Principles for designing proteins with cavities formed by curved β sheets

Abstract

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...

Buckling in armored droplets

“…The analogy between Fig. 1 and the shape of protein active site might play an important role for ligand docking [28,29]. Finally, buckled armored droplets might also be of relevance as potential drug delivery systems [6].…”

Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions

“…15–17, 25–27 The crucial final step following the generation of models is the application of a scoring function to find the structure presumed to be closest to the true native structure according to the most favorable score. Protein structure scoring functions are also important for computational protein design 28–29 and during protein structure refinement of template-based models. 30–32 …”

Expanding the space of protein geometries by computational design ofde novofold families

“…Previous key achievements in de novo design [11][12][13][14][15]20 focused on designing one or a few structures for diverse non-helical-bundle topologies by deriving design rules for specific topologies to identify the most favorable geometries. Proteins designed by this topology-centric strategy have pre-defined secondary structure sizes and loop torsions that are ideal to their topologies.…”

“…4D , Supplementary Figure S11 ), but without using this information as input. Moreover, LUCS does not require prior definition of structural variation based on design rules identified in native structures 20,29 to generate diverse geometries that sample both known and new structural space. New protocols could exploit this ability to flexibly tune protein geometries during design simulations while simultaneously building new functional sites.…”