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**Chapter 7** 

© 2012 Le, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

© 2012 Le, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Incorporating Molecular Dynamics** 

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/52642

**1. Introduction** 

Ly Le

**Simulations into Rational Drug Design:** 

**A Case Study on Influenza a Neuraminidases** 

Nowadays, information about targeted diseases needed for structure-based drug design can be accessed easily. There are more than 80,000 coordinate entries of macromolecules revealed by X-ray, NMR, and Electron Microscopy techniques available in the Brookhaven Protein Data Bank. Many new target proteins whose 3D structures have not been solved experimentally can also be easily predicted by homology modelling with adequate reliability. Similarly, thousands of compounds including their drug-like properties are provided in free chemical databases such as the NCI Diversity set, ZINC, and the Drug Bank. Therefore, it is crucial to applied suitable tools to take advantages of these promising resources for rational drug design. Molecular dynamics (MD) simulation has proven itself as a complement to lab experiments to fill in the gaps in our knowledge between 3D structures of biological targets and their potential inhibitors (Rognan et al., 1998 & Jacob et al., 2011). MD can be simply understood as a simulation of physical movements of particles like atoms in atomistic simulation or a group of atoms in coarse-grained simulation. These particles are allowed to move and interact with each others. Their motions are described by Newton's equations, in which forces between the particles and potential energy are obtained from empirical data or quantum mechanical calculations. There are quite several MD simulation packages that are free for academics such as NAMD (Phillips et al., 2005), AMBER (Case et al., 2005), GROSMOS (Christen et al., 2005) and CHARMM (Brooks et al., 1983). The method was introduced by Alder and Wainwright in the late 1950's (Alder and Wainwright, 1957) for the study of the behaviour of simple liquids and the first protein simulation, bovine pancreatic trypsin inhibitor was done successfully twenty years later (McCammon et al., 1977). After that, MD simulation has been used wildly for investigating, interpreting and discovering the dynamics of biological macromolecules, not only fast internal motions but
