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Identification of target-binding peptide motifs by high-throughput sequencing of phage-selected peptides

机译:通过噬菌体选择肽的高通量测序鉴定靶标结合肽基序

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摘要

High-throughput sequencing was previously applied to phage-selected peptides in order to gain insight into the abundance and diversity of isolated peptides. Herein we developed a procedure to efficiently compare the sequences of large numbers of phage-selected peptides for the purpose of identifying target-binding peptide motifs. We applied the procedure to analyze bicyclic peptides isolated against five different protein targets: sortase A, urokinase-type plasminogen activator, coagulation factor XII, plasma kallikrein and streptavidin. We optimized sequence data filters to reduce biases originating from the sequencing method and developed sequence correction algorithms to prevent identification of false consensus motifs. With our strategy, we were able to identify rare target-binding peptide motifs, as well as to define more precisely consensus sequences and sub-groups of consensus sequences. This information is valuable to choose peptide leads for drug development and it facilitates identification of epitopes. We furthermore show that binding motifs can be identified after a single round of phage selection. Such a selection regimen reduces propagation-related bias and may facilitate application of phage display in non-specialized laboratories, as procedures such as bacterial infection, phage propagation and purification are not required.
机译:先前将高通量测序应用于噬菌体选择的肽,以深入了解分离肽的丰度和多样性。本文中,我们开发了一种程序,可以有效地比较大量噬菌体选择肽的序列,以鉴定靶标结合肽基序。我们应用该程序分析了针对五种不同蛋白质靶标的双环肽:分选酶A,尿激酶型纤溶酶原激活物,凝血因子XII,血浆激肽释放酶和链霉亲和素。我们优化了序列数据过滤器以减少源自测序方法的偏差,并开发了序列校正算法以防止识别错误的共有基序。通过我们的策略,我们能够识别罕见的靶标结合肽基序,以及更精确地定义共有序列和共有序列的子组。该信息对于选择用于药物开发的肽前导非常有价值,并且有助于鉴定表位。我们进一步表明,在单轮噬菌体选择后可以鉴定结合基序。由于不需要诸如细菌感染,噬菌体繁殖和纯化之类的程序,因此这种选择方案减少了与繁殖有关的偏见并且可以促进噬菌体展示在非专业实验室中的应用。

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