Taylor S V, Walter K U, Kast P, Hilvert D
Laboratorium für Organische Chemie, Swiss Federal Institute of Technology, CH-8093 Zürich, Switzerland.
Proc Natl Acad Sci U S A. 2001 Sep 11;98(19):10596-601. doi: 10.1073/pnas.191159298. Epub 2001 Sep 4.
Genetic selection was used to explore the probability of finding enzymes in protein sequence space. Large degenerate libraries were prepared by replacing all secondary structure units in a dimeric, helical bundle chorismate mutase with simple binary-patterned modules based on a limited set of four polar and four nonpolar residues. Two-stage in vivo selection yielded catalytically active variants possessing biophysical and kinetic properties typical of the natural enzyme even though approximately 80% of the protein originates from the simplified modules and >90% of the protein consists of only eight different amino acids. This study provides a quantitative assessment of the number of sequences compatible with a given fold and implicates previously unidentified residues needed to form a functional active site. Given the extremely low incidence of enzymes in completely unbiased libraries, strategies that combine chemical information with genetic selection, like the one used here, may be generally useful in designing novel protein scaffolds with tailored activities.
利用基因筛选来探究在蛋白质序列空间中找到酶的可能性。通过用基于一组有限的四个极性和四个非极性残基的简单二元模式模块替换二聚体螺旋束分支酸变位酶中的所有二级结构单元，制备了大型简并文库。两阶段体内筛选产生了具有天然酶典型生物物理和动力学特性的催化活性变体，尽管大约80%的蛋白质来自简化模块，且>90%的蛋白质仅由八种不同氨基酸组成。这项研究对与给定折叠兼容的序列数量进行了定量评估，并暗示了形成功能性活性位点所需的先前未鉴定的残基。鉴于在完全无偏文库中酶的发生率极低，将化学信息与基因筛选相结合的策略，如本文所用的策略，可能在设计具有定制活性的新型蛋白质支架方面普遍有用。
