从生物信息学的角度看酶的功能和进化。

IF 4.4 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Biochemical Journal Pub Date : 2023-11-29 DOI:10.1042/BCJ20220405
Antonio J M Ribeiro, Ioannis G Riziotis, Neera Borkakoti, Janet M Thornton
{"title":"从生物信息学的角度看酶的功能和进化。","authors":"Antonio J M Ribeiro, Ioannis G Riziotis, Neera Borkakoti, Janet M Thornton","doi":"10.1042/BCJ20220405","DOIUrl":null,"url":null,"abstract":"<p><p>Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.</p>","PeriodicalId":8825,"journal":{"name":"Biochemical Journal","volume":"480 22","pages":"1845-1863"},"PeriodicalIF":4.4000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10754289/pdf/","citationCount":"0","resultStr":"{\"title\":\"Enzyme function and evolution through the lens of bioinformatics.\",\"authors\":\"Antonio J M Ribeiro, Ioannis G Riziotis, Neera Borkakoti, Janet M Thornton\",\"doi\":\"10.1042/BCJ20220405\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.</p>\",\"PeriodicalId\":8825,\"journal\":{\"name\":\"Biochemical Journal\",\"volume\":\"480 22\",\"pages\":\"1845-1863\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2023-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10754289/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biochemical Journal\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1042/BCJ20220405\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemical Journal","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1042/BCJ20220405","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

经过数十亿年的进化,酶被塑造成催化维持地球生命的化学反应。分散在文献中,或组织在在线数据库中,关于酶的知识可以在不同的维度上进行结构,或者与它们作为生物大分子的质量有关,如它们的序列和结构,或者与它们的化学功能有关,如催化位点、动力学、机制和整体反应。酶的进化只有在考虑到这些维度的时候才能被理解。此外,酶的许多特性只有从进化的角度才有意义。我们首先概述了酶进化的主要范式,包括基因复制和分化、趋同进化和结构域重组进化。在第二部分中,我们概述了目前关于酶的集体知识,根据不同类型的数据组织并收集在几个数据库中。我们还强调了一些日益强大的计算工具,这些工具可用于缩小理解上的差距,特别是对于需要费力的实验协议的数据类型。我们相信,蛋白质结构预测的最新进展将成为预测结合、机制和最终化学反应的强大催化剂。在不久的将来,酶的功能和进化的全面绘图可能是可以实现的。
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
Enzyme function and evolution through the lens of bioinformatics.

Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.

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
Biochemical Journal
Biochemical Journal 生物-生化与分子生物学
CiteScore
8.00
自引率
0.00%
发文量
255
审稿时长
1 months
期刊介绍: Exploring the molecular mechanisms that underpin key biological processes, the Biochemical Journal is a leading bioscience journal publishing high-impact scientific research papers and reviews on the latest advances and new mechanistic concepts in the fields of biochemistry, cellular biosciences and molecular biology. The Journal and its Editorial Board are committed to publishing work that provides a significant advance to current understanding or mechanistic insights; studies that go beyond observational work using in vitro and/or in vivo approaches are welcomed. Painless publishing: All papers undergo a rigorous peer review process; however, the Editorial Board is committed to ensuring that, if revisions are recommended, extra experiments not necessary to the paper will not be asked for. Areas covered in the journal include: Cell biology Chemical biology Energy processes Gene expression and regulation Mechanisms of disease Metabolism Molecular structure and function Plant biology Signalling
期刊最新文献
Divergent roles of DRY and NPxxY motifs in selective activation of downstream signalling by the apelin receptor. Sequence variation in the active site of mobile colistin resistance proteins is evolutionarily accommodated through inter-domain interactions. The uncharacterized protein ZNF200 interacts with PRMT3 and aids its stability and nuclear translocation. Mitigating neuroinflammation in cognitive areas: exploring the impact of HMG-CoA reductase inhibitor. Pyroptotic executioner pore-forming protein gasdermin D forms oligomeric assembly and exhibits amyloid-like attributes that could contribute for its pore-forming function.
×
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