Chemi-enzymatic and data mining approaches for the identification of post-translational modifications

蛋白质的翻译后修饰(PTM)在调节许多细胞活动中发挥着内在的作用，包括蛋白质的移位、周转以及与结合伙伴的相互作用。在人类细胞中，200多种PTM的共价连接是由占基因组约5%的专用酶完成的。其中几种酶包括激酶、泛素和小泛素样修饰物(SUMO)酶在癌细胞中调控错误，因此代表了药物发现和癌症研究计划的假定靶点。这些酶的功能与与肿瘤发生相关的表型变化的相关性需要在基因组水平上全面分析PTM，考虑到它们的多样性、化学计量比和在蛋白质结构和细胞提取物中的低分布频率，这是一项艰巨的任务。在这种背景下，质谱仪(MS)已被证明是一种重要的分析工具，可以从复杂的细胞提取物中灵敏而特异地鉴定PTMS。我们的研究项目“用于鉴定PTMS的化学-酶和数据挖掘方法”建立在我们团队在大规模基于MS的蛋白质组学方面的最新进展的基础上，以从亲和力丰富的生物提取物中分析蛋白质修饰。作为这项建议的一部分，我们将开发特定的浓缩和消化策略，以及有针对性的MS检测方法，以识别蛋白质磷酸化和SUMO化；这两种修饰在细胞信号和癌症研究中具有重要意义。开发的工具将应用于癌细胞模型系统的研究，以确定新的底物，并解开由化学刺激剂、激酶抑制剂和已知的与白血病相关的染色体易位调节的相互作用蛋白质网络。更重要的是，该提案中开发的分析工具将更广泛地应用于任何大规模蛋白质组学和药物发现计划，这些计划研究蛋白质-药物相互作用和细胞信号事件，以开发更好的靶向药物，最终改善人类健康。

Post-translational modifications (PTMs) of proteins play an intrinsic role in modulating numerous cellular activities including protein translocation, turnover, and interaction with binding partners. In human cells, the covalent attachment of more than 200 types of PTMs is carried out by dedicated enzymes representing about 5 % of the genome. Several of them including kinases, ubiquitin- and small ubiquitin-like modifier (SUMO) enzymes are misregulated in cancer cells, thus representing putative targets for drug discovery and cancer research programs. The functional correlation of these enzymes with phenotypic changes associated with tumorigenesis requires comprehensive profiling of PTMs at the genomic-scale, a daunting task given their diversity, stoichiometry and low distribution frequency within protein structures and cell extracts. In this context, mass spectrometry (MS) has proven to be an essential analytical tool providing sensitive and specific identification of PTMs from complex cell extracts. Our research program "Chemi-enzymatic and data mining approaches for the identification of PTMs" builds upon recent advances from our group in large-scale quantitative MS-based proteomics to profile protein modifications from affinity-enriched biological extracts. As part of this proposal, we will develop specific enrichment and digestion strategies together with targeted MS detection approaches for the identification of protein phosphorylation and sumoylation; two modifications of significant interest in cell signaling and cancer research. The tools developed will be applied in the study of cancer cell model systems to identify novel substrates and to unravel networks of interacting proteins modulated by chemical stimulants, kinase inhibitors and known chromosomal translocations associated with leukemia. More importantly, analytical tools developed in this proposal will be of broader application to any large-scale proteomics and drug discovery programs investigating protein-drug interactions and cell signaling events for the development of better targeted medicines ultimately improving human health.