Protein Structure Classification

N. Dawson, Sayoni Das, J. Lees, C. Orengo
{"title":"Protein Structure Classification","authors":"N. Dawson, Sayoni Das, J. Lees, C. Orengo","doi":"10.1002/9780470015902.A0003033.PUB3","DOIUrl":null,"url":null,"abstract":"To understand and map the universe of protein structures, it is necessary to collate, annotate and classify these structures in a rational scheme. While the individual protein structures reveal much about the specific molecular mechanisms that underlie a particular biological function, taken together this body of data also allows biologists to explore the evolution of structure and function. As structure is much better conserved than sequence, these data also facilitate the recognition of evolutionary relationships that are hidden at the sequence level. The different approaches that have been taken to tackle this problem include the identification of protein domains, phylogenetic and phenetic classification and hierarchical and nearest-neighbour clustering. Powerful sequence searching methods then enable structural assignments to be allocated to genomic data. \n \n \n \nKey Concepts \n \nProteins comprise recognisable smaller sequence domains. \nDomains usually consist of secondary and supersecondary structures and have an average size of 150 ± 50 residues. \nThese domains may be thought of as units of evolution, which recur in many proteins in various combinations. \nStructural classifications have been developed that group domains into fold and sequence families. \nThe phenetic approach groups the proteins according to their structural characteristics. \nThe phylogenetic approach groups proteins into families according to their evolutionary history. \n \n \n \n \nKeywords: \n \nprotein structure classification; \ncommon folds; \nprotein architecture; \nstructural comparison; \ngenomes","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Encyclopedia of Bioinformatics and Computational Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/9780470015902.A0003033.PUB3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

To understand and map the universe of protein structures, it is necessary to collate, annotate and classify these structures in a rational scheme. While the individual protein structures reveal much about the specific molecular mechanisms that underlie a particular biological function, taken together this body of data also allows biologists to explore the evolution of structure and function. As structure is much better conserved than sequence, these data also facilitate the recognition of evolutionary relationships that are hidden at the sequence level. The different approaches that have been taken to tackle this problem include the identification of protein domains, phylogenetic and phenetic classification and hierarchical and nearest-neighbour clustering. Powerful sequence searching methods then enable structural assignments to be allocated to genomic data. Key Concepts Proteins comprise recognisable smaller sequence domains. Domains usually consist of secondary and supersecondary structures and have an average size of 150 ± 50 residues. These domains may be thought of as units of evolution, which recur in many proteins in various combinations. Structural classifications have been developed that group domains into fold and sequence families. The phenetic approach groups the proteins according to their structural characteristics. The phylogenetic approach groups proteins into families according to their evolutionary history. Keywords: protein structure classification; common folds; protein architecture; structural comparison; genomes
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
蛋白质结构分类
为了了解和绘制蛋白质结构的图谱,有必要以合理的方案对这些结构进行整理、注释和分类。虽然单个蛋白质结构揭示了许多关于特定生物功能基础的特定分子机制,但综合这些数据也使生物学家能够探索结构和功能的进化。由于结构比序列保守得多,这些数据也有助于识别隐藏在序列水平上的进化关系。解决这一问题的不同方法包括蛋白质结构域的鉴定、系统发育和表型分类以及分层和近邻聚类。然后,强大的序列搜索方法使结构分配能够分配给基因组数据。关键概念蛋白质由可识别的较小序列结构域组成。结构域通常由二级和超二级结构组成,平均大小为150±50个残基。这些结构域可以被认为是进化的单位,它们以不同的组合在许多蛋白质中重复出现。结构分类已经发展到将结构域分为折叠族和序列族。表型法根据蛋白质的结构特征对它们进行分组。系统发育方法根据蛋白质的进化史将它们分成家族。关键词:蛋白质结构分类;常见的折叠;蛋白质结构;结构比较;基因组
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
自引率
0.00%
发文量
0
期刊最新文献
Evolutionary Models Intelligent Agents: Multi-Agent Systems Intelligent Agents and Environment Measurements of Accuracy in Biostatistics Vaccine Target Discovery
×
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