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TopLib:构建和搜索自上而下的质谱库以进行蛋白质异构体鉴定。

TopLib: Building and Searching Top-Down Mass Spectral Libraries for Proteoform Identification.

作者信息

Li Kun, Tang Haixu, Liu Xiaowen

机构信息

Deming Department of Medicine, Tulane University, New Orleans, Louisiana 70112, United States.

Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, Indiana 47408, United States.

出版信息

Anal Chem. 2025 Jun 10;97(22):11443-11453. doi: 10.1021/acs.analchem.4c06627. Epub 2025 May 29.

Abstract

Mass spectral library search is a widely used approach for spectral identification in mass spectrometry (MS)-based proteomics. While numerous methods exist for building and searching bottom-up mass spectral libraries, there is a lack of software tools for top-down mass spectral libraries. To fill the gap, we introduce TopLib, a new software package designed for building and searching top-down spectral libraries. TopLib utilizes an efficient spectral representation technique to reduce database size and improve query speed and performance. We systematically evaluated various spectral representation techniques and scoring functions for top-down spectral clustering and search. Our results demonstrate that TopLib is significantly faster and yields higher reproducibility in proteoform identification compared to conventional database search methods in top-down MS.

摘要

质谱库搜索是基于质谱(MS)的蛋白质组学中广泛用于光谱鉴定的方法。虽然存在许多用于构建和搜索自下而上质谱库的方法,但缺乏用于自上而下质谱库的软件工具。为了填补这一空白,我们引入了TopLib,这是一个用于构建和搜索自上而下光谱库的新软件包。TopLib利用一种高效的光谱表示技术来减小数据库大小并提高查询速度和性能。我们系统地评估了用于自上而下光谱聚类和搜索的各种光谱表示技术和评分函数。我们的结果表明,与自上而下质谱中的传统数据库搜索方法相比,TopLib在蛋白质异构体鉴定方面显著更快且具有更高的重现性。

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