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Control of repeat-protein curvature by computational protein design

Abstract

Shape complementarity is an important component of molecular recognition, and the ability to precisely adjust the shape of a binding scaffold to match a target of interest would greatly facilitate the creation of high-affinity protein reagents and therapeutics. Here we describe a general approach to control the shape of the binding surface on repeat-protein scaffolds and apply it to leucine-rich-repeat proteins. First, self-compatible building-block modules are designed that, when polymerized, generate surfaces with unique but constant curvatures. Second, a set of junction modules that connect the different building blocks are designed. Finally, new proteins with custom-designed shapes are generated by appropriately combining building-block and junction modules. Crystal structures of the designs illustrate the power of the approach in controlling repeat-protein curvature.

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Figure 1: Assembly of LRRs from modules.
Figure 2: Design of building-block and junction modules.
Figure 3: Crystal structures of the building-block-module and junction-module designs.
Figure 4: Control of curvature by general module assembly.

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Acknowledgements

We thank J. Bolduc for data collection for DLRR_A and the members of the protein production facility at the Institute for Protein Design for protein production. This work was supported by grants from the Howard Hughes Medical Institute (to D.B.), the Defense Threat Reduction Agency (HDTRA1-11-1-0041 to D.B.) and US National Institutes of Health (R01 GM49857 to B.L.S.). F.P. was supported as the recipient of a Swiss National Science Foundation Postdoctoral Fellowship (PBZHP3-125470) and a Human Frontier Science Program Long-Term Fellowship (LT000070/2009-L). This work was facilitated though the use of advanced computational, storage and networking infrastructure provided by the Hyak supercomputer system at the University of Washington.

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Contributions

K.P. and D.B. conceived the project; K.P. performed the computational design with assistance from F.P. and P.-S.H.; K.P. expressed, purified and characterized the designs with assistance from F.P.; B.W.S. crystallized the designs and determined the structures; K.P. and D.B. drafted the manuscript with input from all authors; B.L.S. and D.B. supervised research.

Corresponding author

Correspondence to David Baker.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Characterization of designed leucine-rich-repeat proteins.

(a) Water-mediate hydrogen-bond network is frequently visible in the convex region of LRR crystal structures. Examples are shown for the idealized L24 (DLRR_B) and L24→L28 fusion structure (DLRR_G3). Water molecules participating in the hydrogen bond (yellow dots) network are represented by spheres. (b) Super-helical shapes of the three idealized building block repeats. For clear visualization, dots tracing the global super-helix defined by the fitted parameters are overlaid with the LRR structures (rotation angle < 720°). The highly conserved leucine residues used for the parameter fitting are represented by spheres. See Supplementary Table 1 for the helical parameter estimation. (c) Structural alignments of the partial Ncap-L245 structure in DLRR_B (top) and L225 structure in DLRR_A (bottom) into the crystal structure of DLRR_E. Cα r.m.s. deviations for the alignments of DLRR_B and DLRR_A are 0.4 Å and 0.3 Å, respectively. (d) Structural defects in the initial fusion model of DLRR_G3. The crystal structure (magenta) of the junction module in DLRR_G3 is aligned with the initial model structure before design (gray) and the final model structure after design (green). The initial model contains large cavity and side chain clashes in the junction module, which are improved in the subsequent design procedure as shown in the final model structure (green). (e) SEC-MALS experiments for DLRR_D, DLRR_E, DLRR_I, DLRR_J, DLRR_K, and DLRR_L. Most of designs are monomeric even though some soluble aggregates/oligomers are observed in DLRR_I and DLRR_K.

Supplementary Figure 2 Experimental characterization of six L22→L28 designs (DLRR_F).

In the top row, structure alignment (left) and sequence alignment (right) of the six junction module designs are represented. The building block sequences (L22 + L28) are shown in the first row of the sequence alignment for comparison. Far-UV CD spectra, thermal denaturation at 218 nm, and SEC-MALS are shown from left to right for each design.

Supplementary Figure 3 Experimental characterization of six L24→L28 designs (DLRR_G).

In the top row, structure alignment (left) and sequence alignment (right) of the six junction module designs are represented. The building block sequences (L24 + L28) are shown in the first row of the sequence alignment for comparison. Far-UV CD spectra, thermal denaturation at 218 nm, and SEC-MALS are shown from left to right for each design. DLRR_G6 has one less {L28→L29} module than the others. The crystal structure of DLRR_G3 is shown in Figure 3d.

Supplementary Figure 4 Experimental characterization of four L24→L32→L24 designs (DLRR_H).

In the top row, structural alignment of the four wedge module designs is represented with the structure. Sequence alignment of the four wedge module designs is shown with the building block and the native L32 module sequence (L24 + L32 + L24) in the first row of the alignment for comparison. Far-UV CD spectra, thermal denaturation at 218 nm, and SEC-MALS are shown from left to right for each design. Design DLRR_I has two identical L32 modules derived from DLRR_H1 (Supplementary Table 2). In SEC-MALS experiments, some soluble aggregates/oligomers are observed in addition to the monomeric status. The crystal structure of DLRR_H2 is shown in Figure 3e.

Supplementary Figure 5 Characterization of designed junction modules.

(a) Sequence alignments between the designed junction modules and the top 3 naturally occurring sequences (square block) found in BLAST1 search for the non-redundant (NR) database. There are numerous sequence differences between the designed modules and the closest sequence in NR. Indeed, BLAST fails to find full length alignments for most of the junction sequences. (b) Comparison of structures of designed and naturally occurring junctions between LRR modules. Left: designed junction modules, Middle: the closest structural matches found in the PDB using TMalign2, Right: structural alignment. The TMalign searches were carried out with the two-unit junction module structures (green) and one or two module structures next to the junction module are shown for both designed and natural structures (yellow) to make the ideality (lack of ideality) of the different structures clearer. Most junctions between different length LRR modules in the native structures occur near the caps where the structure becomes much less regular. This irregularity, evident in the right side of the images from native structures, makes it not possible to generate novel LRR’s with controlled curvature by combining multiple different types of modules simply using junctions already existing in the PDB. (c) Structural comparison between crystal structures and model structures generated by the iterative module assembly protocol described in Method. All model structures show high consistency to the crystal structures (r.m.s. deviationg in Table 2). (d) Native LRR proteins, internalin A (InlA, PDB ID: 1O6S, top left) and ribonuclease inhibitor (RI, PDB ID: 1A4Y, bottom left), achieve high affinity and specificity by having shapes closely conforming to the surfaces of the target proteins (human E-cadherin and ribonuclease A, respectively). Each protein has a curvature optimized to its target, resulting in well-packed complementary protein-protein interfaces with hot-spot clusters (shown by red sticks) at both the N and C termini. In contract, swapping the respective target for each of the LRR proteins (i.e. RI:E-cadherin, orange-cyan complex in the top right and InlA:ribonuclease, green-yellow complex in the bottom right) makes the clashes and large gaps in the binding interface.

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Park, K., Shen, B., Parmeggiani, F. et al. Control of repeat-protein curvature by computational protein design. Nat Struct Mol Biol 22, 167–174 (2015). https://doi.org/10.1038/nsmb.2938

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