Biochemistry and Structural Biology, Lund University, Lund, Sweden.
PLoS Comput Biol. 2023 Mar 24;19(3):e1010262. doi: 10.1371/journal.pcbi.1010262. eCollection 2023 Mar.
Thermodynamic stability is a crucial fitness constraint in protein evolution and is a central factor in shaping the sequence landscapes of proteins. The correlation between stability and molecular fitness depends on the mechanism that relates the biophysical property with biological function. In the simplest case, stability and fitness are related by the amount of folded protein. However, when proteins are toxic in the unfolded state, the fitness function shifts, resulting in higher stability under mutation-selection balance. Likewise, a higher population size results in a similar change in protein stability, as it magnifies the effect of the selection pressure in evolutionary dynamics. This study investigates how such factors affect the evolution of protein stability, site-specific mutation rates, and residue-residue covariation. To simulate evolutionary trajectories with realistic modeling of protein energetics, we develop an all-atom simulator of protein evolution, RosettaEvolve. By evolving proteins under different fitness functions, we can study how the fitness function affects the distribution of proposed and accepted mutations, site-specific rates, and the prevalence of correlated amino acid substitutions. We demonstrate that fitness pressure affects the proposal distribution of mutational effects, that changes in stability can largely explain variations in site-specific substitution rates in evolutionary trajectories, and that increased fitness pressure results in a stronger covariation signal. Our results give mechanistic insight into the evolutionary consequences of variation in protein stability and provide a basis to rationalize the strong covariation signal observed in natural sequence alignments.
热力学稳定性是蛋白质进化中的一个关键适应度约束因素,也是塑造蛋白质序列景观的核心因素。稳定性与分子适应度之间的相关性取决于将生物物理性质与生物功能联系起来的机制。在最简单的情况下,稳定性和适应度通过折叠蛋白的量来关联。然而,当蛋白质在未折叠状态下有毒时,适应度函数会发生转移,导致在突变-选择平衡下稳定性更高。同样,更高的种群大小会导致蛋白质稳定性发生类似的变化,因为它放大了进化动力学中选择压力的影响。本研究探讨了这些因素如何影响蛋白质稳定性、特定位置突变率和残基残基相关性的进化。为了通过对蛋白质能量学的真实模拟来模拟进化轨迹,我们开发了一种全原子蛋白质进化模拟器 RosettaEvolve。通过在不同适应度函数下进化蛋白质,我们可以研究适应度函数如何影响提议和接受突变的分布、特定位置的速率以及相关氨基酸取代的普遍性。我们证明了适应度压力会影响突变效应的提议分布,稳定性的变化可以在很大程度上解释进化轨迹中特定位置取代率的变化,并且适应度压力的增加会导致更强的相关性信号。我们的结果为蛋白质稳定性变化的进化后果提供了机制上的见解,并为合理化自然序列比对中观察到的强相关性信号提供了基础。