Molecular dynamics trajectory analysis

Dauber-Osguthorpe P and D J Osguthorpe 1990. Analysis of Intramolecular Motions by Filterin Molecular Dynamics Trajectories. Journal of the American Chemical Society 112 7921-7935. 

An important issue, the significance of which is sometime underestimated, is the analysis of the resulting molecular dynamics trajectories. Clearly, the value of any computer simulation lies in the quality of the information extracted from it. In fact, it is good practice to plan the analysis procedure before starting the simulation, as the goals of the analysis will often detennine the character of the simulation to be performed. 

One of the main attractions of normal mode analysis is that the results are easily visualized. One can sort the modes in tenns of their contributions to the total MSF and concentrate on only those with the largest contributions. Each individual mode can be visualized as a collective motion that is certainly easier to interpret than the welter of information generated by a molecular dynamics trajectory. Figure 4 shows the first two normal modes of human lysozyme analyzed for their dynamic domains and hinge axes, showing how clean the results can sometimes be. However, recent analytical tools for molecular dynamics trajectories, such as the principal component analysis or essential dynamics method [25,62-64], promise also to provide equally clean, and perhaps more realistic, visualizations. That said, molecular dynamics is also limited in that many of the functional motions in biological molecules occur in time scales well beyond what is currently possible to simulate. 

A theoretical analysis of the possible conformations of polylp-phenylene terephthalate) (PPTA) and polylp-phenylene isophthalate) (PPIA) is performed on the basis of molecular mechanics and molecular dynamics trajectories. The dependence of the persistence length on the fluctuations of the torsional angle around the ester bond is discussed for PPTA in the frame of the RIS model. Realistic parameters like bond length and bond angles are provided by computer simulations using MD. 

Dauber-Osguthorpe, P., and Osguthorpe, D. J. (1990) Analysis of intramolcular motions by filtering molecular dynamics trajectories, 7. Am. Chem. Soc. 112, 7921-7935. 

In addition to providing a microscopic tool for observing the outcomes of physicochemical processes in extraordinary detail, molecular dynamics simulations can, in principle, provide a valuable technique for obtaining thermodynamic variables and rate constants via integration over selected portions of the molecular dynamics trajectory. Several techniques have heen recently employed that allow this kind of analysis, even with the present hmitations regarding length and timescales, such as time-accelerated molecular dynamics [228, 229]. 

In order to obtain more detailed information on the DNA-Actn complexation, molecular dynamics simulation was carried out. Analysis of the molecular dynamics trajectories allows one to describe in detail the stmctures of the investigated complexes (Fig. 2.4). 

Roe DR, Cheatham TE (2013) PTRAJ and CPPTRAJ software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput 9(7) 3084-3095. doi 10.1021/ ct400341p... 

In numerous cases an atomically detailed picture is required to understand function of biological molecules. The wealth of atomic information that is provided by the Molecular Dynamics (MD) method is the prime reason for its popularity and numerous successes. The MD method offers (a) qualitative understanding of atomic processes by detailed analysis of individual trajectories, and (b) comparison of computations to experimental data by averaging over a representative set of sampled trajectories. 

MacroModel (we tested Version 6.5) is a powerful molecular mechanics program. The program can be run from either its graphic interface or an ASCII command file. The command file structure allows very complex simulations to be performed. The XCluster utility permits the analysis and filtering of a large number of structures, such as Monte Carlo or dynamics trajectories. The documentation is very thorough. 

Rather than solve a Schrodinger equation with the Nuclear Hamiltonian (above), a common approximation is to assume that atoms are heavy enough so that classical mechanics is a good enough approximation. Motion of the particles on the potential surface, according to the laws of classical mechanics, is then the subject of classical trajectory analysis or molecular dynamics. These come about by replacing Equation (7) on page 164 with its classical equivalent ... 

In a different context, conformational analysis is essential for the analysis of molecular dynamics simulations. As discussed in Chapter 3, the direct output of a molecular dynamics simulation is a set of confonnations ( snapshots ) that were saved along the trajectory. These conformations are subsequently analyzed in order to extract information about the system. However, if, during a long simulation, the molecule moves from one... 

VMD is designed for the visualization and analysis of biological systems such as proteins, nucleic acids, and lipid bilayer assemblies. It may be used to view more general molecules, as VMD can read several different structural file formats and display the contained structure. VMD provides a wide variety of methods for rendering and coloring a molecule. VMD can be used to animate and analyze the trajectory of a molecular dynamics (MD) simulation. 

In the MD/QM technique each tool is used separately, in an attempt to exploit their particular strengths. Classical molecular dynamics as a very fast sampling technique is first used for efficient sampling of the conformational space for the molecule of interest. A cluster analysis of the MD trajectory is then used to identify the main con-formers (clusters). Finally QM calculations, which provide a more accurate (albeit more computationally expensive) representation of the system, can be applied to just a small number of snapshots carefully extracted from each representative cluster from the MD-generated trajectory. 

Reaction rates are macroscopic averages of the number of microscopical molecules that pass from the reactant to the product valley in the potential hypersurface. An estimation of this rate can be obtained from the energy of the highest point in the reaction path, the transition state. This approach will however fail when the reaction proceeds without an enthalpic barrier or when there are many low frequency modes. The study of these cases will require the analysis of the trajectory of the molecule on the potential hypersurface. This idea constitutes the basis of molecular dynamics (MD) [96]. Molecular dynamics were traditionally too computationally demanding for transition metal complexes, but things seem now to be changing with the use of the Car-Parrinello (CP) method [97]. This approach has in fact been already succesfully applied to the study of the catalyzed polymerization of olefins [98]. 

---