Docking and scoring in virtual screening for drug discovery: methods and applications

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Abstract
Computational methodologies have become a crucial component of many drug discovery programmes, from hit identification to lead optimization and beyond. One key such methodology — docking of small molecules to protein binding sites — was pioneered during the early 1980s, and remains a highly active area of research. The docking process involves the prediction of ligand conformation and orientation (or posing) within a targeted binding site. In general, there are two aims of docking studies: accurate structural modelling and correct prediction of activity. Docking is generally devised as a multi-step process in which each step introduces one or more additional degrees of complexity. The process begins with the application of docking algorithms that pose small molecules in the active site. These algorithms are complemented by scoring functions that are designed to predict the biological activity through the evaluation of interactions between compounds and potential targets. This article reviews basic concepts and specific features of small-molecule–protein docking methods and several selected applications, with particular emphasis on hit identification and lead optimization. We attempt to distinguish between the problems of docking compounds into target sites and of scoring docked conformations, because the available data indicate that numerous robust and accurate docking algorithms are available, whereas imperfections of scoring functions continue to be a major limiting factor.