Tsur Dekel, Tanner Stephen, Zandi Ebrahim, Bafna Vineet, Pevzner Pavel A
Computer Science and Engineering, University of California at San Diego, USA.
Proc IEEE Comput Syst Bioinform Conf. 2005:157-66. doi: 10.1109/csb.2005.34.
Post-translational modifications (PTMs) are of great biological importance. Most existing approaches perform a restrictive search that can only take into account a few types of PTMs and ignore all others. We describe an unrestrictive PTM search algorithm that searches for all types of PTMs at once in a blind mode, i.e., without knowing which PTMs exist in a sample. The blind PTM identification opens a possibility to study the extent and frequencies of different types of PTMs, still an open problem in proteomics. Using our new algorithm, we were able to construct a two-dimensional PTM frequency matrix that reflects the number of MS/MS spectra in a sample for each putative PTM type and each amino acid. Application of this approach to a large IKKb dataset resulted in the largest set of PTMs reported for a single MS/MS sample so far. We demonstrate an excellent correlation between high values in the PTM frequency matrix and known PTMs thus validating our approach. We further argue that the PTM frequency matrix may reveal some still unknown modifications that warrant further experimental validation.
翻译后修饰（PTMs）具有重大的生物学意义。大多数现有方法进行的是限制性搜索，只能考虑少数几种类型的翻译后修饰，而忽略其他所有类型。我们描述了一种非限制性的翻译后修饰搜索算法，该算法以盲目模式同时搜索所有类型的翻译后修饰，即不知道样品中存在哪些翻译后修饰。盲目识别翻译后修饰为研究不同类型翻译后修饰的程度和频率开辟了可能性，这在蛋白质组学中仍是一个未解决的问题。使用我们的新算法，我们能够构建一个二维翻译后修饰频率矩阵，该矩阵反映了样品中每种假定的翻译后修饰类型和每种氨基酸的MS/MS谱图数量。将这种方法应用于一个大型IKKb数据集，得到了迄今为止单个MS/MS样品报道的最大翻译后修饰集。我们证明了翻译后修饰频率矩阵中的高值与已知翻译后修饰之间具有极好的相关性，从而验证了我们的方法。我们进一步认为，翻译后修饰频率矩阵可能揭示一些仍未知的修饰，值得进一步的实验验证。
