FoldX as Protein Engineering Tool: Better Than Random Based Approaches?

被引:151
|
作者
Buss, Oliver [1 ]
Rudat, Jens [1 ]
Ochsenreither, Katrin [1 ]
机构
[1] Karlsruhe Inst Technol, Inst Proc Engn Life Sci, Sect Tech Biol 2, Engler Bunte Ring 3, D-76131 Karlsruhe, Germany
关键词
FoldX; Fold-X; Thermostability; Protein stabilization; Protein engineering; Enzyme engineering; DIRECTED EVOLUTION; SUPEROXIDE-DISMUTASE; THERMAL-STABILITY; IMPROVED THERMOSTABILITY; TEMPERATURE ADAPTATION; SATURATION MUTAGENESIS; ENZYMATIC-PROPERTIES; SEQUENCE STATISTICS; GLUCOSE BIOSENSORS; PREDICTING CHANGES;
D O I
10.1016/j.csbj.2018.01.002
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
Improving protein stability is an important goal for basic research as well as for clinical and industrial applications but no commonly accepted and widely used strategy for efficient engineering is known. Beside random approaches like error prone PCR or physical techniques to stabilize proteins, e.g. by immobilization, in silico approaches are gaining more attention to apply target-oriented mutagenesis. In this review different algorithms for the prediction of beneficial mutation sites to enhance protein stability are summarized and the advantages and disadvantages of FoldX are highlighted. The question whether the prediction of mutation sites by the algorithm FoldX is more accurate than random based approaches is addressed. (C) 2018 Buss et al. Published by Elsevier B.V. on behalf of the Research Network of Computational and Structural Biotechnology.
引用
收藏
页码:25 / 33
页数:9
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