瑞士苏黎世理工学院Ruedi Aebersold等研究人员开发出利用蛋白质组学数据分析复合物的新方法。2021年4月15日，国际知名学术期刊《自然—方法学》在线发表了这一成果。

研究人员报道了PCprophet，这是一种基于尺寸排除色谱法的工具：对所有理论质谱（SEC-SWATH-MS）数据进行顺序窗口采集，从而预测蛋白质复合物并表征其在整个实验条件下的变化。研究人员证明了PCprophet的性能优于最先进的方法，并介绍了一种贝叶斯方法来分析不同条件变化下的蛋白质间相互作用。研究人员提供了命令行和图形界面来支持将PCprophet应用于任何共分馏MS数据集，而与分离或定量液相色谱-MS工作流程无关，从而可用于蛋白质复合物及其生理动力学的检测和定量跟踪。

据悉，尽管有使用分析蛋白质复合物的方法，但是在多种条件下对复合物进行系统分析仍然具有挑战性。基于完整、天然复合物的生化分级分离和蛋白质谱相关性的方法已显示出希望。但是，大多数解释共分馏数据集来产生复杂成分和样品之间重排的方法在很大程度上取决于蛋白质间相互作用的推论。

附：英文原文

Title: PCprophet: a framework for protein complex prediction and differential analysis using proteomic data

Author: Andrea Fossati, Chen Li, Federico Uliana, Fabian Wendt, Fabian Frommelt, Peter Sykacek, Moritz Heusel, Mahmoud Hallal, Isabell Bludau, Tmay Capraz, Peng Xue, Jiangning Song, Bernd Wollscheid, Anthony W. Purcell, Matthias Gstaiger, Ruedi Aebersold

Issue&Volume: 2021-04-15

Abstract: Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein profiles have shown promise. However, most approaches for interpreting cofractionation datasets to yield complex composition and rearrangements between samples depend considerably on protein–protein interaction inference. We introduce PCprophet, a toolkit built on size exclusion chromatography–sequential window acquisition of all theoretical mass spectrometry (SEC-SWATH-MS) data to predict protein complexes and characterize their changes across experimental conditions. We demonstrate improved performance of PCprophet over state-of-the-art approaches and introduce a Bayesian approach to analyze altered protein–protein interactions across conditions. We provide both command-line and graphical interfaces to support the application of PCprophet to any cofractionation MS dataset, independent of separation or quantitative liquid chromatography–MS workflow, for the detection and quantitative tracking of protein complexes and their physiological dynamics.

DOI: 10.1038/s41592-021-01107-5

Source: https://www.nature.com/articles/s41592-021-01107-5