• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

按酶的国际分类编号(EC编号)分类的酶及其活性位点的序列和结构特征

Sequence and structural features of enzymes and their active sites by EC class.

作者信息

Bray Tracey, Doig Andrew J, Warwicker Jim

机构信息

Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK.

出版信息

J Mol Biol. 2009 Mar 13;386(5):1423-36. doi: 10.1016/j.jmb.2008.11.057. Epub 2008 Dec 10.

DOI:10.1016/j.jmb.2008.11.057
PMID:19100748
Abstract

We have analysed a non-redundant set of 294 enzymes for differences in sequence and structural features between the six main Enzyme Commission (EC) classification groups. This systematic study of enzymes, and their active sites in particular, aims to increase understanding of how the structure of an enzyme relates to its functional role. Many features showed significant differences between the EC classes, including active-site polarity, enzyme size and active-site amino acid propensities. Many attributes correlate with each other to form clusters of related features from which we chose representative features for further analysis. Oxidoreductases have more non-polar active sites, which can be attributed to cofactor binding and a preference for Glu over Asp in active sites in comparison to the other classes. Lyases form a significantly higher proportion of oligomers than any other class, whilst the hydrolases form the largest proportion of monomers. These features were then used in a prediction model that classified each enzyme into its top EC class with an accuracy of 33.1%, which is an increase of 16.4% over random classification. Understanding the link between structure and function is critical to improving enzyme design and the prediction of protein function from structure without transfer of annotation from alignments.

摘要

我们分析了一组294种非冗余酶,以研究六大主要酶委员会(EC)分类组之间在序列和结构特征上的差异。这项对酶,尤其是其活性位点的系统研究,旨在增进对酶的结构与其功能作用之间关系的理解。许多特征在EC分类之间表现出显著差异,包括活性位点极性、酶大小和活性位点氨基酸倾向。许多属性相互关联,形成相关特征簇,我们从中选择代表性特征进行进一步分析。氧化还原酶具有更多的非极性活性位点,这可归因于辅因子结合以及与其他类别相比,活性位点中对谷氨酸的偏好超过天冬氨酸。裂合酶形成寡聚体的比例明显高于任何其他类别,而水解酶形成单体的比例最大。然后,这些特征被用于一个预测模型,该模型将每种酶分类到其最高的EC类别,准确率为33.1%,比随机分类提高了16.4%。理解结构与功能之间的联系对于改进酶设计以及从结构预测蛋白质功能而不通过比对转移注释至关重要。

相似文献

1
Sequence and structural features of enzymes and their active sites by EC class.按酶的国际分类编号(EC编号)分类的酶及其活性位点的序列和结构特征
J Mol Biol. 2009 Mar 13;386(5):1423-36. doi: 10.1016/j.jmb.2008.11.057. Epub 2008 Dec 10.
2
Using GO-PseAA predictor to predict enzyme sub-class.使用GO-PseAA预测器预测酶的亚类。
Biochem Biophys Res Commun. 2004 Dec 10;325(2):506-9. doi: 10.1016/j.bbrc.2004.10.058.
3
Predicting enzyme class from protein structure without alignments.无需比对即可从蛋白质结构预测酶的类别。
J Mol Biol. 2005 Jan 7;345(1):187-99. doi: 10.1016/j.jmb.2004.10.024.
4
Predicting enzyme family classes by hybridizing gene product composition and pseudo-amino acid composition.通过杂交基因产物组成和伪氨基酸组成预测酶家族类别。
J Theor Biol. 2005 May 7;234(1):145-9. doi: 10.1016/j.jtbi.2004.11.017. Epub 2005 Jan 26.
5
Relationship between global structural parameters and Enzyme Commission hierarchy: implications for function prediction.全局结构参数与酶委员会层级的关系:对功能预测的启示。
Comput Biol Chem. 2012 Oct;40:15-9. doi: 10.1016/j.compbiolchem.2012.06.003. Epub 2012 Aug 14.
6
Efficiency analysis of KNN and minimum distance-based classifiers in enzyme family prediction.基于 KNN 和最小距离的分类器在酶家族预测中的效率分析。
Comput Biol Chem. 2009 Dec;33(6):461-4. doi: 10.1016/j.compbiolchem.2009.09.002. Epub 2009 Sep 28.
7
Prediction of enzyme classes from 3D structure: a general model and examples of experimental-theoretic scoring of peptide mass fingerprints of Leishmania proteins.从三维结构预测酶类别:利什曼原虫蛋白质肽质量指纹图谱的通用模型及实验-理论评分示例
J Proteome Res. 2009 Sep;8(9):4372-82. doi: 10.1021/pr9003163.
8
[Structure and function of enzymes].
Z Ernahrungswiss Suppl. 1969;8:5-32.
9
Understanding nature's catalytic toolkit.了解大自然的催化工具包。
Trends Biochem Sci. 2005 Nov;30(11):622-9. doi: 10.1016/j.tibs.2005.09.006. Epub 2005 Oct 7.
10
Relationships between functional subclasses and information contained in active-site and ligand-binding residues in diverse superfamilies.不同超家族中功能亚类与活性位点和配体结合残基中所包含信息之间的关系。
Proteins. 2010 Aug 1;78(10):2369-84. doi: 10.1002/prot.22750.

引用本文的文献

1
Evaluating Functional Annotations of Enzymes Using the Gene Ontology.使用基因本体论评估酶的功能注释
Methods Mol Biol. 2017;1446:111-132. doi: 10.1007/978-1-4939-3743-1_9.
2
Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering.利用数据整合和谱聚类检测同功能蛋白亚家族
PLoS Comput Biol. 2016 Jun 27;12(6):e1005001. doi: 10.1371/journal.pcbi.1005001. eCollection 2016 Jun.
3
Exploring the biological and chemical complexity of the ligases.探索连接酶的生物和化学复杂性。
J Mol Biol. 2014 May 15;426(10):2098-111. doi: 10.1016/j.jmb.2014.03.008. Epub 2014 Mar 21.
4
Prediction of detailed enzyme functions and identification of specificity determining residues by random forests.通过随机森林预测详细的酶功能和鉴定特异性决定残基。
PLoS One. 2014 Jan 8;9(1):e84623. doi: 10.1371/journal.pone.0084623. eCollection 2014.
5
Is EC class predictable from reaction mechanism?从反应机制上能否预测 EC 类?
BMC Bioinformatics. 2012 Apr 24;13:60. doi: 10.1186/1471-2105-13-60.
6
Computational Approaches for Automated Classification of Enzyme Sequences.酶序列自动分类的计算方法
J Proteomics Bioinform. 2011 Aug 23;4:147-152. doi: 10.4172/jpb.1000183.
7
SitesIdentify: a protein functional site prediction tool.SitesIdentify:一种蛋白质功能位点预测工具。
BMC Bioinformatics. 2009 Nov 18;10:379. doi: 10.1186/1471-2105-10-379.
8
Evidence for the adaptation of protein pH-dependence to subcellular pH.证明蛋白质 pH 依赖性适应亚细胞 pH。
BMC Biol. 2009 Oct 22;7:69. doi: 10.1186/1741-7007-7-69.