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人工WW结构域中的类天然功能。

Natural-like function in artificial WW domains.

作者信息

Russ William P, Lowery Drew M, Mishra Prashant, Yaffe Michael B, Ranganathan Rama

机构信息

Howard Hughes Medical Institute and Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA.

出版信息

Nature. 2005 Sep 22;437(7058):579-83. doi: 10.1038/nature03990.

Abstract

Protein sequences evolve through random mutagenesis with selection for optimal fitness. Cooperative folding into a stable tertiary structure is one aspect of fitness, but evolutionary selection ultimately operates on function, not on structure. In the accompanying paper, we proposed a model for the evolutionary constraint on a small protein interaction module (the WW domain) through application of the SCA, a statistical analysis of multiple sequence alignments. Construction of artificial protein sequences directed only by the SCA showed that the information extracted by this analysis is sufficient to engineer the WW fold at atomic resolution. Here, we demonstrate that these artificial WW sequences function like their natural counterparts, showing class-specific recognition of proline-containing target peptides. Consistent with SCA predictions, a distributed network of residues mediates functional specificity in WW domains. The ability to recapitulate natural-like function in designed sequences shows that a relatively small quantity of sequence information is sufficient to specify the global energetics of amino acid interactions.

摘要

蛋白质序列通过随机诱变并选择最优适应性而进化。协同折叠成稳定的三级结构是适应性的一个方面,但进化选择最终作用于功能,而非结构。在随附论文中,我们通过应用SCA(一种对多序列比对的统计分析方法),提出了一个针对小蛋白质相互作用模块(WW结构域)的进化限制模型。仅由SCA指导构建的人工蛋白质序列表明,该分析所提取的信息足以在原子分辨率上构建WW折叠。在此,我们证明这些人工WW序列的功能与其天然对应物相似,表现出对含脯氨酸靶肽的类别特异性识别。与SCA预测一致,一个分布式的残基网络介导了WW结构域中的功能特异性。在设计序列中重现类似天然功能的能力表明,相对少量的序列信息足以确定氨基酸相互作用的全局能量学。

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