Mannige Ranjan V
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Jun;87(6):062714. doi: 10.1103/PhysRevE.87.062714. Epub 2013 Jun 24.
Protein sequence evolution has resulted in a vast repertoire of molecular functionality crucial to life. Despite the central importance of sequence evolution to biology, our fundamental understanding of how sequence composition affects evolution is incomplete. This report describes the utilization of lattice model simulations of directed evolution, which indicate that, on average, peptide and protein evolvability is strongly dependent on initial sequence composition. The report also discusses two distinct regimes of sequence evolution by point mutation: (a) the "classical" mode where sequences "crawl" over free energy barriers towards acquiring a target fold, and (b) the "quantum" mode where sequences appear to "tunnel" through large energy barriers generally insurmountable by means of a crawl. Finally, the simulations indicate that oily and charged peptides are the most efficient substrates for evolution at the "classical" and "quantum" regimes, respectively, and that their respective response to temperature is commensurate with analogies made to barrier crossing in classical and quantum systems. On the whole, these results show that sequence composition can tune both the evolvability and the optimal mode of evolution of peptides and proteins.
蛋白质序列进化产生了对生命至关重要的大量分子功能。尽管序列进化对生物学至关重要，但我们对序列组成如何影响进化的基本理解并不完整。本报告描述了定向进化晶格模型模拟的应用，结果表明，平均而言，肽和蛋白质的进化能力强烈依赖于初始序列组成。该报告还讨论了点突变导致的两种不同的序列进化模式：(a) “经典”模式，即序列越过自由能障碍“爬行”以获得目标折叠；(b) “量子”模式，即序列似乎通过通常无法通过“爬行”跨越的大能量障碍“隧穿”。最后，模拟表明，油性肽和带电肽分别是“经典”和“量子”模式下最有效的进化底物，它们对温度的各自响应与经典和量子系统中越过障碍的类比相一致。总体而言，这些结果表明序列组成可以调节肽和蛋白质的进化能力以及进化的最佳模式。
