**Acknowledgement**

180 Bioinformatics

discovery.

Ly Le

**Author details** 

of end-point interactions, including hydrogen bonds, hydrophobic packing and solvent infiltration, of oseltamivir resistance have been thoroughly studied, little is known about the kinetics of the drug binding in mutants at atomic level. The idea that drug resistant mutants actually disrupt entry of oseltamivir into the SA active site of neuraminidase through disruption of an electrostatic binding funnel is in part supported by experiments which have noted reduced drug binding kinetics in H5N1 H274Y and N294S mutants. Even though the oseltamivir-resistant mutations were seen located in or adjacent to the funnel, clearly additional study is still needed for a full understanding of how the H274Y and N294S mutations weaken the binding of the drug. Furthermore, the mutations might not only affect the electrostatic gradient but also the geometry of the drug binding and unbinding path. Future or followup studies should therefore focus on the specific drug entry/exit pathways for oseltamivir-resistant mutant systems, sampling timescales great enough (such as in the

We have presented three important applications of MD simulation in drug design against influenza A virus. While MD simulation has been proven as a powerful tool complement to experiment in drug discovery processes, the problems in accuracy of drug parameter and limitation in time scale of MD simulation definitely affect applications of this tool. The challenge in drug force field development is that, unlike uniformed amino acids or nucleotides, each drug has its own structure and requires separate parameter. Since force field for general macromolecules have been well developed, attention should be shifted to development of adequately accurate drug force field (Wang et al., 2004; Zoete et al., 2012). Another challenge in MD simulation is limitation of time scale. Several important phenomena which are important for drug design application happen in the time scales that can't be done by even the biggest supercomputers in the world. Over the past decade several methods were developed to speed up classical MD simulation including SMD, accelerated MD (Hamelberg et al., 2009), coarse-grained MD simulation (Izvekov et al., 2005). Last but not least, the implementations of specialized hardware including CBE, GPU, and FPGA architectures are important to broaden application of MD simulation to modern drug discovery (Horacio et al., 2012). The recent finding of oseltamivir binding pathway using GPU acceleration and SMD (Le et al., 2010) is an example that the combined improvement of theoretical algorithm and specialized hardware architecture has enabled us to increase the success rate and decrease the cost in rational drug

*School of Biotechnology, Ho Chi Minh International University, Life Science Laboratory, Institute for Computational Science and Technology at Ho Chi Minh City , Vietnam* 

case of simFEQ5 described above) to capture both the binding.

**5. Challenges and opportunities** 

The author wish to thank the Institute for Computational Science and Technology at Ho Chi Minh City and NAFOSTED (The National Foundation for Science and Technology Development) for partially support the research presented in this chapter.
