Initially, structure-based drug design (SBDD) approaches relied on the validity of the “lock and key” model, although this assumption leads to clear limitations. Thus, there are considerable efforts nowadays to incorporate the influence of (changes of) protein flexibility and mobility into recent drug design approaches. These efforts are grounded on the “induced-fit” and “conformational selection” models of ligand binding to proteins. Here we will summarize computational approaches in SBDD that address these issues, with a focus on methods that account for receptor plasticity. In particular, we consider how protein plasticity can be incorporated into docking strategies. Two requirements need to be met for this: first, one needs to detect what can move and how; second, this knowledge needs to be transformed into a docking algorithm. With regard to the former, knowledge about moving protein parts can be gained from experimental information as well as established techniques such as molecular dynamics simulations, graph theoretical and geometry-based approaches, or harmonic analysis-based methods. With regard to the latter, a plethora of approaches has been presented recently that range from considering protein plasticity only implicitly to modeling sidechain movements to also including backbone changes. A hallmark of all these approaches is that they need to balance accuracy and efficiency. Case studies of SBDD for which the inclusion of protein plasticity was crucial to success are noted along these lines. This provides a picture of scope and limitations of the current approaches as well as guidelines for further developments.