Department of Computer Science, Indiana University Bloomington, 700 N. Woodlawn Avenue, Bloomington, IN, 47408, USA.
Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, 719 Indiana Avenue, Indianapolis, IN, 46202, USA.
BMC Bioinformatics. 2018 Aug 13;19(Suppl 9):280. doi: 10.1186/s12859-018-2273-4.
Top-down homogeneous multiplexed tandem mass (HomMTM) spectra are generated from modified proteoforms of the same protein with different post-translational modification patterns. They are frequently observed in the analysis of ultramodified proteins, some proteoforms of which have similar molecular weights and cannot be well separated by liquid chromatography in mass spectrometry analysis.
We formulate the top-down HomMTM spectral identification problem as the minimum error k-splittable flow problem on graphs and propose a graph-based algorithm for the identification and quantification of proteoforms using top-down HomMTM spectra.
Experiments on a top-down mass spectrometry data set of the histone H4 protein showed that the proposed method identified many proteoform pairs that better explain the query spectra than single proteoforms.
自上而下同质串联质谱（HomMTM）谱是由具有不同翻译后修饰模式的同一蛋白质的修饰蛋白产物产生的。它们经常在超修饰蛋白质的分析中被观察到，其中一些蛋白质产物具有相似的分子量，并且在质谱分析中的液相色谱中不能很好地分离。
我们将自上而下的 HomMTM 光谱识别问题表述为图上的最小错误 k 可分裂流问题，并提出了一种基于图的算法，用于使用自上而下的 HomMTM 光谱识别和定量蛋白质产物。
对组蛋白 H4 蛋白质的自上而下质谱数据集的实验表明，与单个蛋白质产物相比，所提出的方法能够识别出许多更好地解释查询光谱的蛋白质产物对。
