Zaidman Daniel, Wolfson Haim J
Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel.
Methods Mol Biol. 2017;1561:279-290. doi: 10.1007/978-1-4939-6798-8_16.
In this chapter we present two methods related to rational design of inhibitory peptides: PepCrawler: A tool to derive binding peptides from protein-protein complexes and the prediction of protein-peptide complexes. Given an initial protein-peptide complex, the method detects improved predicted peptide binding conformations which bind the protein with higher affinity. This program is a robotics motivated algorithm, representing the peptide as a robotic arm moving among obstacles and exploring its conformational space in an efficient way. PinaColada: A peptide design program for the discovery of novel peptide candidates that inhibit protein-protein interactions. PinaColada uses PepCrawler while introducing sequence mutations, in order to find novel inhibitory peptides for PPIs. It uses the ant colony optimization approach to explore the peptide's sequence space, while using PepCrawler in the refinement stage.
在本章中，我们介绍两种与抑制性肽的合理设计相关的方法：PepCrawler：一种从蛋白质-蛋白质复合物中推导结合肽并预测蛋白质-肽复合物的工具。给定一个初始的蛋白质-肽复合物，该方法可检测出具有更高亲和力结合蛋白质的改进预测肽结合构象。此程序是一种受机器人技术启发的算法，将肽表示为在障碍物间移动并高效探索其构象空间的机械臂。PinaColada：一种用于发现抑制蛋白质-蛋白质相互作用的新型肽候选物的肽设计程序。PinaColada在引入序列突变时使用PepCrawler，以便找到用于蛋白质-蛋白质相互作用的新型抑制性肽。它使用蚁群优化方法来探索肽的序列空间，同时在优化阶段使用PepCrawler。
