Computational structure-based redesign of enzyme activity

被引:160
|
作者
Chen, Cheng-Yu [1 ]
Georgiev, Ivelin [2 ]
Anderson, Amy C. [3 ]
Donald, Bruce R. [1 ,2 ]
机构
[1] Duke Univ, Med Ctr, Dept Biochem, Durham, NC 27710 USA
[2] Duke Univ, Dept Comp Sci, Durham, NC 27708 USA
[3] Univ Connecticut, Dept Pharmaceut Sci, Storrs, CT 06269 USA
基金
美国国家卫生研究院;
关键词
biophysical algorithms; gramicidin S synthetase; nonribosomal peptide synthetase; protein design; DEAD-END-ELIMINATION; DIRECTED EVOLUTION; GRAMICIDIN SYNTHETASE; PROTEIN REDESIGN; SEARCH ALGORITHM; CONFERRING CODE; DESIGN; PHENYLALANINE; RECOGNITION; SPECIFICITY;
D O I
10.1073/pnas.0900266106
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
We report a computational, structure-based redesign of the phenylalanine adenylation domain of the nonribosomal peptide synthetase enzyme gramicidin S synthetase A (GrsA-PheA) for a set of noncognate substrates for which the wild-type enzyme has little or virtually no specificity. Experimental validation of a set of top-ranked computationally predicted enzyme mutants shows significant improvement in the specificity for the target substrates. We further present enhancements to the methodology for computational enzyme redesign that are experimentally shown to result in significant additional improvements in the target substrate specificity. The mutant with the highest activity for a noncognate substrate exhibits 1/6 of the wild-type enzyme/wild-type substrate activity, further confirming the feasibility of our computational approach. Our results suggest that structure-based protein design can identify active mutants different from those selected by evolution.
引用
收藏
页码:3764 / 3769
页数:6
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