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首页> 外文期刊>Journal of Molecular Biology >Using Orthologous and Paralogous Proteins to Identify Specificity-determining Residues in Bacterial Transcription Factors.
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Using Orthologous and Paralogous Proteins to Identify Specificity-determining Residues in Bacterial Transcription Factors.

机译:使用直系同源和旁系同源蛋白鉴定细菌转录因子中确定特异性的残基。

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Concepts of orthology and paralogy are become increasingly important as whole-genome comparison allows their identification in complete genomes. Functional specificity of proteins is assumed to be conserved among orthologs and is different among paralogs. We used this assumption to identify residues which determine specificity of protein-DNA and protein-ligand recognition. Finding such residues is crucial for understanding mechanisms of molecular recognition and for rational protein and drug design. Assuming conservation of specificity among orthologs and different specificity of paralogs, we identify residues that correlate with this grouping by specificity. The method is taking advantage of complete genomes to find multiple orthologs and paralogs. The central part of this method is a procedure to compute statistical significance of the predictions. The procedure is based on a simple statistical model of protein evolution. When applied to a large family of bacterial transcription factors, our method identified 12 residues that are presumed to determine the protein-DNA and protein-ligand recognition specificity. Structural analysis of the proteins and available experimental results strongly support our predictions. Our results suggest new experiments aimed at rational re-design of specificity in bacterial transcription factors by a minimal number of mutations.
机译:由于全基因组比较可以在完整的基因组中进行识别,因此正字学和寄生学的概念变得越来越重要。蛋白质的功能特异性被认为在直系同源物之间是保守的,而在旁系同源物之间是不同的。我们使用该假设来鉴定决定蛋白质-DNA和蛋白质-配体识别特异性的残基。找到这样的残基对于理解分子识别机制以及合理的蛋白质和药物设计至关重要。假设直系同源物之间保留特异性,而旁系同源物具有不同的特异性,我们通过特异性鉴定与该分组相关的残基。该方法利用完整的基因组来发现多个直系同源物和旁系同源物。该方法的中心部分是计算预测的统计显着性的过程。该程序基于蛋白质进化的简单统计模型。当应用于一大类细菌转录因子时,我们的方法鉴定出了12个残基,这些残基被认为可确定蛋白质-DNA和蛋白质-配体的识别特异性。蛋白质的结构分析和可用的实验结果强烈支持我们的预测。我们的结果表明新的实验旨在通过最少数量的突变合理地重新设计细菌转录因子的特异性。

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