Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are "encoded" in the thousands of known protein structures, "decoding" them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds-a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.

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Active sites and ligand binding cavities in native proteins are often formed by curved β-sheets, and the ability to control β-sheet curvature would allow design of binding proteins with cavities customized to specific ligands. Towards this end, we investigated the mechanisms controlling β-sheet curvature by studying the geometry of β-sheets in naturally occurring protein structures and * Correspondence to: dabaker@u.washington.edu. † These authors contributed equally to this work. Supplementary Materials: Materials and MethodsFigs. S1 to S22 Tables S1 to S7 Input files and command lines for design calculations HHS Public Access Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript folding simulations. The principles emerging from this analysis were used to de novo design a series of proteins with curved β-sheets topped with a-helices. NMR and crystal structures of the designs closely match the computational models, showing that β-sheet curvature can be controlled with atomic-level accuracy. Our approach enables the design of proteins with cavities and provides a route to custom design ligand binding and catalytic sites.Ligand binding proteins with curved β-sheets surrounding the binding pocket, as in the NTF2-like, β-barrel, and jelly roll folds, play key roles in molecular recognition, metabolic pathways and cell signaling. Approaches to designing small molecule binding proteins and enzymes to date have started by searching for native protein scaffolds with ligand binding pockets with roughly the right geometry, and then redesigning the surrounding residues to optimize interactions with the small molecule. While this approach has yielded new binding proteins and catalysts (1-5), it is not optimal: there may be no naturally occurring scaffold with a pocket with the correct geometry, and introduction of mutations in the design process may change the pocket structure (6, 7). Building de novo proteins with custom-tailored binding sites could be a more effective strategy, but this remains an outstanding challenge (8-11). De novo protein design has recently focused on proteins with ideal backbone structures (12-16) (straight helices, uniform β-strands and short loops; see ref (17) for a recent exception) and optimal core sidechain packing, but the binding pockets of naturally occurring proteins lie on concave surfaces formed by non-ideal features such as kinked helices, curved β-sheets or long loops. The design of proteins with concave surfaces requires examination of how such irregular structural features can be programmed into the amino acid sequence.We begin by analyzing how classic (18, 19) β-bulges (irregularities in the pleating of edge strands) and register shifts (local termination of strand pairing) coupled with intrinsic β-strand geometry induce curvature in antiparallel β-sheets (20, 21). We quantify the curvature of an edge strand making an antiparallel pairing with a second strand by the bend angle (Fig. 1A). The absolute value of the bend angle (α) at residue i is the angle bet...

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 due to their non-local nature and 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, sidechain 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 jelly-roll structures with double-stranded β-helices formed by 8 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.