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Searching the conformational space for docking
In molecular modelling, docking is a method which predicts the preferred orientation of one molecule to another when bound together in a stable complex. In the case of protein docking, the search space consists of all possible orientations of the protein with respect to the ligand. Flexible docking in addition considers all possible conformations of the protein paired with all possible conformations of the ligand.
With present computing resources, it is impossible to exhaustively explore these search spaces; instead, there are many strategies which attempt to sample the search space with optimal efficiency. Most docking programs in use account for a flexible ligand, and several attempt to model a flexible protein receptor. Each "snapshot" of the pair is referred to as a pose.
== Molecular dynamics (MD) simulations ==
In this approach, proteins are typically held rigid, and the ligand is allowed to freely explore their conformational space. The generated conformations are then docked successively into the protein, and an MD simulation consisting of a simulated annealing protocol is performed. This is usually supplemented with short MD energy minimization steps, and the energies determined from the MD runs are used for ranking the overall scoring. Although this is a computer-expensive method (involving potentially hundreds of MD runs), it has some advantages: for example, no specialized energy/scoring functions are required. MD force-fields can typically be used to find poses that are reasonable and can be compared with experimental structures.
The Distance Constrained Essential Dynamics method (DCED) has been used to generate multiple structures for docking, called eigenstructures. This approach, although avoiding most of the costly MD calculations, can capture the essential motions involved in a flexible receptor, representing a form of coarse-grained dynamics.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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