Molecular Dynamics is a computer simulation approach permitting the time evolution prediction of an interacting particular system which involves the generation of atomic trajectories of a system using numerical integration of Newton’s laws of motion to define specific interatomic potential using the initial condition and boundary condition. It is one of the principle approaches for the study of biological molecules computationally for calculating the time dependent behaviour of a molecular system. It provides detailed information about the fluctuations and conformational changes in proteins and nucleic acids.
Owing to the rapid development of faster computer architectures and better algorithms for high-level computations in a time-affordable manner, the impact of computational drug design for novel drug discovery has been intensified. Traditional molecular dynamics (MD) simulations allow the implementation of structure based drug designing (SBDD) strategies that fully account for structural flexibility of the overall model system of drug–target complex.
Traditional MD is a physical method for studying the interaction and motion of atoms and molecules based on Newton's laws of motion. Early studies by Karplus & McCammon and by Warshel & Levitt showed the crucial role of classical MD simulations in studying biological systems by using MD simulations to attain various protein conformations and nucleic acids conformations, including the initial attempts to simulate spontaneously complex phenomena of biological systems, such as understanding how proteins fold.
MD simulation analysis is one of the essential steps while designing novel drugs using computational approaches. MD analysis not just evaluates and validates the protein structures, either predicted computationally or experimentally, but also validates the drug-target compatibility by providing various statistical information about the interacting drug-target complex. The basic MD simulation algorithm is presented in the following flow diagram:
Applications of MD Simulations
In structural bioinformatics, structure prediction of biological molecules has been one of the most ancient problems addressed. Molecular dynamics along with the longest simulations performed, has been substantially used for ab initio protein structure prediction, directing to simulate protein folding from scratch, which is not the preferred strategy to attain a theoretical model of protein structure.
Template-based modeling (homology modeling) is the most efficient technique, which involves one or several 3D structures of proteins displaying a justified degree of similarity to the protein of interest are taken as templates. Irrespective of the modeling algorithm used, the end result is a model bearing the new amino acid sequence and a structure conforming to the used templates. Generally, the last step of the structure prediction process suggests the qualification of the structure using normally molecular mechanics. The use of molecular dynamics simulations looks like an obvious step in refining such structural models.
Simulation provides a more realistic model theoretically, and allows the structure to adapt to the new sequence. MD simulations require systems to be close to their native (equilibrium) conformation, otherwise, insignificant and difficult to detect artifacts may occur. Applying various MD approaches to the refinement of such predicted protein models has led to a number of conclusions.
MD simulation approaches are being utilized for the investigation of structures, dynamics, and thermodynamics of biological molecules (proteins, DNA/RNA) and their complexes. They are also being utilized for the determination of structures of biomolecules from x-ray crystallography and NMR experiments.
Tools used for MD Simulations
There is a huge number of web-based and stand alone tools available for MD simulations. Following are some most commonly utilized tools for MD simulations of biological systems, their specifications system requirements:
Abalone - is a commercial GPU based, general purpose molecular modeling program, that focuses on the dynamics of biopolymers. Primarily works on Windows OS yet its other alternatives can also be used for Linux and Mac OS.
ACEMD - is the next generation molecular GPU based dynamic simulation web-engine. It is designed to accelerate the drug discovery process by providing all necessary capabilities for biomolecular simulations. Works on all types of operating systems.
AMBER - is a both GPU and CPU based suite of biomolecular simulation programs. AMBER stands for Assisted Model Building with Energy Refinement,which is a molecular dynamics and energy minimization program.
CHARMM - is a versatile GPU/CPU based molecular modeling and simulation program designed to provide broad application to the simulation of many-particle systems, and includes a comprehensive set of force fields to simulate biomolecules. This tool can be run on a variety of UNIX-compatible platforms, with optional graphical output.
GROMACS - is an open source GPU/CPU based web program. It is a complete modelling package for proteins, membrane systems and more, including fast molecular dynamics, normal mode analysis, essential dynamics analysis and many trajectory analysis utilities. Can be run on any type of operating system.
MD Simulation Analysis
Once the MD simulations have been predicted for the target protein-ligand complex, the next step is to analyze the results. Different tools provide different sorts of information and results but the main purpose for performing MD simulations is to calculate RMSD, RMSF, and PCA calculations, H-bonds analysis, delG values calculations for the construction of contact matrix to analyze the molecular interactions between the biological target and drug candidate.
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