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

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This publication doesn't include Institute of Computer Science. It includes Central European Institute of Technology. Official publication website can be found on muni.cz.
Authors

MARCOS E. CHIDYAUSIKU T.M. MCSHAN A.C. EVANGELIDIS Thomas NERLI S. CARTER L. NIVON L.G. DAVIS A. OBERDORFER G. TRIPSIANES Konstantinos SGOURAKIS N.G. BAKER D.

Year of publication 2018
Type Article in Periodical
Magazine / Source NATURE STRUCTURAL & MOLECULAR BIOLOGY
MU Faculty or unit

Central European Institute of Technology

Citation
Doi http://dx.doi.org/10.1038/s41594-018-0141-6
Keywords STRUCTURE PREDICTION; COMPUTATIONAL DESIGN; SECONDARY STRUCTURE; SOLENOID PROTEINS; SANDWICH PROTEIN; NEGATIVE DESIGN; CHEMICAL-SHIFTS; NMR; ROSETTA; VALIDATION
Description beta-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-beta-sheet proteins from first principles lags far behind the design of all-alpha or mixed-alpha beta domains owing to their non-local nature and the tendency of exposed beta-strand edges to aggregate. Through study of loops connecting unpaired beta-strands (beta-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and beta-strand length that arise from hydrogen bonding and packing constraints on regular beta-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded beta-helices formed by eight antiparallel beta-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the beta-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local beta-sheet protein structures.
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