Docking and Scoring in Drug Discovery

Abstract

The rational development of new lead compounds requires good understanding of the relationship between all the actors involved in a binding event (protein, ligand, water, metal ions, cofactors, etc.). Computational methods attempt to reproduce and predict the behavior of nature even though this can be very difficult. The docking/scoring paradigm is probably the most widespread and potentially useful computer-aided technique used in the discovery of new drugs. This paradigm can be analyzed as the sum of a “geometric” problem, that is, the implementation of algorithms to find the possible positions of a ligand in a receptor cavity, and a “chemistry” problem, that is, the evaluation of the solution list using good and realistic energy functions. In this chapter, we deal with the panorama of docking and scoring approaches and the related software packages. After a general introduction, some basic principles about the goodness and limits of experimental data used for computational simulations are described. Then an exhaustive examination of the most common docking methods and packages is carried out followed by an analysis of scoring functions developed to date, including the evolving consensus scoring approach. Next, several problems with the paradigm and their state-of-the-art partial solutions are discussed, including active site water, ionization states, tautomerization, flexibility, and the probability of more than one “correct” solution. Particular attention is paid for the upside and the downside of the problem in a short user guide for the docking and scoring beginner, followed by a conclusions and outlook. Keywords: computational chemistry; free energy; ligand docking; modeling; scoring functions