David R, Cheriton School of Computer Science, University of Waterloo, Canada.
BMC Bioinformatics. 2010 Jan 18;11 Suppl 1(Suppl 1):S4. doi: 10.1186/1471-2105-11-S1-S4.
Tandem mass spectrometry (MS/MS) has become the primary way for protein identification in proteomics. A good score function for measuring the match quality between a peptide and an MS/MS spectrum is instrumental for the protein identification. Traditionally the to-be-measured peptides are fragmented with the collision induced dissociation (CID) method. More recently, the electron transfer dissociation (ETD) method was introduced and has proven to produce better fragment ion ladders for larger and more basic peptides. However, the existing software programs that analyze ETD MS/MS data are not as advanced as they are for CID.
To take full advantage of ETD data, in this paper we develop a new score function to evaluate the match between a peptide and an ETD MS/MS spectrum. Experiments on real data demonstrated that this newly developed score function significantly improved the de novo sequencing accuracy of the PEAKS software on ETD data.
A new and better score function for ETD MS/MS peptide identification was developed. The method used to develop our ETD score function can be easily reused to train new score functions for other types of MS/MS data.
串联质谱（MS/MS）已成为蛋白质组学中蛋白质鉴定的主要方法。用于测量肽与 MS/MS 谱之间匹配质量的良好评分函数对于蛋白质鉴定至关重要。传统上，待测量的肽是用碰撞诱导解离（CID）方法进行碎片化的。最近，引入了电子转移解离（ETD）方法，事实证明它可以为更大和更碱性的肽产生更好的片段离子梯。然而，分析 ETD MS/MS 数据的现有软件程序不如 CID 那样先进。
为了充分利用 ETD 数据，本文我们开发了一种新的评分函数来评估肽与 ETD MS/MS 谱之间的匹配。对真实数据的实验表明，与 CID 相比，新开发的评分函数显著提高了 PEAKS 软件在 ETD 数据上从头测序的准确性。
开发了一种新的、更好的 ETD MS/MS 肽鉴定评分函数。用于开发我们的 ETD 评分函数的方法可以轻松地重复用于训练其他类型的 MS/MS 数据的新评分函数。
