Manitoba Centre for Proteomics and Systems Biology, University of Manitoba , 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada.
Department of Internal Medicine, University of Manitoba , 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada.
Anal Chem. 2017 May 16;89(10):5526-5533. doi: 10.1021/acs.analchem.7b00537. Epub 2017 Apr 26.
The development of a peptide retention prediction model for hydrophilic interaction liquid chromatography (XBridge Amide column) is described for a collection of ∼40 000 tryptic peptides. Off-line 2D LC-MS/MS analysis (HILIC-RPLC) of S. cerevisiae whole cell lysate has been used to acquire retention information for a HILIC separation. The large size of the optimization data set (more than 2 orders of magnitude compared to previous reports) permits the accurate assignment of hydrophilic retention coefficients of individual amino acids, establishing both the effects of amino acid position relative to peptide termini and the influence of peptide secondary structure in HILIC. The accuracy of a simple additive model with peptide length correction (R value of ∼0.96) was found to be much higher compared to an algorithm of similar complexity applied to RPLC (∼0.91). This indicates significantly smaller influence of peptide secondary structure and interactions with counterions in HILIC. Nevertheless, sequence-specific features were found. Helical peptides that tend to retain stronger than predicted in RPLC exhibit negative prediction errors using an additive HILIC model. N-cap helix stabilizing motifs, which increase retention of amphipathic helical peptides in RP, reduce peptide retention in HILIC independently of peptide amphipathicity. Peptides carrying multiple Pro and Gly (residues with lowest helical propensity) retain stronger than predicted. We conclude that involvement of the peptide backbone's carbonyl and amide groups in hydrogen-bond stabilization of helical structures is a major factor, which determines sequence-dependent behavior of peptides in HILIC. The incorporation of observed sequence dependent features into our Sequence-Specific Retention Calculator HILIC model resulted in 0.98 R value correlation, significantly exceeding the predictive performance of all RP and HILIC models developed for complex mixtures of tryptic peptides.
描述了用于亲水性相互作用液相色谱（XBridge Amide 柱）的肽保留预测模型的开发，该模型针对约 40000 个胰蛋白酶肽。已使用酿酒酵母全细胞裂解物的离线 2D LC-MS/MS 分析（HILIC-RPLC）获取 HILIC 分离的保留信息。优化数据集的规模很大（与以前的报告相比超过 2 个数量级），可以准确分配单个氨基酸的亲水保留系数，从而确定氨基酸位置相对于肽末端的影响以及肽在 HILIC 中的二级结构的影响。与应用于 RPLC 的类似复杂度的算法（约 0.91）相比，具有肽长度校正的简单加性模型（R 值约为 0.96）的准确性要高得多。这表明在 HILIC 中肽二级结构和与抗衡离子的相互作用的影响要小得多。尽管如此，还是发现了序列特异性特征。在 RPLC 中保留能力强于预测的螺旋肽在使用加性 HILIC 模型时表现出负预测误差。增加 RP 中两亲性螺旋肽保留的 N-帽螺旋稳定基序，独立于肽两亲性，降低 HILIC 中的肽保留。携带多个 Pro 和 Gly（螺旋倾向最低的残基）的肽保留能力强于预测。我们得出结论，肽骨架的羰基和酰胺基团参与螺旋结构的氢键稳定是一个主要因素，它决定了肽在 HILIC 中序列依赖性行为。将观察到的序列相关特征纳入我们的序列特异性保留计算器 HILIC 模型中，导致 R 值相关性为 0.98，显著超过为复杂混合胰蛋白酶肽开发的所有 RP 和 HILIC 模型的预测性能。
