramanian plots in the analysis of protein dynamics data

A method for viewing the changes In protein mainchain dihedral angles is described. This facility is used in the analysis of prolein molecular dynamics simulations. Each conformation resulting from the dynamics simulation has a Balasubramanian plot calculated. These 2D schematic plots are then viewed on the Winchester Graphics System. using the animation facility. This results in a ‘movie’ of the simulation being displayed.     

Multiscale modeling of lipids and lipid bilayers

A multiscale modeling approach is applied for simulations of lipids and lipid assemblies on mesoscale. First, molecular dynamics simulation of initially disordered system of lipid molecules in water within all-atomic model was carried out. On the next stage, structural data obtained from the molecular dynamics (MD) simulation were used to build a coarse-grained (ten sites) lipid model, with effective interaction potentials computed by the inverse Monte Carlo method. Finally, several simulations of the coarse-grained model on longer length- and time-scale were performed, both within Monte Carlo and molecular dynamics simulations: a periodical sample of lipid molecules ordered in bilayer, a free sheet of such bilayer without periodic boundary conditions, formation of vesicle from a plain membrane, process of self-assembly of lipids randomly dispersed in volume. It was shown that the coarse-grained model, developed exclusively from all-atomic simulation data, reproduces well all the basic features of lipids in water solution.