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蛋白质进化中的体积变化。

Volume changes in protein evolution.

作者信息

Gerstein M, Sonnhammer E L, Chothia C

机构信息

MRC Laboratory of Molecular Biology, Cambridge, U.K.

出版信息

J Mol Biol. 1994 Mar 4;236(4):1067-78. doi: 10.1016/0022-2836(94)90012-4.

Abstract

We have determined the variations in volume that occur during evolution in the buried core of three different families of proteins. The variation of the whole core is very small (approximately 2.5%) compared to the variation at individual sites (approximately 13%). However, by comparing our results to those expected from random sequences with no correlations between sites, we show that the small variation observed may simply be a manifestation of the statistical "law of large numbers" and not reflect any compensating changes in, or global constraints upon, protein sequences. We have also analysed in detail the volume variations at individual sites, both in the core and on the surface, and compared these variations with those expected from random sequences. Individual sites on the surface have nearly the same variation as random sequences (24% versus 28% variation). However, individual sites in the core have about half the variation of random sequences (13% versus 30%). Roughly, half of these core sites strongly conserve their volume (0 to 10% variation); one quarter have moderate variation (10 to 20%); and the remaining quarter vary randomly (20 to 40%). Our results have clear implications for the relationship between protein sequence and structure. For our analysis, we have developed a new and simple method for weighting protein sequences to correct for unequal representation, which we describe in an Appendix.

摘要

我们已经确定了三种不同蛋白质家族埋藏核心在进化过程中发生的体积变化。与单个位点的变化(约13%)相比,整个核心的变化非常小(约2.5%)。然而,通过将我们的结果与位点之间无相关性的随机序列预期结果进行比较,我们表明观察到的小变化可能仅仅是统计“大数定律”的一种表现,并不反映蛋白质序列中的任何补偿性变化或全局限制。我们还详细分析了核心和表面单个位点的体积变化,并将这些变化与随机序列的预期变化进行了比较。表面上的单个位点与随机序列的变化几乎相同(24%对28%的变化)。然而,核心中的单个位点的变化约为随机序列的一半(13%对30%)。大致来说,这些核心位点中有一半强烈保持其体积(0至10%的变化);四分之一有中等变化(10至20%);其余四分之一随机变化(20至40%)。我们的结果对蛋白质序列与结构之间的关系具有明确的启示。为了我们的分析,我们开发了一种新的简单方法来加权蛋白质序列以校正不等代表性,我们在附录中对此进行了描述。

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