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Survey of public domain software for docking simulations and virtual screening

DOI: 10.1186/1479-7364-5-5-497

Keywords: drug discovery, small molecule docking, virtual screening, docking packages, visualisation of docking poses, oestrogen receptor, oestrogen activity prediction, SAR

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Docking simulations and virtual screening are being routinely used in drug design, enabling rapid identification of hits and lead compounds [1-3]. The goal of docking simulations is to determine the binding mode (bound conformation) and the strength of binding (binding affinity) between a ligand, which is typically assumed to be a small molecule, and a macromolecular receptor, such as a protein [1,3,4]. Given a resolved or modelled structure of a target receptor, virtual screening involves performing docking simulations for a large number of candidate compounds in order to identify putative leads [2,5,6]. These candidates can subsequently be characterised and validated by empirical binding and activity assays, and by assessing their toxicity, pharmacokinetics and other properties for further drug development [7-9].Many methods for molecular docking and virtual screening have been developed to date, including AutoDock,[10,11] DOCK,[12-14] Flex,[15] Glide,[16] GOLD,[17] RosettaDock,[18] SLIDE [19,20] and Surflex [21]. These methods introduce various approximations to simplify the problem -- for example, assuming a rigid body docking model in which the receptor structure is fixed. Rigid body docking allows one to speed-up computations by comparison with flexible docking (in which the receptor structure is allowed to move) by precomputing the forces experienced by the ligand on a grid. In general, docking simulations involve two main components: sampling algorithms to find plausible conformations of the complex, and scoring functions to estimate relative binding affinities and rank ligand poses [1].The sampling of alternative conformation is coupled with the search for the optimal solution --that is, poses with the highest binding affinity (or score), which typically involves solving a global optimisation problem. Consequently, various optimisation techniques -- such as Monte Carlo, simulated annealing or genetic algorithms -- are used in the context of docking simulati


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