Recursive ensemble mutagenesis.
Recursive ensemble mutagenesis.
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递归整体诱变。
DOI：
10.1093/protein/6.3.327
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发表时间：
1993
期刊：
影响因子：
--
通讯作者：
Youvan,DC
中科院分区：
文献类型：
--
作者：
Delagrave,S;Goldman,ER;Youvan,DC
我们开发了一种普遍适用的实验程序来寻找功能蛋白，这些蛋白是野生型的许多突变步骤。通常用于搜索某些组合问题的解的优化算法已被用于搜索蛋白质的序列空间的问题。通常由数字计算机执行的许多步骤都体现在这种新的分子遗传学技术中，称为递归集合突变(REM)。REM使用从组合盒突变(CCM)的先前迭代中获得的信息来更有效地搜索序列空间。我们使用REM同时突变了一个模型蛋白质中的六个氨基酸残基。与传统的CCM相比，一次REM迭代产生的“阳性”突变体的频率增加了30倍。由于额外的6个残基的突变预计会有类似量级的倍增因子，因此在18个位点上进行REM预计将产生与随机[NN(G，C)]18突变相比指数级(30000倍)的阳性突变体产量增加。
We have developed a generally applicable experimental procedure to find functional proteins that are many mutational steps from wild type. Optimization algorithms, which are typically used to search for solutions to certain combinatorial problems, have been adapted to the problem of searching the ‘sequence space’ of proteins. Many of the steps normally performed by a digital computer are embodied in this new molecular genetics technique, termed recursive ensemble mutagenesis (REM). REM uses information gained from previous iterations of combinatorial cassette mutagenesis (CCM) to search sequence space more efficiently. We have used REM to simultaneously mutate six amino acid residues in a model protein. As compared to conventional CCM, one iteration of REM yielded a 30-fold increase in the frequency of ‘positive’ mutants. Since a multiplicative factor of similar magnitude is expected for the mutagenesis of additional sets of six residues, performing REM on 18 sites is expected to yield an exponential (30 000-fold) increase in the throughput of positive mutants as compared to random [NN(G,C)]18mutagenesis.