Binding and sensing diverse small molecules using shape-complementary pseudocycles

Abstract

We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.

Fig. 1.. Design strategy.

(A) Diverse conformers of the small molecule of interest are docked into deep learning–generated pseudocycles containing a wide array of central pockets, and the interface sequence is optimized for high-affinity binding with Rosetta or LigandMPNN. Top-ranked designs are tested experimentally, and the backbones of the best hits and the docked poses are extensively resampled. After sequence design, top-ranked second-round designs are experimentally tested (fig. S1, A and B). (B) Because pseudocycles are constructed from modular repeating units that surround the central binding pocket, the binders can be readily transformed into sensors through multiple strategies. (C to F) Examples of first-round design models for each target ligand.

Fig. 2.. X-ray crystallography demonstrates accuracy of design approach.

(A and B) The crystal structure of CHD_r1 (gray; ligand not modeled because of partial ligand electron density) is very similar to the computational design model (colored). (C and D) The crystal structure and the binding interface of CHD_buttress (gray) is very similar to the computational design model (colored). (E) The key polar- and hydrogen-bonding networks at the designed interface. (F) Composite omit map of interface region; the 2mFo-DFc electron density map at 1 σ level for CHD_buttress matches the design closely. Density maps are colored in teal. The protein backbone is shown in cartoons, and CHD and the key interacting side chains are shown in sticks. Pink, ligand carbon atoms; red, oxygen; blue, nitrogen; white, polar hydrogen. Also see fig. S7.

Fig. 3.. Experimental characterization of selected round-two designs.

(A to D) Nanomolar affinity CHD binders CHD_d1 to d4 (full list in fig. S9). (E) Nanomolar binder for AMA (see fig. S12). (F) Micromolar methotrexate binder. (G and H) Two nanomolar T44 binders (full list in fig. S14). For each panel, from left to right: the design model, zoom-in on the side-chain–ligand interactions, FP (or SPR in the case of AMA) binding measurements, and SEC traces. K_d values and error bars are from two independent experiments. Interacting side chains and ligands are shown in sticks, with oxygen, nitrogen, iodine, and polar hydrogen colored in red, blue, purple, and white, respectively. Key interactions are indicated by gray dashed lines. Cartoons and sticks for helixes, sheets, and loops are colored in teal, magenta, and dark blue, respectively.

Fig. 4.. Conversion of pseudocycle binders into ligand-gated channels and CID systems.

(A to F) Ligand-sensing de novo nanopore construction. (A) shows how the three structural repeat units of CHD_r1 were inserted into three different loops in a 12-stranded de novo nanopore by using inpainting to join the chains, such that the central axes of binder and nanopore are aligned. The conductance of the original nanopore is ~220 pS (fig. S17A) and is not influenced by CHD. The conductance of binder-fused nanopore in the absence (B) and presence of CHD [(C) to (E)] are shown for comparison. In the absence of CHD (B), the pore fluctuates between a state with high conductance very similar to the unmodified pore and a low-conductance state (C); in the presence of CHD, the duration of the low-conductance states is greatly increased [(C) to (E)]; the longer record (C) and a single closure event (D) are shown for clarity, and the histogram of the current with and without ligand is shown in (E). Different currents (0, 10, 15, and 20 pA) are marked out for clarity using dashed lines in black, magenta, teal, and green, respectively in (B) to (E). The gated nanopores are robust through multiple cycles of opening and closure (C). Upon reversal of the voltage, the original high-conductance state is restored (fig. S19B). As indicated schematically in (F), the conductance fluctuations of the binder-fused pore in absence of ligand likely reflect transient association of the three subunits; ligand binding stabilizes the associated state leading to prolonged blocking of the pore. (G to I) CID system construction. The CHD binder, CHD_r1, was buttressed by diffusion of an outer ring of helices to increase the stability of split protein fragments (Fig. 2, C to F, and figs. S7B and S20). To create a CID system, we split the buttressed binders into halves and redesign the protein-protein interface to increase solubility of the fragments and disfavor association in the absence of ligand. Characterization of CHD induced association of the split fragments by SEC (H) and mass photometry (I). Dimerization of the two split domains (A and B) in presence (first trace from top), but not the absence, (second trace from top) of ligand. The individual monomers do not dimerize in the presence (third and fourth trace from top) or absence (fifth and sixth traces from the top) of ligands. N-terminal GFP tags were fused to the monomers to facilitate detection by mass photometry.