在MS/MS频谱中检测转化后修饰的诊断特征
Daniel J Geiszler1, Daniel A Polasky2, Fengchao Yu2
1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Nature communications
|July 12, 2023
概括
本研究引入了一种自动化方法,用于识别任何翻译后修饰 (PTM) 的独特光谱特征. 这提高了在基于质谱的蛋白质组学中检测和定位改性的性能.
科学领域:
- 蛋白质组学是指蛋白质组学.
- 质谱测量质量谱测量
- 后翻译修改 后翻译修改
背景情况:
- 翻译后修改 (PTM) 在生物过程中至关重要.
- 在基于质谱的蛋白质组学中检测PTM是具有挑战性的,因为复杂的碎片化模式.
- 现有的方法难以可靠地识别和定位改性.
研究的目的:
- 开发一种全自动化方法,用于识别任何PTM的诊断光谱特征.
- 在蛋白质组学数据中增强修饰的恢复和局部化.
- 为了提高基于质谱的PTM分析的准确性.
主要方法:
- 开发了一种自动化的计算方法,以找到PTM的诊断光谱特征.
- 将这些功能纳入蛋白质组学搜索引擎.
- 分析了各种修饰的碎片化模式,包括使用化学蛋白质组探针,RNA交叉链,酸和ADP-ribosylation的碎片化模式.
- 研究了诊断离子强度和统计性质之间的关系.
主要成果:
- 成功确定了各种PTM的诊断光谱特征.
- 证明改进了对修饰的检测和定位.
- 在多个具有挑战性的PTM实例中验证了该方法.
- 将该方法集成到PTM-Shepherd工具和FragPipe平台中.
结论:
- 自动化方法有效地识别了PTM特定的光谱特征.
- 这种方法显著增强了蛋白质组学中修饰的检测和定位.
- 开发的工具 (PTM-Shepherd,FragPipe) 为PTM分析提供了一个强大的解决方案.
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