Proteome-scale structural prediction of the giant Marseillevirus reveals conserved folds and putative homologs of the hypothetical proteins

IF 2.5 4区 医学 Q3 VIROLOGY
Tanvi Aggarwal, Kiran Kondabagil
{"title":"Proteome-scale structural prediction of the giant Marseillevirus reveals conserved folds and putative homologs of the hypothetical proteins","authors":"Tanvi Aggarwal,&nbsp;Kiran Kondabagil","doi":"10.1007/s00705-024-06155-8","DOIUrl":null,"url":null,"abstract":"<div><p>A significant proportion of the highly divergent and novel proteins of giant viruses are termed “hypothetical” due to the absence of detectable homologous sequences in the existing databases. The quality of genome and proteome annotations often relies on the identification of signature sequences and motifs in order to assign putative functions to the gene products. These annotations serve as the first set of information for researchers to develop workable hypotheses for further experimental research. The structure-function relationship of proteins suggests that proteins with similar functions may also exhibit similar folding patterns. Here, we report the first proteome-wide structure prediction of the giant Marseillevirus. We use AlphaFold-predicted structures and their comparative analysis with the experimental structures in the PDB database to preliminarily annotate the viral proteins. Our work highlights the conservation of structural folds in proteins with highly divergent sequences and reveals potentially paralogous relationships among them. We also provide evidence for gene duplication and fusion as contributing factors to giant viral genome expansion and evolution. With the easily accessible AlphaFold and other advanced bioinformatics tools for high-confidence <i>de novo</i> structure prediction, we propose a combined sequence and predicted-structure-based proteome annotation approach for the initial characterization of novel and complex organisms or viruses.</p></div>","PeriodicalId":8359,"journal":{"name":"Archives of Virology","volume":"169 11","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Virology","FirstCategoryId":"3","ListUrlMain":"https://link.springer.com/article/10.1007/s00705-024-06155-8","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"VIROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

A significant proportion of the highly divergent and novel proteins of giant viruses are termed “hypothetical” due to the absence of detectable homologous sequences in the existing databases. The quality of genome and proteome annotations often relies on the identification of signature sequences and motifs in order to assign putative functions to the gene products. These annotations serve as the first set of information for researchers to develop workable hypotheses for further experimental research. The structure-function relationship of proteins suggests that proteins with similar functions may also exhibit similar folding patterns. Here, we report the first proteome-wide structure prediction of the giant Marseillevirus. We use AlphaFold-predicted structures and their comparative analysis with the experimental structures in the PDB database to preliminarily annotate the viral proteins. Our work highlights the conservation of structural folds in proteins with highly divergent sequences and reveals potentially paralogous relationships among them. We also provide evidence for gene duplication and fusion as contributing factors to giant viral genome expansion and evolution. With the easily accessible AlphaFold and other advanced bioinformatics tools for high-confidence de novo structure prediction, we propose a combined sequence and predicted-structure-based proteome annotation approach for the initial characterization of novel and complex organisms or viruses.

Abstract Image

巨型马赛病毒的蛋白质组尺度结构预测揭示了假定蛋白的保守褶皱和假定同源物
由于现有数据库中没有可检测到的同源序列,巨型病毒中很大一部分高度分化的新型蛋白质被称为 "假说"。基因组和蛋白质组注释的质量往往依赖于特征序列和主题的识别,以便为基因产物分配推定功能。这些注释是研究人员为进一步实验研究提出可行假设的第一套信息。蛋白质的结构-功能关系表明,具有相似功能的蛋白质也可能表现出相似的折叠模式。在此,我们首次报告了巨型马赛病毒的全蛋白质组结构预测。我们利用 AlphaFold 预测的结构及其与 PDB 数据库中实验结构的对比分析,对病毒蛋白质进行了初步注释。我们的工作凸显了具有高度差异序列的蛋白质的结构褶皱保护,并揭示了它们之间潜在的旁系关系。我们还提供了基因复制和融合作为巨型病毒基因组扩展和进化的促成因素的证据。利用易于获取的 AlphaFold 和其他先进的生物信息学工具进行高置信度的全新结构预测,我们提出了一种基于序列和预测结构的蛋白质组注释方法,用于初步鉴定新型复杂生物或病毒的特征。
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 求助全文
来源期刊
Archives of Virology
Archives of Virology 医学-病毒学
CiteScore
5.10
自引率
7.40%
发文量
324
审稿时长
4.5 months
期刊介绍: Archives of Virology publishes original contributions from all branches of research on viruses, virus-like agents, and virus infections of humans, animals, plants, insects, and bacteria. Coverage spans a broad spectrum of topics, from descriptions of newly discovered viruses, to studies of virus structure, composition, and genetics, to studies of virus interactions with host cells, organisms and populations. Studies employ molecular biologic, molecular genetics, and current immunologic and epidemiologic approaches. Contents include studies on the molecular pathogenesis, pathophysiology, and genetics of virus infections in individual hosts, and studies on the molecular epidemiology of virus infections in populations. Also included are studies involving applied research such as diagnostic technology development, monoclonal antibody panel development, vaccine development, and antiviral drug development.Archives of Virology wishes to publish obituaries of recently deceased well-known virologists and leading figures in virology.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信