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J Comput Chem. 2011 Apr 15;32(5):866-77. doi: 10.1002/jcc.21666. Epub 2010 Oct 14.
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Bayesian modeling of the yeast SH3 domain interactome predicts spatiotemporal dynamics of endocytosis proteins.贝叶斯模型的酵母 SH3 结构域互作组预测了内吞作用蛋白的时空动力学。
PLoS Biol. 2009 Oct;7(10):e1000218. doi: 10.1371/journal.pbio.1000218. Epub 2009 Oct 20.
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Using genome-wide measurements for computational prediction of SH2-peptide interactions.利用全基因组测量进行SH2-肽相互作用的计算预测。
Nucleic Acids Res. 2009 Aug;37(14):4629-41. doi: 10.1093/nar/gkp394. Epub 2009 Jun 5.
6
Characterization of domain-peptide interaction interface: a generic structure-based model to decipher the binding specificity of SH3 domains.结构域-肽相互作用界面的表征:一种基于通用结构的模型,用于解读SH3结构域的结合特异性
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Characterization of domain-peptide interaction interface: a case study on the amphiphysin-1 SH3 domain.结构域-肽相互作用界面的表征:以发动蛋白-1 SH3结构域为例的研究
J Mol Biol. 2008 Feb 29;376(4):1201-14. doi: 10.1016/j.jmb.2007.12.054. Epub 2008 Jan 3.
10
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鉴定结构域-肽相互作用界面:通过通用基于结构的模型预测酵母中 SH3 结构域介导的蛋白质-蛋白质相互作用网络。

Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein-protein interaction network in yeast by generic structure-based models.

机构信息

Institute of Functional Nano & Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, China.

出版信息

J Proteome Res. 2012 May 4;11(5):2982-95. doi: 10.1021/pr3000688. Epub 2012 Apr 9.

DOI:10.1021/pr3000688
PMID:22468754
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3345086/
Abstract

Determination of the binding specificity of SH3 domain, a peptide recognition module (PRM), is important to understand their biological functions and reconstruct the SH3-mediated protein-protein interaction network. In the present study, the SH3-peptide interactions for both class I and II SH3 domains were characterized by the intermolecular residue-residue interaction network. We developed generic MIEC-SVM models to infer SH3 domain-peptide recognition specificity that achieved satisfactory prediction accuracy. By investigating the domain-peptide recognition mechanisms at the residue level, we found that the class-I and class-II binding peptides have different binding modes even though they occupy the same binding site of SH3. Furthermore, we predicted the potential binding partners of SH3 domains in the yeast proteome and constructed the SH3-mediated protein-protein interaction network. Comparison with the experimentally determined interactions confirmed the effectiveness of our approach. This study showed that our sophisticated computational approach not only provides a powerful platform to decipher protein recognition code at the molecular level but also allows identification of peptide-mediated protein interactions at a proteomic scale. We believe that such an approach is general to be applicable to other domain-peptide interactions.

摘要

确定 SH3 结构域(一种肽识别模块(PRM))的结合特异性对于理解其生物学功能和重建 SH3 介导的蛋白质-蛋白质相互作用网络非常重要。在本研究中,通过分子间残基-残基相互作用网络来表征 I 类和 II 类 SH3 结构域的 SH3-肽相互作用。我们开发了通用的 MIEC-SVM 模型来推断 SH3 结构域-肽识别特异性,该模型达到了令人满意的预测准确性。通过在残基水平上研究结构域-肽识别机制,我们发现尽管结合肽占据了 SH3 的相同结合位点,但 I 类和 II 类结合肽具有不同的结合模式。此外,我们预测了酵母蛋白质组中 SH3 结构域的潜在结合伙伴,并构建了 SH3 介导的蛋白质-蛋白质相互作用网络。与实验确定的相互作用的比较证实了我们方法的有效性。这项研究表明,我们复杂的计算方法不仅提供了一个强大的平台来在分子水平上破译蛋白质识别密码,还允许在蛋白质组学尺度上识别肽介导的蛋白质相互作用。我们相信这种方法是通用的,可以应用于其他结构域-肽相互作用。