避免c-Src蛋白的多肽类拮抗剂与多个蛋白发生混杂性结合，对于降低抗癌药物的毒性风险具有重要作用。本研究运用生物信息学方法对氨基酸序列进行优化设计，旨在减少混杂性结合的发生。本研究综合利用各种多肽数据库和生物信息学工具，首先总结了多肽分子与多个蛋白SH3结构域之间潜在的混杂性结合，并发现了其中的内在规律。随后，根据所发现的规律，对多肽的氨基酸序列进行针对性的优化设计。结果表明，大多数多肽在经过优化后，所结合的c-Src以外的蛋白数量都有所下降，从而显著提高了多肽与c-Src蛋白之间结合的特异性（P<0.05），并降低了其潜在的毒性风险。本研究所取得的结果将为设计具有高度特异性和低毒性的靶向性多肽药物提供参考。

It is important to avoid promiscuous binding between an anticancer peptide and multiple proteins with SH3 domain, so as to minimize the risks of unpredictable toxic and side effects. In the present study, we applied bioinformatics methods to optimize amino acid sequences, in order to reduce the probability of promiscuous binding. Relevant peptide databases and bioinformatics tools were utilized to summarize the rules of promiscuous binding between peptides and SH3 domains. Based on that, we specifically optimized the amino acid sequences of the peptides. The results suggest that most of the modified amino acid sequences exhibit lower level of binding promiscuity, which significantly improves the overall binding specificity and reduces safety risks (P<0.05). This study provides a reference for designing targeted peptide drugs with high binding specificity and low toxicity.

重庆市科委前沿与应用基础研究计划项目（cstc2014jcyjA10104）；重庆第二师范学院校级科研创新团队（KYC-cxtd03-2017004）；第二批重庆市高等学校青年骨干教师资助计划。