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通过小分子配体结合来表征蛋白质结构域关联

Characterizing protein domain associations by Small-molecule ligand binding.

作者信息

Li Qingliang, Cheng Tiejun, Wang Yanli, Bryant Stephen H

机构信息

National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA.

出版信息

J Proteome Sci Comput Biol. 2012 Dec 3;1. doi: 10.7243/2050-2273-1-6.

Abstract

BACKGROUND

Protein domains are evolutionarily conserved building blocks for protein structure and function, which are conventionally identified based on protein sequence or structure similarity. Small molecule binding domains are of great importance for the recognition of small molecules in biological systems and drug development. Many small molecules, including drugs, have been increasingly identified to bind to multiple targets, leading to promiscuous interactions with protein domains. Thus, a large scale characterization of the protein domains and their associations with respect to small-molecule binding is of particular interest to system biology research, drug target identification, as well as drug repurposing.

METHODS

We compiled a collection of 13,822 physical interactions of small molecules and protein domains derived from the Protein Data Bank (PDB) structures. Based on the chemical similarity of these small molecules, we characterized pairwise associations of the protein domains and further investigated their global associations from a network point of view.

RESULTS

We found that protein domains, despite lack of similarity in sequence and structure, were comprehensively associated through binding the same or similar small-molecule ligands. Moreover, we identified modules in the domain network that consisted of closely related protein domains by sharing similar biochemical mechanisms, being involved in relevant biological pathways, or being regulated by the same cognate cofactors.

CONCLUSIONS

A novel protein domain relationship was identified in the context of small-molecule binding, which is complementary to those identified by traditional sequence-based or structure-based approaches. The protein domain network constructed in the present study provides a novel perspective for chemogenomic study and network pharmacology, as well as target identification for drug repurposing.

摘要

背景

蛋白质结构域是蛋白质结构和功能在进化上保守的构建模块,传统上是根据蛋白质序列或结构相似性来识别的。小分子结合结构域对于生物系统中小分子的识别和药物开发非常重要。越来越多的小分子,包括药物,被发现可与多个靶点结合,从而导致与蛋白质结构域的混杂相互作用。因此,大规模表征蛋白质结构域及其与小分子结合的关联对于系统生物学研究、药物靶点识别以及药物再利用尤为重要。

方法

我们整理了一份来自蛋白质数据库(PDB)结构的13822个小分子与蛋白质结构域的物理相互作用集合。基于这些小分子的化学相似性,我们表征了蛋白质结构域的成对关联,并从网络角度进一步研究了它们的全局关联。

结果

我们发现,尽管蛋白质结构域在序列和结构上缺乏相似性,但它们通过结合相同或相似的小分子配体而全面关联。此外,我们在结构域网络中识别出了模块,这些模块由密切相关的蛋白质结构域组成,它们共享相似的生化机制,参与相关生物途径,或受相同的同源辅因子调控。

结论

在小分子结合的背景下识别出了一种新的蛋白质结构域关系,这与传统的基于序列或基于结构的方法所识别的关系互补。本研究构建的蛋白质结构域网络为化学基因组学研究和网络药理学以及药物再利用的靶点识别提供了新的视角。

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本文引用的文献

1
Predicting drug targets based on protein domains.基于蛋白质结构域预测药物靶点。
Mol Biosyst. 2012 Apr;8(5):1528-34. doi: 10.1039/c2mb05450g. Epub 2012 Mar 8.
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Global analysis of small molecule binding to related protein targets.小分子与相关蛋白靶标的全球分析。
PLoS Comput Biol. 2012 Jan;8(1):e1002333. doi: 10.1371/journal.pcbi.1002333. Epub 2012 Jan 12.
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Nucleic Acids Res. 2010 Jan;38(Database issue):D211-22. doi: 10.1093/nar/gkp985. Epub 2009 Nov 17.

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