利用 DEER 光谱建立蛋白质模型。

IF 10.4 1区 生物学 Q1 BIOPHYSICS Annual Review of Biophysics Pub Date : 2024-12-17 DOI:10.1146/annurev-biophys-030524-013431
Maxx H Tessmer, Stefan Stoll
{"title":"利用 DEER 光谱建立蛋白质模型。","authors":"Maxx H Tessmer, Stefan Stoll","doi":"10.1146/annurev-biophys-030524-013431","DOIUrl":null,"url":null,"abstract":"<p><p>Double electron-electron resonance (DEER) combined with site-directed spin labeling can provide distance distributions between selected protein residues to investigate protein structure and conformational heterogeneity. The utilization of the full quantitative information contained in DEER data requires effective protein and spin label modeling methods. Here, we review the application of DEER data to protein modeling. First, we discuss the significance of spin label modeling for accurate extraction of protein structural information and review the most popular label modeling methods. Next, we review several important aspects of protein modeling with DEER, including site selection, how DEER restraints are applied, common artifacts, and the unique potential of DEER data for modeling structural ensembles and conformational landscapes. Finally, we discuss common applications of protein modeling with DEER data and provide an outlook.</p>","PeriodicalId":50756,"journal":{"name":"Annual Review of Biophysics","volume":" ","pages":""},"PeriodicalIF":10.4000,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Protein Modeling with DEER Spectroscopy.\",\"authors\":\"Maxx H Tessmer, Stefan Stoll\",\"doi\":\"10.1146/annurev-biophys-030524-013431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Double electron-electron resonance (DEER) combined with site-directed spin labeling can provide distance distributions between selected protein residues to investigate protein structure and conformational heterogeneity. The utilization of the full quantitative information contained in DEER data requires effective protein and spin label modeling methods. Here, we review the application of DEER data to protein modeling. First, we discuss the significance of spin label modeling for accurate extraction of protein structural information and review the most popular label modeling methods. Next, we review several important aspects of protein modeling with DEER, including site selection, how DEER restraints are applied, common artifacts, and the unique potential of DEER data for modeling structural ensembles and conformational landscapes. Finally, we discuss common applications of protein modeling with DEER data and provide an outlook.</p>\",\"PeriodicalId\":50756,\"journal\":{\"name\":\"Annual Review of Biophysics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":10.4000,\"publicationDate\":\"2024-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Biophysics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-biophys-030524-013431\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Biophysics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1146/annurev-biophys-030524-013431","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 0

摘要

双电子-电子共振(dual electron-electron resonance, DEER)结合定点自旋标记技术可以提供所选蛋白质残基之间的距离分布,从而研究蛋白质的结构和构象异质性。利用DEER数据中包含的全部定量信息需要有效的蛋白质和自旋标签建模方法。本文综述了DEER数据在蛋白质建模中的应用。首先,我们讨论了自旋标签建模对准确提取蛋白质结构信息的意义,并回顾了目前最流行的标签建模方法。接下来,我们回顾了用DEER进行蛋白质建模的几个重要方面,包括位点选择、如何应用DEER约束、常见的人工产物以及DEER数据在结构集成和构象景观建模方面的独特潜力。最后,讨论了利用DEER数据进行蛋白质建模的常见应用,并对其进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Protein Modeling with DEER Spectroscopy.

Double electron-electron resonance (DEER) combined with site-directed spin labeling can provide distance distributions between selected protein residues to investigate protein structure and conformational heterogeneity. The utilization of the full quantitative information contained in DEER data requires effective protein and spin label modeling methods. Here, we review the application of DEER data to protein modeling. First, we discuss the significance of spin label modeling for accurate extraction of protein structural information and review the most popular label modeling methods. Next, we review several important aspects of protein modeling with DEER, including site selection, how DEER restraints are applied, common artifacts, and the unique potential of DEER data for modeling structural ensembles and conformational landscapes. Finally, we discuss common applications of protein modeling with DEER data and provide an outlook.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Annual Review of Biophysics
Annual Review of Biophysics 生物-生物物理
CiteScore
21.00
自引率
0.00%
发文量
25
期刊介绍: The Annual Review of Biophysics, in publication since 1972, covers significant developments in the field of biophysics, including macromolecular structure, function and dynamics, theoretical and computational biophysics, molecular biophysics of the cell, physical systems biology, membrane biophysics, biotechnology, nanotechnology, and emerging techniques.
期刊最新文献
Membrane Association of Intrinsically Disordered Proteins. Molecular Level Super-Resolution Fluorescence Imaging. Toward Principles of Brain Network Organization and Function. Information Processing in Biochemical Networks. Kinetics of Amyloid Oligomer Formation.
×
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