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采用MED-SuMo分类方法分析与HSP90相关的折叠结构。

Analysis of HSP90-related folds with MED-SuMo classification approach.

作者信息

Doppelt-Azeroual Olivia, Moriaud Fabrice, Delfaud François, de Brevern Alexandre G

机构信息

MEDIT SA, 2 rue du Belvédère, Palaiseau, France.

出版信息

Drug Des Devel Ther. 2009 Sep 21;3:59-72. doi: 10.2147/dddt.s4706.

DOI:10.2147/dddt.s4706
PMID:19920922
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2769237/
Abstract

Three-dimensional structural information is critical for understanding functional protein properties and the precise mechanisms of protein functions implicated in physiological and pathological processes. Comparison and detection of protein binding sites are key steps for annotating structures with functional predictions and are extremely valuable steps in a drug design process. In this research area, MED-SuMo is a powerful technology to detect and characterize similar local regions on protein surfaces. Each amino acid residue's potential chemical interactions are represented by specific surface chemical features (SCFs). The MED-SuMo heuristic is based on the representation of binding sites by a graph structure suitable for exploration by an efficient comparison algorithm. We use this approach to analyze one particular SCOP superfamily which includes HSP90 chaperone, MutL/DNA topoisomerase, histidine kinases, and alpha-ketoacid dehydrogenase kinase C (BCK). They share a common fold and a common region for ATP-binding. To analyze both similar and differing features of this fold, we use a novel classification method, the MED-SuMo multi approach (MED-SMA). We highlight common and distinct features of these proteins. The different clusters created by MED-SMA yield interesting observations. For instance, one cluster gathers three types of proteins (HSP90, topoisomerase VI, and BCK) which all bind the drug radicicol.

摘要

三维结构信息对于理解蛋白质的功能特性以及蛋白质在生理和病理过程中发挥功能的精确机制至关重要。蛋白质结合位点的比较和检测是通过功能预测对结构进行注释的关键步骤,也是药物设计过程中极其有价值的步骤。在这个研究领域,MED-SuMo是一种用于检测和表征蛋白质表面相似局部区域的强大技术。每个氨基酸残基的潜在化学相互作用由特定的表面化学特征(SCF)表示。MED-SuMo启发式方法基于通过适合高效比较算法探索的图结构来表示结合位点。我们使用这种方法来分析一个特定的SCOP超家族,其中包括HSP90伴侣蛋白、MutL/DNA拓扑异构酶、组氨酸激酶和α-酮酸脱氢酶激酶C(BCK)。它们具有共同的折叠结构和ATP结合的共同区域。为了分析这种折叠结构的相似和不同特征,我们使用了一种新颖的分类方法,即MED-SuMo多方法(MED-SMA)。我们突出了这些蛋白质的共同和独特特征。MED-SMA创建的不同簇产生了有趣的观察结果。例如,一个簇聚集了三种类型的蛋白质(HSP90、拓扑异构酶VI和BCK),它们都与药物萝卜硫素结合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/d17da54e1e5d/dddt-3-059f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/eef4f1d738f2/dddt-3-059f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/84a9a064806a/dddt-3-059f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/af3182562fd1/dddt-3-059f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/006885ff0d7a/dddt-3-059f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/8ec4a1de381d/dddt-3-059f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/216827e3f4be/dddt-3-059f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/baba3b57cc4c/dddt-3-059f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/d17da54e1e5d/dddt-3-059f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/eef4f1d738f2/dddt-3-059f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/84a9a064806a/dddt-3-059f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/af3182562fd1/dddt-3-059f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/006885ff0d7a/dddt-3-059f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/8ec4a1de381d/dddt-3-059f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/216827e3f4be/dddt-3-059f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/baba3b57cc4c/dddt-3-059f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/2769237/d17da54e1e5d/dddt-3-059f8.jpg

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引用本文的文献

1
Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins.快速、自动化的功能分类方法——MED-SuMo:在嘌呤结合蛋白上的应用。
Protein Sci. 2010 Apr;19(4):847-67. doi: 10.1002/pro.364.

本文引用的文献

1
The Hsp90 inhibitor radicicol interacts with the ATP-binding pocket of bacterial sensor kinase PhoQ.热休克蛋白90(Hsp90)抑制剂萝卜硫素与细菌传感激酶PhoQ的ATP结合口袋相互作用。
J Mol Biol. 2008 May 23;379(1):82-93. doi: 10.1016/j.jmb.2008.03.036. Epub 2008 Mar 26.
2
Protein structure databases with new web services for structural biology and biomedical research.具备面向结构生物学和生物医学研究的新网络服务的蛋白质结构数据库。
Brief Bioinform. 2008 Jul;9(4):276-85. doi: 10.1093/bib/bbn015. Epub 2008 Apr 22.
3
Towards improving compound selection in structure-based virtual screening.
迈向改进基于结构的虚拟筛选中的化合物选择。
Drug Discov Today. 2008 Mar;13(5-6):219-26. doi: 10.1016/j.drudis.2007.12.002. Epub 2008 Feb 4.
4
Structures and diseases.结构与疾病。
Nat Struct Mol Biol. 2008 Feb;15(2):117-20. doi: 10.1038/nsmb0208-117.
5
Structural genomics: from genes to structures with valuable materials and many questions in between.结构基因组学:从基因到结构,其间有宝贵的材料和诸多问题。
Nat Methods. 2008 Feb;5(2):129-32. doi: 10.1038/nmeth0208-129.
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Virtual screening and its integration with modern drug design technologies.虚拟筛选及其与现代药物设计技术的整合。
Curr Med Chem. 2008;15(1):37-46. doi: 10.2174/092986708783330683.
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A novel Hsp90 inhibitor to disrupt Hsp90/Cdc37 complex against pancreatic cancer cells.一种新型热休克蛋白90(Hsp90)抑制剂,可破坏Hsp90/细胞周期蛋白依赖性激酶37(Cdc37)复合物以对抗胰腺癌细胞。
Mol Cancer Ther. 2008 Jan;7(1):162-70. doi: 10.1158/1535-7163.MCT-07-0484.
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The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation.SeqFEATURE 三维功能位点模型库:与现有方法的比较及在蛋白质功能注释中的应用。
Genome Biol. 2008 Jan 16;9(1):R8. doi: 10.1186/gb-2008-9-1-r8.
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Data growth and its impact on the SCOP database: new developments.数据增长及其对SCOP数据库的影响:新进展
Nucleic Acids Res. 2008 Jan;36(Database issue):D419-25. doi: 10.1093/nar/gkm993. Epub 2007 Nov 13.
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Automatic generation of 3D motifs for classification of protein binding sites.用于蛋白质结合位点分类的3D基序自动生成
BMC Bioinformatics. 2007 Aug 30;8:321. doi: 10.1186/1471-2105-8-321.