Department of Chemistry and Biochemistry, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego, La Jolla California 92093, USA.
J Proteome Res. 2011 Jan 7;10(1):320-9. doi: 10.1021/pr100953b. Epub 2010 Dec 13.
Polyketide and nonribosomal peptides constitute important classes of small molecule natural products. Due to the proven biological activities of these compounds, novel methods for discovery and study of the polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) enzymes responsible for their production remains an area of intense interest, and proteomic approaches represent a relatively unexplored avenue. While these enzymes may be distinguished from the proteomic milieu by their use of the 4'-phosphopantetheine (PPant) post-translational modification, proteomic detection of PPant peptides is hindered by their low abundance and labile nature which leaves them unassigned using traditional database searching. Here we address key experimental and computational challenges to facilitate practical discovery of this important post-translational modification during shotgun proteomics analysis using low-resolution ion-trap mass spectrometers. Activity-based enrichment maximizes MS input of PKS/NRPS peptides, while targeted fragmentation detects putative PPant active sites. An improved data analysis pipeline allows experimental identification and validation of these PPant peptides directly from MS² data. Finally, a machine learning approach is developed to directly detect PPant peptides from only MS² fragmentation data. By providing new methods for analysis of an often cryptic post-translational modification, these methods represent a first step toward the study of natural product biosynthesis in proteomic settings.
聚酮和非核糖体肽是小分子天然产物的重要类别。由于这些化合物具有已证实的生物活性，因此寻找和研究负责其产生的聚酮合酶（PKS）和非核糖体肽合成酶（NRPS）的新方法仍然是一个非常感兴趣的领域，而蛋白质组学方法则代表了一个相对未被探索的途径。虽然这些酶可以通过使用 4'-磷酸泛酰巯基乙胺（PPant）的翻译后修饰来与蛋白质组环境区分开来，但由于其丰度低和不稳定，使用传统的数据库搜索很难检测到 PPant 肽。在这里，我们解决了使用低分辨率离子阱质谱仪进行鸟枪法蛋白质组学分析时实现这种重要翻译后修饰的实际发现所面临的关键实验和计算挑战。基于活性的富集最大限度地提高了 PKS/NRPS 肽的 MS 输入，而靶向碎裂则检测到了假定的 PPant 活性位点。改进后的数据分析流程允许直接从 MS²数据中实验鉴定和验证这些 PPant 肽。最后，开发了一种机器学习方法，可仅从 MS²碎裂数据中直接检测到 PPant 肽。通过提供分析通常是隐蔽的翻译后修饰的新方法，这些方法代表了在蛋白质组学环境中研究天然产物生物合成的第一步。
