Computational Tools for Hydrogen–Deuterium Exchange Mass Spectrometry Data Analysis

IF 51.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Chemical Reviews Pub Date : 2024-10-31 DOI:10.1021/acs.chemrev.4c0043810.1021/acs.chemrev.4c00438
Michele Stofella, Antonio Grimaldi, Jochem H. Smit, Jürgen Claesen, Emanuele Paci* and Frank Sobott*, 
{"title":"Computational Tools for Hydrogen–Deuterium Exchange Mass Spectrometry Data Analysis","authors":"Michele Stofella,&nbsp;Antonio Grimaldi,&nbsp;Jochem H. Smit,&nbsp;Jürgen Claesen,&nbsp;Emanuele Paci* and Frank Sobott*,&nbsp;","doi":"10.1021/acs.chemrev.4c0043810.1021/acs.chemrev.4c00438","DOIUrl":null,"url":null,"abstract":"<p >Hydrogen–deuterium exchange (HDX) has become a pivotal method for investigating the structural and dynamic properties of proteins. The versatility and sensitivity of mass spectrometry (MS) made the technique the ideal companion for HDX, and today HDX-MS is addressing a growing number of applications in both academic research and industrial settings. The prolific generation of experimental data has spurred the concurrent development of numerous computational tools, designed to automate parts of the workflow while employing different strategies to achieve common objectives. Various computational methods are available to perform automated peptide searches and identification; different statistical tests have been implemented to quantify differences in the exchange pattern between two or more experimental conditions; alternative strategies have been developed to deconvolve and analyze peptides showing multimodal behavior; and different algorithms have been proposed to computationally increase the resolution of HDX-MS data, with the ultimate aim to provide information at the level of the single residue. This review delves into a comprehensive examination of the merits and drawbacks associated with the diverse strategies implemented by software tools for the analysis of HDX-MS data.</p>","PeriodicalId":32,"journal":{"name":"Chemical Reviews","volume":"124 21","pages":"12242–12263 12242–12263"},"PeriodicalIF":51.4000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.chemrev.4c00438","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemical Reviews","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.chemrev.4c00438","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Hydrogen–deuterium exchange (HDX) has become a pivotal method for investigating the structural and dynamic properties of proteins. The versatility and sensitivity of mass spectrometry (MS) made the technique the ideal companion for HDX, and today HDX-MS is addressing a growing number of applications in both academic research and industrial settings. The prolific generation of experimental data has spurred the concurrent development of numerous computational tools, designed to automate parts of the workflow while employing different strategies to achieve common objectives. Various computational methods are available to perform automated peptide searches and identification; different statistical tests have been implemented to quantify differences in the exchange pattern between two or more experimental conditions; alternative strategies have been developed to deconvolve and analyze peptides showing multimodal behavior; and different algorithms have been proposed to computationally increase the resolution of HDX-MS data, with the ultimate aim to provide information at the level of the single residue. This review delves into a comprehensive examination of the merits and drawbacks associated with the diverse strategies implemented by software tools for the analysis of HDX-MS data.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
氢氘交换质谱数据分析计算工具
氢氘交换(HDX)已成为研究蛋白质结构和动态特性的重要方法。质谱(MS)的多功能性和灵敏度使其成为 HDX 的理想伴侣,如今,HDX-MS 在学术研究和工业领域的应用日益增多。大量实验数据的产生促进了众多计算工具的同步发展,这些工具旨在自动化部分工作流程,同时采用不同的策略来实现共同的目标。目前有多种计算方法可用于肽的自动搜索和鉴定;不同的统计检验方法可用于量化两种或多种实验条件下交换模式的差异;另有多种策略可用于对表现出多模式行为的肽进行解卷积和分析;还有不同的算法可用于通过计算提高 HDX-MS 数据的分辨率,最终目的是提供单个残基水平的信息。这篇综述全面探讨了用于分析 HDX-MS 数据的软件工具所采用的各种策略的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Chemical Reviews
Chemical Reviews 化学-化学综合
CiteScore
106.00
自引率
1.10%
发文量
278
审稿时长
4.3 months
期刊介绍: Chemical Reviews is a highly regarded and highest-ranked journal covering the general topic of chemistry. Its mission is to provide comprehensive, authoritative, critical, and readable reviews of important recent research in organic, inorganic, physical, analytical, theoretical, and biological chemistry. Since 1985, Chemical Reviews has also published periodic thematic issues that focus on a single theme or direction of emerging research.
期刊最新文献
Toward Efficient Utilization of Photogenerated Charge Carriers in Photoelectrochemical Systems: Engineering Strategies from the Atomic Level to Configuration The Analysis of Electron Densities: From Basics to Emergent Applications Tackling Undruggable Targets with Designer Peptidomimetics and Synthetic Biologics Noncanonical Amino Acid Incorporation in Animals and Animal Cells. Issue Editorial Masthead
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1