Siegert Timothy R, Bird Michael, Kritzer Joshua A
Department of Chemistry, Tufts University, 62 Talbot Ave., Medford, MA, 02155, USA.
Methods Mol Biol. 2017;1561:255-277. doi: 10.1007/978-1-4939-6798-8_15.
Peptides are an increasingly useful class of molecules, finding unique applications as chemical probes and potential drugs. They are particularly adept at inhibiting protein-protein interactions, which are often difficult to target using small molecules. The identification and rational design of protein-binding epitopes remains a bottleneck in the development of bioactive peptides. One fruitful strategy has been using structured scaffolds to present essential hot spot residues involved in protein-protein recognition, and this process has been greatly advanced by computational tools that can identify hot spot residues. Here we discuss LoopFinder, a program that uses structures from the Protein Data Bank to comprehensively search for protein-protein interactions that are mediated by nonhelical, nonsheet loop structures. We developed LoopFinder to identify these "hot loops" and to assist in the design of cyclic peptides that mimic these important structures. In this article, we provide all key files, outline step-by-step methods for users to conduct independent LoopFinder searches, and provide guidance on additional potential applications for the LoopFinder program.
肽是一类越来越有用的分子，作为化学探针和潜在药物有着独特的应用。它们特别擅长抑制蛋白质-蛋白质相互作用，而小分子往往难以靶向这种相互作用。蛋白质结合表位的鉴定和合理设计仍然是生物活性肽开发中的一个瓶颈。一种富有成效的策略是使用结构化支架来呈现参与蛋白质-蛋白质识别的关键热点残基，并且通过能够识别热点残基的计算工具，这一过程已经取得了很大进展。在这里，我们讨论LoopFinder，这是一个利用蛋白质数据库中的结构全面搜索由非螺旋、非片状环结构介导的蛋白质-蛋白质相互作用的程序。我们开发LoopFinder是为了识别这些“热点环”，并协助设计模拟这些重要结构的环肽。在本文中，我们提供了所有关键文件，概述了用户进行独立LoopFinder搜索的逐步方法，并为LoopFinder程序的其他潜在应用提供了指导。
