Wroe Richard, Bornberg-Bauer Erich, Chan Hue Sun
Faculty of Life Sciences, University of Manchester, United Kingdom.
Biophys J. 2005 Jan;88(1):118-31. doi: 10.1529/biophysj.104.050369. Epub 2004 Oct 22.
Understanding the evolution of biopolymers is a key element in rationalizing their structures and functions. Simple exact models (SEMs) are well-positioned to address general principles of evolution as they permit the exhaustive enumeration of both sequence and structure (conformational) spaces. The physics-based models of the complete mapping between genotypes and phenotypes afforded by SEMs have proven valuable for gaining insight into how adaptation and selection operate among large collections of sequences and structures. This study compares the properties of evolutionary landscapes of a variety of SEMs to delineate robust predictions and possible model-specific artifacts. Among the models studied, the ruggedness of evolutionary landscape is significantly model-dependent; those derived from more protein-like models appear to be smoother. We found that a common practice of restricting protein structure space to maximally compact lattice conformations results in (i.e., "designs in") many encodable (designable) structures that are not otherwise encodable in the corresponding unrestrained structure space. This discrepancy is especially severe for model potentials that seek to mimic the major role of hydrophobic interactions in protein folding. In general, restricting conformations to be maximally compact leads to larger changes in the model genotype-phenotype mapping than a moderate shifting of reference state energy of the model potential function to allow for more specific encoding via the "designing out" effects of repulsive interactions. Despite these variations, the superfunnel paradigm applies to all SEMs we have tested: For a majority of neutral nets across different models, there exists a funnel-like organization of native stabilities for the sequences in a neutral net encoding for the same structure, and the thermodynamically most stable sequence is also the most robust against mutation.
理解生物聚合物的进化是阐明其结构和功能的关键要素。简单精确模型（SEMs）非常适合解决进化的一般原则，因为它们允许对序列空间和结构（构象）空间进行详尽的枚举。由SEMs提供的基于物理学的基因型与表型之间完整映射的模型，已被证明对于深入了解适应和选择如何在大量序列和结构集合中起作用很有价值。本研究比较了各种SEMs进化景观的特性，以描绘出可靠的预测结果和可能的模型特定假象。在所研究的模型中，进化景观的崎岖程度显著依赖于模型；那些源自更类似蛋白质模型的景观似乎更平滑。我们发现，将蛋白质结构空间限制为最大程度紧凑的晶格构象这一常见做法，会导致（即“设计入”）许多在相应无限制结构空间中无法编码的可编码（可设计）结构。对于试图模拟疏水相互作用在蛋白质折叠中主要作用的模型势来说，这种差异尤为严重。一般而言，将构象限制为最大程度紧凑，相比于适度改变模型势函数的参考态能量以通过排斥相互作用的“设计出”效应实现更具体的编码，会导致模型基因型 - 表型映射发生更大的变化。尽管存在这些差异，超漏斗范式适用于我们测试过的所有SEMs：对于不同模型中的大多数中性网络，在编码相同结构的中性网络中的序列，存在一种类似漏斗的天然稳定性组织，并且热力学上最稳定的序列对突变也最具抗性。
