Molecular dynamics simulations:bring biomolecular structures alive on a computer

The molecular dynamics (MD) simulations play a very important role in science today. They have been used successfully in binding free-energy calculations and rational design of drugs and vaccines. MD simulations can help visualize and understand structures and dynamics at an atomistic level when combined with molecular graphics programs. The molecular and atomistic properties can be displayed on a computer in a time-dependent way, which opens a road toward a better understanding of the relationship of structure, dynamics, and function. In this chapter, the basics of MD are explained, together with a step-by-step description of setup and running an MD simulation.

Molecular dynamics simulations of the adsorption and diffusion behavior of pure and mixed alkanes in silicalite

The adsorption and diffusion of mixed hydrocarbon components in silicalite have been studied using molecular dynamic simulation methods. We have investigated the effect of molecular loadings and temperature on the diffusional behavior of both pure and mixed alkane components. For binary mixtures with components of similar sizes, molecular diffusional behavior in the channels was noticed to be reversed as loading is increased. This behavior was noticeably absent for components of different sizes in the mixture. Methane molecules in the methane/propane mixture have the highest diffusion coefficients across the entire loading range. Binary mixtures containing ethane molecules prove more difficult to separate compared to other binary components. In the ternary mixture, however, ethane molecules diffuse much faster at 400 K in the channel with a tendency to separate out quickly from other components. © 2005 Elsevier Inc. All rights reserved.

Monte Carlo and molecular dynamics simulations of methane in potassium montmorillonite clay hydrates at elevated pressures and temperatures

The structure and dynamics of methane in hydrated potassium montmorillonite clay have been studied under conditions encountered in sedimentary basin and compared to those of hydrated sodium montmorillonite clay using computer simulation techniques. The simulated systems contain two molecular layers of water and followed gradients of 150 barkm-1 and 30 Kkm-1 up to a maximum burial depth of 6 km. Methane particle is coordinated to about 19 oxygen atoms, with 6 of these coming from the clay surface oxygen. Potassium ions tend to move away from the center towards the clay surface, in contrast to the behavior observed with the hydrated sodium form. The clay surface affinity for methane was found to be higher in the hydrated K-form. Methane diffusion in the two-layer hydrated K-montmorillonite increases from 0.39×10-9 m2s-1 at 280 K to 3.27×10-9 m2s-1 at 460 K compared to 0.36×10-9 m2s-1 at 280 K to 4.26×10-9 m2s-1 at 460 K in Na-montmorillonite hydrate. The distributions of the potassium ions were found to vary in the hydrates when compared to those of sodium form. Water molecules were also found to be very mobile in the potassium clay hydrates compared to sodium clay hydrates. © 2004 Elsevier Inc. All All rights reserved.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

Characterization of the structure of RAMP1 by mutagenesis and molecular modeling

Receptor activity modifying proteins (RAMPs) are a family of single-pass transmembrane proteins that dimerize with G-protein-coupled receptors. They may alter the ligand recognition properties of the receptors (particularly for the calcitonin receptor-like receptor, CLR). Very little structural information is available about RAMPs. Here, an ab initio model has been generated for the extracellular domain of RAMP1. The disulfide bond arrangement (Cys 27-Cys82, Cys40-Cys72, and Cys 57-Cys104) was determined by site-directed mutagenesis. The secondary structure (a-helices from residues 29-51, 60-80, and 87-100) was established from a consensus of predictive routines. Using these constraints, an assemblage of 25,000 structures was constructed and these were ranked using an all-atom statistical potential. The best 1000 conformations were energy minimized. The lowest scoring model was refined by molecular dynamics simulation. To validate our strategy, the same methods were applied to three proteins of known structure; PDB:1HP8, PDB:1V54 chain H (residues 21-85), and PDB:1T0P. When compared to the crystal structures, the models had root mean-square deviations of 3.8 Å, 4.1 Å, and 4.0 Å, respectively. The model of RAMP1 suggested that Phe93, Tyr 100, and Phe101 form a binding interface for CLR, whereas Trp74 and Phe92 may interact with ligands that bind to the CLR/RAMP1 heterodimer. © 2006 by the Biophysical Society.

Complex temporal patterns in molecular dynamics:a direct measure of the phase-space exploration by the trajectory at macroscopic time scales

Computer simulated trajectories of bulk water molecules form complex spatiotemporal structures at the picosecond time scale. This intrinsic complexity, which underlies the formation of molecular structures at longer time scales, has been quantified using a measure of statistical complexity. The method estimates the information contained in the molecular trajectory by detecting and quantifying temporal patterns present in the simulated data (velocity time series). Two types of temporal patterns are found. The first, defined by the short-time correlations corresponding to the velocity autocorrelation decay times (â‰0.1â€ps), remains asymptotically stable for time intervals longer than several tens of nanoseconds. The second is caused by previously unknown longer-time correlations (found at longer than the nanoseconds time scales) leading to a value of statistical complexity that slowly increases with time. A direct measure based on the notion of statistical complexity that describes how the trajectory explores the phase space and independent from the particular molecular signal used as the observed time series is introduced. © 2008 The American Physical Society.

Computational mechanics reveals nanosecond time correlations in molecular dynamics of liquid systems

Statistical complexity, a measure introduced in computational mechanics has been applied to MD simulated liquid water and other molecular systems. It has been found that statistical complexity does not converge in these systems but grows logarithmically without a limit. The coefficient of the growth has been introduced as a new molecular parameter which is invariant for a given liquid system. Using this new parameter extremely long time correlations in the system undetectable by traditional methods are elucidated. The existence of hundreds of picosecond and even nanosecond long correlations in bulk water has been demonstrated. © 2008 Elsevier B.V. All rights reserved.

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

Toward the atomistic simulation of T cell epitopes automated construction of MHC:peptide structures for free energy calculations

Epitopes mediated by T cells lie at the heart of the adaptive immune response and form the essential nucleus of anti-tumour peptide or epitope-based vaccines. Antigenic T cell epitopes are mediated by major histocompatibility complex (MHC) molecules, which present them to T cell receptors. Calculating the affinity between a given MHC molecule and an antigenic peptide using experimental approaches is both difficult and time consuming, thus various computational methods have been developed for this purpose. A server has been developed to allow a structural approach to the problem by generating specific MHC:peptide complex structures and providing configuration files to run molecular modelling simulations upon them. A system has been produced which allows the automated construction of MHC:peptide structure files and the corresponding configuration files required to execute a molecular dynamics simulation using NAMD. The system has been made available through a web-based front end and stand-alone scripts. Previous attempts at structural prediction of MHC:peptide affinity have been limited due to the paucity of structures and the computational expense in running large scale molecular dynamics simulations. The MHCsim server (http://igrid-ext.cryst.bbk.ac.uk/MHCsim) allows the user to rapidly generate any desired MHC:peptide complex and will facilitate molecular modelling simulation of MHC complexes on an unprecedented scale.

Water-peptide dynamics during conformational transitions

Transitions between metastable conformations of a dipeptide are investigated using classical molecular dynamics simulation with explicit water molecules. The distribution of the surrounding water at different moments before the transitions and the dynamical correlations of water with the peptide's configurational motions indicate that the water molecules represent an integral part of the molecular system during the conformational changes, in contrast to the metastable periods when water and peptide dynamics are essentially decoupled.

Molecular dynamics study of solvent transport in nanoscale osmosis

An ideal of osmotic equilibrium between an ideal solution and pure solvent separated by a semi-permeable membrane is studied numerically using the method of molecular dynamics. The osmotic flow is observed as the inflow of the solvent across the membrane from the dilute to the concentrated side. The validity of van't Hoff's law for osmotic pressure is confirmed over a wide range of concentrations. It is found that the law is established by a balance between non-uniform partial pressures of solute and solvent. Furthermore, the present model permits an understanding of the mechanism of the osmotic flow in the relaxation process as the liquids evolve from the initial state to the equilibrium state. We focus in particular on the interaction between solute and solvent. ©2008 The Physical Society of Japan.

Stress-induced platelet formation in silicon:a molecular dynamics study

The effect of stress on vacancy cluster configurations in silicon is examined using molecular dynamics. At zero pressure, the shape and stability of the vacancy clusters agrees with previous atomistic results. When stress is applied the orientation of small planar clusters changes to reduce the strain energy. The preferred orientation for the vacancy clusters under stress agrees with the experimentally observed orientations of hydrogen platelets in the high stress regions of hydrogen implanted silicon. These results suggest a theory for hydrogen platelet formation. © 2005 The American Physical Society.

Water network dynamics at the critical moment of a peptide's ß-turn formation:a molecular dynamics study

All-atom molecular dynamics simulations for a single molecule of Leu-Enkephalin in aqueous solution have been used to study the role of the water network during the formation of ß-turns. We give a detailed account of the intramolecular hydrogen bonding, the water-peptide hydrogen bonding, and the orientation and residence times of water molecules focusing on the short critical periods of transition to the stable ß-turns. These studies suggest that, when intramolecular hydrogen bonding between the first and fourth residue of the ß-turn is not present, the disruption of the water network and the establishment of water bridges constitute decisive factors in the formation and stability of the ß-turn. Finally, we provide possible explanations and mechanisms for the formations of different kinds of ß-turns.

Bridging large and small scales of water models using hybrid Molecular Dynamics/Fluctuating Hydrodynamics framework

This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.

Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide:can the α3 and β2m domains be neglected?

Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histo-compatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVY-DGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide–MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the α1–α2 domain, the α3 and β2m domains cannot be neglected. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1803–1813, 2004