PHONEMeS: Efficient Modeling of Signaling Networks Derived from Large-Scale Mass Spectrometry Data
PHONEMeS: Efficient Modeling of Signaling Networks Derived from Large-Scale Mass Spectrometry Data
复制标题
PHONEMeS： 根据大规模质谱数据建立信号网络的高效模型
DOI：
10.1021/acs.jproteome.0c00958
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发表时间：
2021-03-08
影响因子：
4.4
通讯作者：
Saez-Rodriguez, Julio
中科院分区：
文献类型：
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作者：
Gjerga, Enio;Dugourd, Aurelien;Saez-Rodriguez, Julio
蛋白质的翻译后修饰在细胞过程的调节中发挥着重要作用。蛋白质组修饰的质谱分析为研究蛋白质抑制剂如何影响细胞内的磷酸信号传导机制提供了巨大的潜力。我们最近提出了 PHONEMeS，一种使用高内涵鸟枪磷酸化蛋白质组数据构建信号扰动流逻辑网络模型的方法。然而，在其最初的实现中，PHONEMeS 的计算要求很高，并且仅用于在扰动环境中对信号进行建模。我们将 PHONEMeS 重新表述为一种整数线性程序 (ILP)，其效率比原始程序高出几个数量级。我们还扩展了可以分析的场景。 PHONEMeS 不仅可以对已知目标的扰动数据进行建模，还可以对任何一组失调激酶的上游和下游失调通路进行建模。最后，PHONEMeS 现在可以分析多个时间点的数据集，这有助于我们更好地了解信号传播的动态。我们在各种医学相关数据集上说明了新方法的价值，其中我们阐明了信号机制和药物作用模式。
Post-translational modifications of proteins play an important role in the regulation of cellular processes. The mass spectrometry analysis of proteome modifications offers huge potential for the study of how protein inhibitors affect the phosphosignaling mechanisms inside the cells. We have recently proposed PHONEMeS, a method that uses high-content shotgun phosphoproteomic data to build logical network models of signal perturbation flow. However, in its original implementation, PHONEMeS was computationally demanding and was only used to model signaling in a perturbation context. We have reformulated PHONEMeS as an Integer Linear Program (ILP) that is orders of magnitude more efficient than the original one. We have also expanded the scenarios that can be analyzed. PHONEMeS can model data upon perturbation on not only a known target but also deregulated pathways upstream and downstream of any set of deregulated kinases. Finally, PHONEMeS can now analyze data sets with multiple time points, which helps us to obtain better insight into the dynamics of the propagation of signals. We illustrate the value of the new approach on various data sets of medical relevance, where we shed light on signaling mechanisms and drug modes of action.