Prediction of Missed Proteolytic Cleavages for the Selection of Surrogate Peptides for Quantitative Proteomics
Prediction of Missed Proteolytic Cleavages for the Selection of Surrogate Peptides for Quantitative Proteomics
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DOI：
10.1089/omi.2011.0156
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发表时间：
2012-09-01
影响因子：
3.3
通讯作者：
Hubbard, Simon J.
中科院分区：
文献类型：
--
作者：
Lawless, Craig;Hubbard, Simon J.
定量蛋白质组学实验通常使用蛋白水解肽作为其亲本蛋白的替代品，从肽水平定量推断蛋白质量。这一过程通常依赖于亲本蛋白完全消化到其极限肽，这样它们的信号才真正具有代表性。不幸的是，蛋白质水解通常是不完全的，并且经常产生遗漏的裂解肽，这些肽不太可能是定量的最佳替代品，特别是对于寻求获得绝对值的标记介导方法。我们已经生成了一个预测计算工具，能够预测哪些候选蛋白水解肽键可能被标准酶胰蛋白酶遗漏。我们的交叉验证预测工具使用支持向量机，在多个蛋白质组中实现了超过0.94精度（PPV）的高精度，伴随着0.79的高灵敏度。我们相信这是一种选择候选定量肽的有用工具，可以最大限度地减少由于错过切割而导致的损失，这将为定量蛋白质组学管道以及其他蛋白质组学领域带来福音。我们的结果在最近的研究结果的背景下讨论了蛋白质组学消化方案中遗漏的裂解动力学，并显示与观察到的实验趋势一致。该软件已在http://king.smith.man.ac.uk/mcpred上提供。
Quantitative proteomics experiments are usually performed using proteolytic peptides as surrogates for their parent proteins, inferring protein amounts from peptide-level quantitation. This process is frequently dependent on complete digestion of the parent protein to its limit peptides so that their signal is truly representative. Unfortunately, proteolysis is often incomplete, and missed cleavage peptides are frequently produced that are unlikely to be optimal surrogates for quantitation, particularly for label-mediated approaches seeking to derive absolute values. We have generated a predictive computational tool that is able to predict which candidate proteolytic peptide bonds are likely to be missed by the standard enzyme trypsin. Our cross-validated prediction tool uses support vector machines and achieves high accuracy in excess of 0.94 precision (PPV), with attendant high sensitivity of 0.79, across multiple proteomes. We believe this is a useful tool for selecting candidate quantotypic peptides, seeking to minimize likely loss owing to missed cleavage, which will be a boon for quantitative proteomic pipelines as well as other areas of proteomics. Our results are discussed in the context of recent results examining the kinetics of missed cleavages in proteomic digestion protocols, and show agreement with observed experimental trends. The software has been made available at http://king.smith.man.ac.uk/mcpred.