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This method can be combined with a coarse grained representation of the protein molecule. Another variant of NMA is an elastic network model (ENM), in which the mechanics defined by the empirical force field is replaced by a ball and spring harmonic potential. Using those approximations enables application of aaNMA to simulations of a protein molecules consisting of a few thousand residues. The common solution overcoming this limitation is to reduce the number of degrees of freedom, which can be achieved by, fixing lengths and angles of bonds in the molecule or by calculating only rotation and translation of some residues. The all-atoms NMA (aaNMA) is computationally demanding and therefore is limited to systems containing hundreds of residues. The local deformations are represented by high frequency modes, while larger movements are represented by low frequency modes. It models protein or other molecules as a harmonic oscillating system and classifies all possible deformations around a stable equilibrium. The normal mode analysis method has been successfully used to determine and investigate the approximate protein dynamics. Two methods are particularly useful in aiding the interpretation of MD results, these are the normal mode analysis (NMA) and the principal component analysis (PCA). It also provides quantitative interpretation of the results, which can be used for comparison with other simulations or for further analysis. The correct interpretation of MD data can produce static images presenting the results of dynamic behavior of the molecule shown in the form of, for example, vectors pointing into direction of the highest displacement of the molecular fragment. In order to obtain more data from the system it is critical to perform proper analysis of the MD results.
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Those animations give researchers important information about movement of the molecule, but usually they are not enough. The results of the molecular dynamics simulation can be visualized as an animation. Those implementations offer significant time reduction for molecular dynamics calculations and also the reduction of system complexity makes it easier to avoid the risk of simulation failure. GROMACS offers implicit solvent as an alternative and exposes three generalized Born (GB) implementations: Still, Hawkins-Cramer-Truhlar (HCT), Onufriev-Bashford-Case (OBC). Those limitations were stimulus to develop other methods of handling solvent in molecular dynamics simulations. The water box, if used without the proper periodic boundary conditions, would lead to undesired border effects, which could disturb the whole simulation. The system with explicit solvent needs to be placed into the so-called water box. Although the explicit solvent is still the standard solution model in molecular dynamics simulations and GROMACS offers TIP3P, TIP4P, SPC, and their variants as a water model, the calculation using thousands of those water molecules is computationally demanding, as they interact not only with the molecule of interest, but with each other as well.
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One of such options is the reduction of the number of interacting centers through the use of an implicit solvent model. Performing molecular dynamics simulation is a relatively complicated task, therefore every option to reduce level of complexity of calculations is welcome. PyMOL exposes an API for third party plugins, we took advantage of that fact and the Dynamics PyMOL plugin was developed to facilitate molecular dynamics simulations in PyMOL GUI, using the underlying GROMACS. One of the software that allows molecular dynamics (MD) simulations is GROMACS.
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Biomolecules in the real world demonstrate dynamics behavior, so it is not enough, to only analyze the static PDB file in order to obtain full knowledge of molecular properties. They are formatted as PDB files and one of the most popular software to visualize them is PyMOL. Structures of molecules obtained from X-ray crystallography, nuclear magnetic resonance, and other methods are stored in the Protein Data Bank.