The development of a new drug is an expensive and time-consuming process that takes around 10-15 years with an average cost of US $ 1.3-2.9 billion . Virtual screening approaches have been increasingly applied in the drug discovery process, evidenced by their involvement in more than 70 approved drugs . In most cases, computational approaches have been extensively used in the initial stages including hit to lead and lead optimisation. They can offset the costs associated with bringing novel drugs to market, and accelerate the preclinical drug screening process. Docking is the most prominently used virtual screening approach. It has been employed as a fast way to predict whether a given compound is able to bind to a specific target, and to estimate the putative bound conformation of the compound. Docking approaches perform well at recapitulating binding modes and assessing the fit of molecules into binding sites. Furthermore, this placement ability allows them to separate actives and inactive molecules and provide enriched selections with greater chance of showing bioactivity. However, the docking scores are generally not an accurate indicator for the binding energies and cannot rank the activity of structurally similar molecules. Consequently, more sophisticated approaches are needed, that on the one hand capture the dynamic nature of protein ligand binding, whilst also provide a more correct physical assessment of the interaction and binding energies. Molecular dynamics simulations are well suited to study the dynamics of the proteins, refined binding poses, and more importantly, generate more reliable predicted binding affinities.