• 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

用于快速酶谱分析的下一代化学蛋白质组学工具。

Next generation chemical proteomic tools for rapid enzyme profiling.

作者信息

Uttamchandani Mahesh, Lu Candy H S, Yao Shao Q

机构信息

Defence Medical and Environmental Research Institute, DSO National Laboratories, 27 Medical Drive, Singapore 117510.

出版信息

Acc Chem Res. 2009 Aug 18;42(8):1183-92. doi: 10.1021/ar9000586.

DOI:10.1021/ar9000586
PMID:19435360
Abstract

Sequencing of the human genome provided a wealth of information about the genomic blueprint of a cell. But genes do not tell the entire story of life and living processes; identifying the roles of enzymes and mapping out their interactions is also crucial. Enzymes catalyze virtually every cellular process and metabolic exchange. They not only are instrumental in sustaining life but also are required for its regulation and diversification. Diseases such as cancer can be caused by minor changes in enzyme activities. In addition, the unique enzymes of pathogenic organisms are ripe targets for combating infections. Consequently, nearly one-third of all current drug targets are enzymes. An estimated 18-29% of eukaryotic genes encode enzymes, but only a limited proportion of enzymes have thus far been characterized. Therefore, little is understood about the physiological roles, substrate specificity, and downstream targets of the vast majority of these important proteins. A key step toward the biological characterization of enzymes, as well as their adoption as drug targets, is the development of global solutions that bridge the gap in understanding these proteins and their interactions. We herein present technological advances that facilitate the study of enzymes and their properties in a high-throughput manner. Over the years, our group has introduced and developed a variety of such enabling platforms for many classes of enzymes, including kinases, phosphatases, and proteases. For each of these different types of enzymes, specific design considerations are required to develop the appropriate chemical tools to characterize each class. These tools include activity-based probes and chemical compound libraries, which are rapidly assembled using efficient combinatorial synthesis or "click chemistry" strategies. The resulting molecular assortments may then be screened against the target enzymes in high-throughput using microplates or microarrays. These techniques offer powerful means to study, profile, and discover potent small molecules that can modulate enzyme activity. This Account will describe the concepts involved in designing chemical probes and libraries for comparative enzyme screening and drug discovery applications, as well as highlight how these technologies are changing the way in which enzymes may be rapidly profiled and characterized.

摘要

人类基因组测序为细胞的基因组蓝图提供了丰富信息。但基因并不能讲述生命及生命过程的全部故事;确定酶的作用并描绘它们的相互作用同样至关重要。酶几乎催化了每一个细胞过程和代谢交换。它们不仅对维持生命至关重要,而且对生命的调节和多样化也必不可少。诸如癌症等疾病可能由酶活性的微小变化引起。此外,致病生物的独特酶是对抗感染的理想靶点。因此,目前所有药物靶点中近三分之一是酶。据估计,18 - 29%的真核基因编码酶,但迄今为止只有有限比例的酶得到了表征。因此,对于这些重要蛋白质中的绝大多数,人们对其生理作用、底物特异性和下游靶点了解甚少。酶的生物学表征以及将其用作药物靶点的关键一步是开发能够弥合对这些蛋白质及其相互作用理解差距的全局解决方案。我们在此介绍有助于以高通量方式研究酶及其性质的技术进展。多年来,我们团队为包括激酶、磷酸酶和蛋白酶在内的多种酶类引入并开发了各种此类支持平台。对于每一种不同类型的酶,都需要特定的设计考量来开发合适的化学工具以表征每一类酶。这些工具包括基于活性的探针和化合物库,它们可通过高效的组合合成或“点击化学”策略快速组装而成。然后可以使用微孔板或微阵列对所得分子组合针对目标酶进行高通量筛选。这些技术为研究、分析和发现能够调节酶活性的强效小分子提供了有力手段。本综述将描述设计用于比较酶筛选和药物发现应用的化学探针和库所涉及的概念,并强调这些技术如何改变快速分析和表征酶的方式。

相似文献

1
Next generation chemical proteomic tools for rapid enzyme profiling.用于快速酶谱分析的下一代化学蛋白质组学工具。
Acc Chem Res. 2009 Aug 18;42(8):1183-92. doi: 10.1021/ar9000586.
2
Microarray-based enzyme profiling: Recent advances and applications (Review).基于微阵列的酶谱分析:最新进展及应用(综述)。
Biointerphases. 2010 Sep;5(3):FA24-31. doi: 10.1116/1.3462969.
3
Protein and small molecule microarrays: powerful tools for high-throughput proteomics.蛋白质和小分子微阵列:高通量蛋白质组学的强大工具。
Mol Biosyst. 2006 Jan;2(1):58-68. doi: 10.1039/b513935j. Epub 2005 Nov 25.
4
Recent progress in biomolecular engineering.生物分子工程的最新进展。
Biotechnol Prog. 2000 Jan-Feb;16(1):2-16. doi: 10.1021/bp088059d.
5
The opportunities and challenges of personalized genome-based molecular therapies for cancer: targets, technologies, and molecular chaperones.基于个性化基因组的癌症分子疗法的机遇与挑战:靶点、技术和分子伴侣
Cancer Chemother Pharmacol. 2003 Jul;52 Suppl 1:S45-56. doi: 10.1007/s00280-003-0593-0. Epub 2003 Jun 18.
6
Activity-based proteomics: enzymatic activity profiling in complex proteomes.基于活性的蛋白质组学:复杂蛋白质组中的酶活性分析
Amino Acids. 2006 Jun;30(4):333-50. doi: 10.1007/s00726-006-0305-2. Epub 2006 May 15.
7
Protease proteomics: revealing protease in vivo functions using systems biology approaches.蛋白酶组学:运用系统生物学方法揭示蛋白酶的体内功能
Mol Aspects Med. 2008 Oct;29(5):339-58. doi: 10.1016/j.mam.2008.04.003. Epub 2008 May 1.
8
Application of combinatorial library methods in cancer research and drug discovery.组合文库方法在癌症研究与药物发现中的应用。
Anticancer Drug Des. 1997 Apr;12(3):145-67.
9
Small molecule microarrays: recent advances and applications.小分子微阵列:最新进展与应用
Curr Opin Chem Biol. 2005 Feb;9(1):4-13. doi: 10.1016/j.cbpa.2004.12.005.
10
High-throughput screening of biocatalytic activity: applications in drug discovery.生物催化活性的高通量筛选:在药物发现中的应用
Curr Opin Chem Biol. 2006 Apr;10(2):162-8. doi: 10.1016/j.cbpa.2006.02.033. Epub 2006 Mar 7.

引用本文的文献

1
Recent advances in activity-based probes (ABPs) and affinity-based probes (ABPs) for profiling of enzymes.用于酶谱分析的基于活性的探针(ABP)和基于亲和力的探针(ABP)的最新进展。
Chem Sci. 2021 May 18;12(24):8288-8310. doi: 10.1039/d1sc01359a.
2
Responsive principles and applications of smart materials in biosensing.智能材料在生物传感中的响应原理及应用
Smart Mater Med. 2020;1:54-65. doi: 10.1016/j.smaim.2020.07.001. Epub 2020 Jul 21.
3
Data Analysis Strategies for Protein Microarrays.蛋白质微阵列的数据分析策略
Microarrays (Basel). 2012 Aug 6;1(2):64-83. doi: 10.3390/microarrays1020064.
4
In Vivo Probe of Lipid II-Interacting Proteins.在体探针脂质 II 相互作用蛋白。
Angew Chem Int Ed Engl. 2016 Jul 11;55(29):8401-4. doi: 10.1002/anie.201603441. Epub 2016 May 25.
5
Identification of multiple metabolic enzymes from mice cochleae tissue using a novel functional proteomics technology.使用一种新型功能蛋白质组学技术从小鼠耳蜗组织中鉴定多种代谢酶。
PLoS One. 2015 Mar 26;10(3):e0121826. doi: 10.1371/journal.pone.0121826. eCollection 2015.
6
Prediction of function in protein superfamilies.蛋白质超家族中功能的预测。
F1000 Biol Rep. 2009 Dec 9;1:91. doi: 10.3410/B1-91.