注释
鉴定(生物学)
序列(生物学)
计算机科学
软件
序列数据库
计算生物学
数据库搜索引擎
数据库
情报检索
数据挖掘
生物
人工智能
搜索引擎
遗传学
基因
程序设计语言
植物
作者
Yuling Dai,Robert J. Millikin,Zach Rolfs,Michael R. Shortreed,Lloyd M. Smith
标识
DOI:10.1021/acs.jproteome.2c00305
摘要
Tandem mass spectrometry (MS/MS) is widely employed for the analysis of complex proteomic samples. While protein sequence database searching and spectral library searching are both well-established peptide identification methods, each has shortcomings. Protein sequence databases lack fragment peak intensity information, which can result in poor discrimination between correct and incorrect spectrum assignments. Spectral libraries usually contain fewer peptides than protein sequence databases, which limits the number of peptides that can be identified. Notably, few post-translationally modified peptides are represented in spectral libraries. This is because few search engines can both identify a broad spectrum of PTMs and create corresponding spectral libraries. Also, programs that generate spectral libraries using deep learning approaches are not yet able to accurately predict spectra for the vast majority of PTMs. Here, we address these limitations through use of a hybrid search strategy that combines protein sequence database and spectral library searches to improve identification success rates and sensitivity. This software uses Global PTM Discovery (G-PTM-D) to produce spectral libraries for a wide variety of different PTMs. These features, along with a new spectrum annotation and visualization tool, have been integrated into the freely available and open-source search engine MetaMorpheus.
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