A variety of academic and commercial methods for computational ligand docking are currently available (see Ref 1 (link) for an extensive review of current methods). Most of these methods simplify the problem in two ways to make the computation tractable. First, the conformational space is reduced by imposing limitations to the system, such as a rigid receptor and fixed bond angles and lengths in the ligand. Second, a simplified scoring function, often based on empirical free energies of binding, is used to score poses quickly at each step of the conformation search.
Both of these are serious limitations, and users must employ tools such as molecular dynamics or free energy perturbation if a more realistic conformational search or energy prediction is necessary. These tools are complementary with computational docking methods, since docking methods generally search a larger conformational space, but more advanced methods can predict conformation and energy more accurately within a local area of the conformational landscape.
Advanced docking methods may be used to improve results in cases where the limitations of requiring a rapid method for energy evaluation are too restrictive. For instance, many docking methods employ a rigid model for the receptor, which often leads to improper results for proteins with appreciable induced fit upon binding. AutoDock includes a method for treating a selection of receptor sidechains explicitly, to account for limited conformational changes in the receptor. In addition, ordered water molecules often mediate interactions between ligands and receptors, and advanced methods for treating selected waters explicitly have been implemented in AutoDock. Both of these advanced methods are demonstrated in this protocol.
Many reports have compared the performance of popular docking methods such as AutoDock (recently reviewed by Sousa et al. 7 (link)). Different methods can achieve different success rates depending on specific targets, but in general, they all perform similarly when tested on a series of diverse protein-ligand complexes: they all perform well for the prediction of bound complexes for drug-sized molecules, with estimates of free energies of binding with errors of roughly 2–3 kcal/mol, provided that there is not significant motion required in the receptor. Better results may be obtained by tuning the docking method for a particular system or moving to more sophisticated and computationally-intensive parameterizations of the system.
Both of these are serious limitations, and users must employ tools such as molecular dynamics or free energy perturbation if a more realistic conformational search or energy prediction is necessary. These tools are complementary with computational docking methods, since docking methods generally search a larger conformational space, but more advanced methods can predict conformation and energy more accurately within a local area of the conformational landscape.
Advanced docking methods may be used to improve results in cases where the limitations of requiring a rapid method for energy evaluation are too restrictive. For instance, many docking methods employ a rigid model for the receptor, which often leads to improper results for proteins with appreciable induced fit upon binding. AutoDock includes a method for treating a selection of receptor sidechains explicitly, to account for limited conformational changes in the receptor. In addition, ordered water molecules often mediate interactions between ligands and receptors, and advanced methods for treating selected waters explicitly have been implemented in AutoDock. Both of these advanced methods are demonstrated in this protocol.
Many reports have compared the performance of popular docking methods such as AutoDock (recently reviewed by Sousa et al. 7 (link)). Different methods can achieve different success rates depending on specific targets, but in general, they all perform similarly when tested on a series of diverse protein-ligand complexes: they all perform well for the prediction of bound complexes for drug-sized molecules, with estimates of free energies of binding with errors of roughly 2–3 kcal/mol, provided that there is not significant motion required in the receptor. Better results may be obtained by tuning the docking method for a particular system or moving to more sophisticated and computationally-intensive parameterizations of the system.
