Peptides have recently attracted much attention as promising drug candidates. Rational design of peptide-derived therapeutics usually requires structural characterization of the underlying protein–peptide interaction. Given that experimental characterization can be difficult, reliable computational tools are needed. In recent years, a variety of approaches have been developed for ‘protein–peptide docking’, that is, predicting the structure of the protein–peptide complex, starting from the protein structure and the peptide sequence, including variable degrees of information about the peptide binding site and/or conformation. In this review, we provide an overview of protein–peptide docking methods and outline their capabilities, limitations, and applications in structure-based drug design. Key challenges are also briefly discussed, such as modeling of large-scale conformational changes upon binding, scoring of predicted models, and optimal inclusion of varied types of experimental data and theoretical predictions into an integrative modeling process.

肽作为有前途的候选药物最近引起了广泛的关注。肽衍生疗法的合理设计通常需要对潜在的蛋白-肽相互作用进行结构表征。鉴于可能难以进行实验表征，因此需要可靠的计算工具。近年来，已开发出多种方法用于“蛋白质-肽对接”，即从蛋白质的结构和肽序列开始，预测蛋白质-肽复合物的结构，包括有关肽的信息的可变程度结合位点和/或构象。在这篇综述中，我们提供了蛋白质-肽对接方法的概述，并概述了它们的功能，局限性以及在基于结构的药物设计中的应用。还简要讨论了主要挑战，