Tokuriki Nobuhiko, Stricher Francois, Schymkowitz Joost, Serrano Luis, Tawfik Dan S
Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel.
J Mol Biol. 2007 Jun 22;369(5):1318-32. doi: 10.1016/j.jmb.2007.03.069. Epub 2007 Mar 31.
How the thermodynamic stability effects of protein mutations (DeltaDeltaG) are distributed is a fundamental property related to the architecture, tolerance to mutations (mutational robustness), and evolutionary history of proteins. The stability effects of mutations also dictate the rate and dynamics of protein evolution, with deleterious mutations being the main inhibitory factor. Using the FoldX algorithm that attempts to computationally predict DeltaDeltaG effects of mutations, we deduced the overall distributions of stability effects for all possible mutations in 21 different globular, single domain proteins. We found that these distributions are strikingly similar despite a range of sizes and folds, and largely follow a bi-Gaussian function: The surface residues exhibit a narrow distribution with a mildly destabilizing mean DeltaDeltaG ( approximately 0.6 kcal/mol), whereas the core residues exhibit a wider distribution with a stronger destabilizing mean ( approximately 1.4 kcal/mol). Since smaller proteins have a higher fraction of surface residues, the relative weight of these single distributions correlates with size. We also found that proteins evolved in the laboratory follow an essentially identical distribution, whereas de novo designed folds show markedly less destabilizing distributions (i.e. they seem more robust to the effects of mutations). This bi-Gaussian model provides an analytical description of the predicted distributions of mutational stability effects. It comprises a novel tool for analyzing proteins and protein models, for simulating the effect of mutations under evolutionary processes, and a quantitative description of mutational robustness.
蛋白质突变的热力学稳定性效应(ΔΔG)是如何分布的,这是一个与蛋白质的结构、对突变的耐受性(突变稳健性)以及进化历史相关的基本特性。突变的稳定性效应还决定了蛋白质进化的速率和动力学,其中有害突变是主要的抑制因素。我们使用FoldX算法试图通过计算预测突变的ΔΔG效应,推导了21种不同的球状单结构域蛋白质中所有可能突变的稳定性效应的总体分布。我们发现,尽管这些蛋白质的大小和折叠方式各不相同,但它们的分布却惊人地相似,并且在很大程度上遵循双高斯函数:表面残基呈现出窄分布,其平均ΔΔG具有轻微的去稳定作用(约0.6千卡/摩尔),而核心残基呈现出宽分布,其平均去稳定作用更强(约1.4千卡/摩尔)。由于较小的蛋白质表面残基比例较高,这些单一分布的相对权重与大小相关。我们还发现,在实验室中进化的蛋白质遵循基本相同的分布,而从头设计的折叠结构显示出明显更弱的去稳定分布(即它们似乎对突变的影响更具稳健性)。这种双高斯模型为预测的突变稳定性效应分布提供了一种分析描述。它包括一种用于分析蛋白质和蛋白质模型、模拟进化过程中突变效应以及对突变稳健性进行定量描述的新工具。