De novo design of a non-local β-sheet protein with high stability and accuracy

反平行(数学) 测试表 蛋白质设计 蛋白质结构 结晶学 化学 物理 生物化学 量子力学 磁场
作者
Enrique Marcos,Tamuka M. Chidyausiku,Andrew C. McShan,Thomas Evangelidis,Santrupti Nerli,Lauren Carter,Lucas G. Nivón,Audrey L. Davis,Gustav Oberdorfer,Konstantinos Tripsianes,Nikolaos G. Sgourakis,David Baker
出处
期刊:Nature Structural & Molecular Biology [Springer Nature]
卷期号:25 (11): 1028-1034 被引量:123
标识
DOI:10.1038/s41594-018-0141-6
摘要

β-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-β-sheet proteins from first principles lags far behind the design of all-α or mixed-αβ domains owing to their non-local nature and the tendency of exposed β-strand edges to aggregate. Through study of loops connecting unpaired β-strands (β-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and β-strand length that arise from hydrogen bonding and packing constraints on regular β-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded β-helices formed by eight antiparallel β-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the β-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local β-sheet protein structures. Baker, Marcos and colleagues analyze β-arches (loops connecting unpaired β-strands) and derive rules used for de novo design of a hyperthermostable jellyroll structure, with eight antiparallel β-strands forming double-stranded β-helices.
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