New algorithms and an in silico benchmark for computational enzyme design

被引:264
作者
Zanghellini, Alexandre
Jiang, Lin
Wollacott, Andrew M.
Cheng, Gong
Meiler, Jens
Althoff, Eric A.
Rothlisberger, Daniela
Baker, David [1 ]
机构
[1] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
[2] Univ Washington, Mol Biophys Struct & Design Program, Seattle, WA 98195 USA
[3] Vanderbilt Univ, Dept Chem & Pharmacol, Nashville, TN 37232 USA
[4] Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USA
关键词
enzyme design; protein design; active site recapitulation; protein-ligand interactions; geometric hashing;
D O I
10.1110/ps.062353106
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.
引用
收藏
页码:2785 / 2794
页数:10
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