**2. Ensemble-based docking**

#### **2.1. Receptor**

#### *2.1.1. MD simulation of ionized oseltamivir-neuraminidase complex*

The molecular model of H1N1pdm used in MD simulation was built from the crystal structure of avian H5N1 and the amino acid sequence of swine flu H1N1pdm from GenBank Locus ID CY041156. All simulations were performed using NAMD 2.720 and the CHARMM31 force field with the CMAP correction. The ionized systems were minimized for 10,000 integration steps and equilibrated for 20 ns with a 1 fs time step. Following this, a 20 ns unconstrained equilibration production run was performed for subsequent trajectory analysis, with frames stored after each picosecond (every 1000 time steps). Constant temperature (T = 300 K) was enforced using Langevin dynamics with a damping coefficient of 1 ps−1. Constant pressure (p = 1 atm) was enforced using the Nosé-Hoover Langevin piston method. Van der Waals interaction cut-off distances were set at 12 Å (smooth switching function beginning at 10 Å) and long-range electrostatic forces were computed using the particle-mesh Ewald (PME) summation method. The trajectories from our 20ns production run of EQ simulation of H1N1pdm neuraminidase with oseltamivir bound, were clustered as shown in Figure 1, and then used for ensemble based docking.

160 Bioinformatics

also slow conformational changes and even whole folding processes of some small proteins. MD simulation has become important complement to experimental procedures in structurefunction determination of targeted diseases and rational design of their inhibitors. In the lead discovery stage, thousands of compounds from free chemical databases are docked against the rigid structures of receptors. Such screening processes are fast but are associated with a high number of false positives and false negatives. Flexible docking has improved the outcome of this process, but to a very limited degree. A recent method that significantly increases the accuracy of the lead identification process is called ensemble-based docking. This method combines the docking algorithm (Morris et al., 1998) with the dynamic structure of proteins taken from MD simulations as well as statistical analysis of binding energy (Amaro et al., 2008). Another important aspect of rational drug design is to understand all drug-protein interactions at an atomistic level and how these interactions are ruptured by certain mutations, leading to drug resistance. Thorough understanding of drug resistant mechanisms is crucial for the design of new agents effective against current drug-resistant strains. MD simulation is also an important tool in identifying drug binding pathway. However, this could be one of the most challenging tasks in computer-aided drug design due to the limitation of MD simulation time scale. One of the solutions is to combine electrostatic surface potential analysis with steered MD (SMD) simulation (Isralewitz et al., 2001). Forces can be applied to drug molecules in order to pull it along possible pathways predicted from electrostatic surface potential. The findings of drug binding pathway are highly important for investigation on non-active site mutations which possibly prevent drugs from entering binding site by rupture the structure of binding pathway as well as for the rational design of new drugs with good binding kinetics.

In this chapter we highlight the successes in using MD simulations to speed up the rational design of antiviral drugs. Due to their ability to mutate quickly, the viruses can easily survive people's immune systems and resist current drugs. Currently, there are two pathogenic viruses, the 2003 avian flu (H5N1) virus( Ford Stephen et al., 2006) and the 2009 swine flu (H1N1pdm) virus (Butler et al., 2009), which share the same subtype 1 (N1) of neuraminidase. Neuraminidase, a glycoprotein component on a flu virus' surface that cleaves the alpha-ketosidic linkage of sialic acid (SA) located on human cells to release new virions that then infect nearby healthy cells, is the most important target for antiviral drug design. Oseltamivir functions as a neuraminidase inhibitor that binds competitively to the Sialic Acid (SA) binding site (Laver et al., 2006). Unfortunately, oseltamivir resistance has been a big concern to public health since 2005 and thus continues effort to gain insight of drug resistant mechanism and designing new effective medicine become highly significant.

The molecular model of H1N1pdm used in MD simulation was built from the crystal structure of avian H5N1 and the amino acid sequence of swine flu H1N1pdm from

**2. Ensemble-based docking** 

*2.1.1. MD simulation of ionized oseltamivir-neuraminidase complex* 

**2.1. Receptor** 

**Figure 1.** Schematic representations of drug-bound simulation systems. Shown here as a representative example of simulated systems is H1N1pdm bound to oselvamivir. In A), the simulation system is shown in the full explicit solvation box with oseltamivir and the active-site calcium ion labelled. In B), oseltamivir is shown buried in the SA binding pocket of H1N1pdm rendered in surface view
