Sasai M
Graduate School of Human Informatics, Nagoya University, Japan.
Proc Natl Acad Sci U S A. 1995 Aug 29;92(18):8438-42. doi: 10.1073/pnas.92.18.8438.
Evolutionary selection of sequences is studied with a knowledge-based Hamiltonian to find the design principle for folding to a model protein structure. With sequences selected by naive energy minimization, the model structure tends to be unstable and the folding ability is low. Sequences with high folding ability have only the low-lying energy minimum but also an energy landscape which is similar to that found for the native sequence over a wide region of the conformation space. Though there is a large fluctuation in foldable sequences, the hydrophobicity pattern and the glycine locations are preserved among them. Implications of the design principle for the molecular mechanism of folding are discussed.
利用基于知识的哈密顿量研究序列的进化选择，以找到折叠成模型蛋白质结构的设计原则。通过简单的能量最小化选择的序列，模型结构往往不稳定且折叠能力较低。具有高折叠能力的序列不仅具有低能最小值，而且在构象空间的广泛区域内具有与天然序列相似的能量景观。尽管可折叠序列存在较大波动，但它们之间的疏水性模式和甘氨酸位置得以保留。讨论了该设计原则对折叠分子机制的影响。
