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

蛋白质的翻译后修饰（PTMs）在调节许多细胞活动中起内在作用，包括蛋白质易位、周转以及与结合伴侣的相互作用。在人类细胞中，超过200种类型的PTM的共价连接通过代表约5%基因组的专用酶进行。其中几种包括激酶，泛素和小泛素样修饰物（SUMO）酶在癌细胞中被错误调节，因此代表了药物发现和癌症研究计划的假定靶点。这些酶与肿瘤发生相关的表型变化的功能相关性需要在基因组规模上对PTM进行全面分析，这是一项艰巨的任务，因为它们在蛋白质结构和细胞提取物中的多样性、化学计量和低分布频率。在这种情况下，质谱法（MS）已被证明是一个重要的分析工具，提供敏感和特异性的鉴定复杂的细胞提取物的PTM。我们的研究项目“用于鉴定PTM的化学-酶促和数据挖掘方法”建立在我们小组在大规模定量MS蛋白质组学方面的最新进展之上，以从亲和富集的生物提取物中分析蛋白质修饰。作为该提案的一部分，我们将开发特定的富集和消化策略以及靶向MS检测方法，用于鉴定蛋白质磷酸化和sumoylation;这两种修饰在细胞信号传导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的网络。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的蛋白质组学和药物发现计划，研究蛋白质-药物相互作用和细胞信号传导事件，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.