Combining computational and experimental screening for rapid optimization of protein properties
Combining computational and experimental screening for rapid optimization of protein properties
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DOI：
10.1073/pnas.212627499
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发表时间：
2002-12-10
影响因子：
11.1
通讯作者：
Dahiyat, BI
中科院分区：
文献类型：
--
作者：
Hayes, RJ;Bentzien, J;Dahiyat, BI
我们提出了一种计算和实验相结合的方法快速优化蛋白质。使用β-内酰胺酶作为测试案例，我们使用蛋白质设计自动化技术重新设计了活性位点区域作为计算屏幕，以搜索整个序列空间。通过消除与蛋白质折叠不相容的序列，蛋白质设计自动化迅速地将序列的数量减少到适合实验筛选的大小，产生了大约200，000个突变体的文库。然后构建并实验筛选这些变体，以选择对抗生素头孢噻肟具有改善的抗性的变体。在一轮中，我们获得了表现出1，280倍抗性增加的变体。据我们所知，所有的突变都是新的，即，它们还没有被随机诱变或DNA改组鉴定为有益的，也没有在任何天然存在的TEM β-内酰胺酶（最普遍类型的革兰氏阴性β-内酰胺酶）中看到。这种结合的方法允许快速改进任何可以通过实验筛选的性质，并为蛋白质工程提供了一个强大的广泛适用的工具。
We present a combined computational and experimental method for the rapid optimization of proteins. Using beta-lactamase as a test case, we redesigned the active site region using our Protein Design Automation technology as a computational screen to search the entire sequence space. Byeliminating sequences incompatible with the protein fold, Protein Design Automation rapidly reduced the number of sequences to a size amenable to experimental screening, resulting in a library of approximate to200,000 mutants. These were then constructed and experimentally screened to select for variants with improved resistance to the antibiotic cefotaxime. In a single round, we obtained variants exhibiting a 1,280-fold increase in resistance. To our knowledge, all of the mutations were novel, i.e., they have not been identified as beneficial by random mutagenesis or DNA shuffling or seen in any of the naturally occurring TEM beta-lactamases, the most prevalent type of Gram-negative beta-lactamases. This combined approach allows for the rapid improvement of any property that can be screened experimentally and provides a powerful broadly applicable tool for protein engineering.