Estimating the Distribution of Protein Post-Translational Modification States by Mass Spectrometry.
Estimating the Distribution of Protein Post-Translational Modification States by Mass Spectrometry.
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DOI：
10.1021/acs.jproteome.8b00150
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发表时间：
2018-08-03
影响因子：
4.4
通讯作者：
Gunawardena J
中科院分区：
文献类型：
--
作者：
Compton PD;Kelleher NL;Gunawardena J
蛋白质的翻译后修饰（PTM）在细胞信息编码中起着核心作用，但PTM状态的复杂性一直难以解开。单个分子可以表现出跨多个位点共发生的PTM的“模态”或组合模式，并且分子群体可以表现出不同模态的量的分布。如何通过质谱法（MS）来估计这种“模态分布”？基于切割成肽的自下而上MS破坏了不同肽上PTM之间的相关性，但可以想象，具有适当切割模式的多种蛋白酶可以重建modform分布。我们介绍了一种数学语言来描述MS测量和显示，相反，无论有多少不同的蛋白酶是可用的，重建所需的信息的短缺指数随着网站数量的增加而增加。虽然对完整蛋白质进行自上而下的MS可以做得更好，但目前的技术无法阻止指数恶化。然而，我们的分析也表明，所有形式的MS产生线性方程的modform量。这允许不同的MS协议被集成，并且modform分布被约束在高维“modform区域”内，这可以提供用于分析信息编码的可行代理。
Post-translational modifications (PTMs) of proteins play a central role in cellular information encoding, but the complexity of PTM state has been challenging to unravel. A single molecule can exhibit a “modform” or combinatorial pattern of co-occurring PTMs across multiple sites, and a molecular population can exhibit a distribution of amounts of different modforms. How can this “modform distribution” be estimated by mass spectrometry (MS)? Bottom-up MS, based on cleavage into peptides, destroys correlations between PTMs on different peptides, but it is conceivable that multiple proteases with appropriate patterns of cleavage could reconstruct the modform distribution. We introduce a mathematical language for describing MS measurements and show, on the contrary, that no matter how many distinct proteases are available, the shortfall in information required for reconstruction worsens exponentially with increasing numbers of sites. Whereas top-down MS on intact proteins can do better, current technology cannot prevent the exponential worsening. However, our analysis also shows that all forms of MS yield linear equations for modform amounts. This permits different MS protocols to be integrated and the modform distribution to be constrained within a high-dimensional “modform region”, which may offer a feasible proxy for analyzing information encoding.
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影响因子：
7.3
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Nobles KN;Xiao K;Ahn S;Shukla AK;Lam CM;Rajagopal S;Strachan RT;Huang TY;Bressler EA;Hara MR;Shenoy SK;Gygi SP;Lefkowitz RJ
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通讯作者：
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