Publication details
De novo design of a non-local beta-sheet protein with high stability and accuracy
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Periodical |
| Magazine / Source | NATURE STRUCTURAL & MOLECULAR BIOLOGY |
| MU Faculty or unit | |
| 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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