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An Efficient Dynamic Programming Algorithm for Phosphorylation Site Assignment of Large-Scale Mass Spectrometry Data

机译：大规模质谱数据磷酸化站点分配有效动态规划算法

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摘要

Phosphorylation site assignment of large-scale data from high throughput tandem mass spectrometry (LC-MS/MS) data is an important aspect of phosphoproteomics. Correct assignment of phosphorylated residue(s) is important for functional interpretation of the data within a biological context. Common search algorithms (Sequest etc.) for mass spectrometry data are not designed for accurate site assignment; thus, additional algorithms are needed. In this paper, we propose a linear-time and linear-space dynamic programming strategy for phospho-rylation site assignment. The algorithm, referred to as PhosSA, optimizes the objective function defined as the summation of peak intensities that are associated with theoretical phosphopeptide fragmentation ions. Quality control is achieved through the use of a post-processing criteria whose value is indicative of the signal-to-noise (S/N) properties and redundancy of the fragmentation spectra. The algorithm is tested using experimentally generated data sets of peptides with known phosphorylation sites while varying the fragmentation strategy (CID or HCD) and molar amounts of the peptides. The algorithm is also compatible with various peptide labeling strategies including SILAC and iTRAQ. PhosSA is shown to achieve > 99% accuracy with a high degree of sensitivity. The algorithm is extremely fast and scalable (able to process up to 0.5 million peptides in an hour). The implemented algorithm is freely available at http://helixweb.nih.gov/ESBL/PhosSA/ for academic purposes.
机译：来自高通量串联质谱（LC-MS / MS）数据的大规模数据的磷酸化部位分配是磷蛋白酶的重要方面。正确分配磷酸化残留物对于生物学环境中数据的功能解释是重要的。用于质谱数据的常见搜索算法（续集等）不设计用于准确的现场分配;因此，需要额外的算法。在本文中，我们提出了一种用于磷酸族化现场分配的线性时间和线性空间动态规划策略。该算法称为Phossa，优化了定义为与理论磷酸肽碎片离子相关的峰强度的总和的目标函数。通过使用后处理标准来实现质量控制，其值指示碎片谱的信号对噪声（S / N）属性和冗余。使用通过实验生成的肽的肽的肽测试算法，同时改变碎片策略（CID或HCd）和母肽的晶粒量。该算法还与各种肽标记策略相容，包括氧化硅酸和ITRAQ。 Phossa显示出高度敏感度的精度> 99％。该算法非常快速且可扩展（能够在一小时内处理高达0.5百万个肽）。实现的算法在http://helixweb.nih.gov/esbl/phossa/进行学术目的。

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