11. Docking Simulation
Chia-Hsien Lee and Hsueh-Fen Juan∗
Graduate Institute of Biomedical Electronics and Bioinformatics,
National Taiwan University, Taipei, Taiwan
∗[email protected]- Introduction
In computational drug discovery, there are two strategies to do drug design:
ligand-based and structure-based. In ligand-based drug design, a set of
common ligand of target protein is used to deduce, from the similarity of that
set of ligands, a novel drug. In structure-based drug design, information of
protein structure and putative compounds are utilized in the drug discovery
process. For example, in the work of Bessa et al.,^1 docking simulation
was performed to explore the reason of synergy interaction between the
two specific compounds and antibiotic oxacillin. Li et al.^2 used docking
simulation (structure-based) and pharmacophore (ligand-based drug design)
and then found two putative lead compounds for inosine 5′-monophosphate
dehydrogenase, which is an attractive target in immunosuppressive, anti-
cancer, antiviral, and antiparasitic therapeutic strategies. We will focus on
structure-based drug design, especially docking simulation, from now on.
Docking simulation is the most widely used technique in structure-based
drug design. The structures of the target protein and compound are input
into a docking algorithm which will find the best pose of their binding. Since
it is all about finding the “best” poses of the binding of protein and the
compound, docking simulation is essentially an optimization problem, and
thus can be solved by optimization algorithms after proper formulation. Most
docking simulation software packages use various optimization algorithms for
their calculation jobs.
Autodock Vina,^3 a standalone docking and an open-source application
package, is widely used when a biologist needs to run docking simulation.
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