Abstract: Protein-peptide interaction is prevailing in computational biology, the accurate binding site prediction of protein-peptide is of great importance for understanding signal pathway in vivo, protein functionality and rational drug design. Since computational protein-peptide docking methods can provide sufficient modeling, the performance of them is crucial for experimental accuracy and docking success. In this paper, by reviewing current research progress in protein-peptide docking, it has a comprehensive understanding of protein-peptide docking methods performance, and especially extends the Fully Informed Particle Swarm Dock （FIPSDock） docking method to protein-peptide complexes for test. Experiments are conducted on 21 test cases of standard peptide docking benchmark peptiDB and another custom dataset with 13 cases, to have a comparative comparison of docking accuracy and success rate, the results demonstrate feasibility and novel performance of  FIPSDock for peptide docking.

Key words: peptide docking, protein-peptide interaction, binding site prediction, docking minimization

摘要： 蛋白质-多肽间相互作用是计算生物学中的热门方向，对其结合的精确预测对于了解体内复杂的信号通路以及蛋白质功能，及进一步进行药物设计有着至关重要的作用。蛋白质-多肽对接方法能够有效地模拟蛋白质-多肽间相互作用，其对接性能直接决定模拟实验的准确性和成功与否。针对当前主要的蛋白质-多肽对接方法，综合测试了其算法性能；同时将本实验室开发的基于全信息粒子群算法的分子对接工具FIPSDock（Fully-Informed-Particle-Swarm-Dock）延伸到蛋白质-多肽对接领域，并评估其性能。利用标准蛋白质-多肽对接数据集（peptiDB）的21个测试例及13个定制测试例进行性能测试，主要对比分析了各算法的成功率和对接精度。结果表明FIPSDock可用于蛋白质-多肽对接，并相对于其他对接算法展示出优异的性能。

关键词: 多肽对接, 蛋白质-多肽间相互作用, 结合位点预测, 对接优化