AutoDock Gateway for Molecular Docking Simulations in Cloud Systems - Cloud Computing with e-Science Applications - page 221

application, namely, AutoDock. In fact, three different variants of AutoDock
parameter sweep workflows have been developed, and they are described.
10.3.1 The AutoDock Application
Traditionally, in vitro studies have been used to investigate the binding of
receptors to their ligands and enzymes to their substrates. These wet labo-
ratory experiments are both time consuming and expensive to carry out.
An in-silico system based on computer simulations can facilitate the model-
ing of receptor-ligand interactions prior to the wet laboratory experiments
and enable scientists to better focus the in-vitro experiments using only
the most promising molecules. With the advances in computer technology,
it is now feasible to screen hundreds of thousands of compounds against a
single receptor to identify new inhibitors or therapeutic agents. However,
the modeling programs are not user friendly, and the relationship between
results obtained by molecular modeling and by in-vitro studies and the
newer biosensors still needs to be established.
AutoDock is one example of a program that allows in-silico modeling
of intermolecular interactions. AutoDock is a suite of automated docking
tools. It is designed to predict how small molecules, such as substrates or
drug candidates, bind to a receptor of known three-dimensional (3D) struc-
ture. AutoDock currently comprises two discrete generations of software:
AutoDock4 and AutoDock Vina.
AutoDock 4 is typically used to accurately model the molecular dock-
ing of a single ligand to a single receptor. In this instance, the process is
composed of three discrete stages. First, a low-complexity sequential pre-
processing stage defines a random starting location in 3D space (termed the
docking space ) for both the ligand and the receptor. This is achieved using
a tool within AutoDockTools (ADT) called AutoGrid. The locations, which
are characterized by atomic energy levels at each point within the docking
space, act as a single common input to a second stage. The second stage can
comprise many parallel jobs, each receiving a copy of the ligand and receptor
starting locations that form the input to a genetic algorithm. The algorithm
acts to randomly rotate/reposition the ligand and then determine likely
docking/binding sites based on energy levels, which are calculated from
the original starting locations. This process can be considered a parameter
sweep, where the varied input parameter is the initial random rotation of the
ligand. Finally, a single low-complexity sequential postprocessing stage can
be used to identify the most likely binding sites by comparing energies from
all jobs of the preceding stage (where minimized energies represent likely
docking sites).
AutoDock Vina provides several enhancements over AutoDock4, increas-
ing average simulation accuracy while also being up to two orders of
magnitude faster. Autodock Vina is particularly useful for virtual screening,
whereby a large set of ligands can be compared for docking suitability with a