Backbone flexibility in computational protein design

被引:78
|
作者
Mandell, Daniel J. [1 ,2 ]
Kortemme, Tanja [1 ,2 ,3 ]
机构
[1] Univ Calif San Francisco, Grad Program Bioinformat & Computat Biol, San Francisco, CA 94158 USA
[2] Univ Calif San Francisco, Calif Inst Quantitat Biosci, San Francisco, CA 94158 USA
[3] Univ Calif San Francisco, Dept Bioengn & Therapeut Sci, San Francisco, CA 94158 USA
基金
美国国家科学基金会;
关键词
DEAD-END ELIMINATION; AMINO-ACID-SEQUENCE; SIDE-CHAIN; STRUCTURE PREDICTION; TEMPLATES; DIVERSITY; STABILITY; ALGORITHM; EVOLUTION; SPACE;
D O I
10.1016/j.copbio.2009.07.006
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The field of computational protein design has produced striking successes, including the engineering of novel enzymes. Many of these achievements employed methodologies that sample amino acid side-chains on a fixed backbone, while methods that explicitly model backbone flexibility have so far largely focused on the design of new structures rather than functions. Recent methodological improvements in conformational sampling techniques, some borrowed from the field of robotics to model mechanically accessible conformations, now provide exciting opportunities to explore amino acid sequences and backbone structures simultaneously. Incorporating functional constraints into flexible backbone design should help to achieve challenging engineering goals that exploit the role of conformational variability in controlling biological processes, while more generally advancing biophysical understanding of the relationship between variations in protein sequence, structure, dynamics, and function.
引用
收藏
页码:420 / 428
页数:9
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