Abstract：
Docking methods can be used to predict the orientations of two or more molecules with respect of each other using a plethora of various algorithms, which can be based on the physics of interactions or can use information from databases and templates. The usability of these approaches depends on the type and size of the molecules, whose relative orientation will be estimated. The two most important limitations are (i) the computational cost of the prediction and (ii) the availability of the structural information for similar complexes. In general, if there is enough information about similar systems, knowledge-based and template-based methods can significantly reduce the computational cost while providing high accuracy of the prediction. However, if the information about the system topology and interactions between its partners is scarce, physics-based methods are more reliable or even the only choice. In this chapter, knowledge-, template-, and physics-based methods will be compared and briefly discussed providing examples of their usability with a special emphasis on physics-based protein-protein, protein-peptide, and protein-fullerene docking in the UNRES coarse-grained model.
摘要：
对接方法可用于使用多种算法来预测两个或更多个分子相对于彼此的取向。它可以基于相互作用的物理原理，也可以使用来自数据库和模板的信息。这些方法的可用性取决于分子的类型和大小，将估计其相对方向。两个最重要的限制是（i）预测的计算成本和（ii）相似复合物的结构信息的可用性。总的来说,如果有足够的类似系统的信息，基于知识和基于模板的方法可以显着降低计算成本，同时提供高精度的预测。然而,如果有关系统拓扑及其合作伙伴之间的交互的信息很少，基于物理的方法更可靠，甚至是唯一的选择。在这一章中,知识-，模板-,和基于物理的方法将进行比较和简要讨论，提供其可用性的例子，特别强调基于物理的蛋白质，蛋白质，蛋白质肽，和UNRES粗粒模型中的蛋白质-富勒烯对接。
