The completion of the human genome project has resulted in an increasing number of new
therapeutic targets for drug discovery. At the same time, high-throughput protein
purification, crystallography and nuclear magnetic resonance spectroscopy techniques have
been developed and contributed to many structural details of proteins and protein–ligand
complexes. These advances allow the computational strategies to permeate all aspects of
drug discovery today [1-5], such as the virtual screening (VS) techniques [6] for hit
identification and methods for lead optimization. Compared with traditional experimental
high-throughput screening (HTS), VS is a more direct and rational drug discovery approach
and has the advantage of low cost and effective screening [7-9]. VS can be classified into
ligand-based and structure-based methods. When a set of active ligand molecules is known
and little or no structural information is available for targets, the ligand-based methods, such
as pharmacophore modeling and quantitative structure activity relationship (QSAR) methods
can be employed. As to structure-based drug design, molecular docking is the most common
method which has been widely used ever since the early 1980s [10]. Programs based on
different algorithms were developed to perform molecular docking studies, which have
made docking an increasingly important tool in pharmaceutical research. Various excellent
reviews on docking have been published in the past [5, 11-14], and many comparison
studies were conducted to evaluate the relative performance of the programs [15-18].