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Cross-linked Peptide Data Obtained by Ion Mobility used to Sort Correct/Incorrect in silico Protein Conformation Predictions

机译:通过离子迁移率获得的交联肽数据,用于在硅蛋白兼容预测中进行校正/不正确

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Definition of the atomic interfaces in protein-protein complexes often depends on use of physical techniques like chemical cross-linking and mass spectrometry. Typical workflows include: chemically cross-linking two or more proteins, digesting proteins to peptides, proteolysis in H2O16 and H2O18 followed by MS analysis to detect and identify cross-linked peptides as we recently published (Gao et al. JBC & Anal Chem 2006). As with detection and sequencing of phosphopeptides, problematic to this approach is that cross-linked peptides are normally at low stoichiometry relative to all other peptides in the mixture and are thus very difficult to find. We investigated the ability of a new commercial ion mobility instrument to detect and identify cross-linked peptides. We also investigated the utility of using MS identified cystine-containing peptides to sort correct from incorrect in silico protein structure predictions made using tools like Rosetta from Professor David Baker at the University of Washington.
机译:蛋白质 - 蛋白质复合物中原子界面的定义通常取决于使用化学交联和质谱等物理技术的使用。典型的工作流包括:化学交联两种或更多种蛋白质,消化蛋白肽,蛋白水解H2O16和H2O18随后MS分析,以检测和识别的交联的肽,因为我们最近出版(Gao等人JBC&分析化学2006年)。 。与磷酸肽的检测和测序一样,对于这种方法有问题是交联肽通常相对于混合物中的所有其他肽的低化学计量,因此非常难以找到。我们调查了新的商业离子移动性仪器检测和识别交联肽的能力。我们还研究了使用MS鉴定的含有胱氨酸肽的效用,从硅蛋白质结构预测中的不正确排序,使用来自华盛顿大学的David Baker等Rosetta等工具的硅蛋白质结构预测。

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