The SARS-CoV-2 pandemic has led to an urgent need to understand the molecular basis for immune recognition of SARS-CoV-2 spike (S) glycoprotein antigenic sites. To define the genetic and structural basis for SARS-CoV-2 neutralization, we determined the structures of two human monoclonal antibodies COV2-2196 and COV2-21301, which form the basis of the investigational antibody cocktail AZD7442, in complex with the receptor binding domain (RBD) of SARS-CoV-2. COV2-2196 forms an “aromatic cage” at the heavy/light chain interface using germline-encoded residues in complementarity determining regions (CDRs) 2 and 3 of the heavy chain and CDRs 1 and 3 of the light chain. These structural features explain why highly similar antibodies (public clonotypes) have been isolated from multiple individuals1–4. The structure of COV2-2130 reveals that an unusually long LCDR1 and HCDR3 make interactions with the opposite face of the RBD from that of COV2-2196. Using deep mutational scanning and neutralization escape selection experiments, we comprehensively mapped the critical residues of both antibodies and identified positions of concern for possible viral escape. Nonetheless, both COV2-2196 and COV2130 showed strong neutralizing activity against SARS-CoV-2 strain with recent variations of concern including E484K, N501Y, and D614G substitutions. These studies reveal germline-encoded antibody features enabling recognition of the RBD and demonstrate the activity of a cocktail like AZD7442 in preventing escape from emerging variant viruses.

The development of improved methods for early detection and characterization of cancer presents a major clinical challenge. One approach that has shown excellent potential in preclinical and clinical evaluation is molecular imaging with small-scaffold, non-antibody based, engineered proteins. These novel diagnostic agents produce high contrast images due to their fast clearance from the bloodstream and healthy tissues, can be evolved to bind a multitude of cancer biomarkers, and are easily functionalized by site-specific bioconjugation methods. Several small protein scaffolds have been verified for in vivo molecular imaging including affibodies and their two-helix variants, knottins, fibronectins, DARPins, and several natural ligands. Further, the biodistribution of these engineered ligands can be optimized through rational mutation of the conserved regions, careful selection and placement of chelator, and modification of molecular size.

Purpose Determine the efficacy of a 45-amino acid Gp2 domain, engineered to bind to epidermal growth factor receptor (EGFR), as a positron emission tomography (PET) probe of EGFR in a xenograft mouse model. Methods The EGFR-targeted Gp2 (Gp2-EGFR) and a non-binding control were site-specifically labeled with 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelator. Binding affinity was tested towards human EGFR and mouse EGFR. Biological activity on downstream EGFR signaling was examined in cell culture. DOTA-Gp2 molecules were labeled with 64Cu and intravenously injected (0.6–2.3 MBq) into mice bearing EGFRhigh (n=7) and EGFRlow (n=4) xenografted tumors. PET/computed tomography (CT) images were acquired at 45 min, 2 h, and 24 h. Dynamic PET (25 min) was also acquired. Tomography results were verified with gamma counting of resected tissues. Two-tailed t tests with unequal variances provided statistical comparison. Results DOTA-Gp2-EGFR bound strongly to human (KD = 7 ± 5 nM) and murine (KD = 29 ± 6 nM) EGFR, and non-targeted Gp2 had no detectable binding. Gp2-EGFR did not agonize EGFR nor antagonize EGF-EGFR. 64Cu-Gp2-EGFR tracer effectively localized to EGFRhigh tumors at 45 minutes (3.2 ± 0.5 %ID/g). High specificity was observed with significantly lower uptake in EGFRlow tumors (0.9 ± 0.3 %ID/g, p < 0.001), high tumor-to-background ratios (11 ± 6 tumor:muscle, p < 0.001). Non-targeted Gp2 tracer had low uptake in EGFRhigh tumors (0.5 ± 0.3 %ID/g, p < 0.001). Similar data was observed at 2 h and tumor signal was retained at 24 h (2.9 ± 0.3 %ID/g). Conclusion An engineered Gp2 PET imaging probe exhibited low background and target-specific EGFRhigh tumor uptake at 45 min, with tumor signal retained at 24 h post-injection, and compared favorably with published EGFR PET probes for alternative protein scaffolds. These beneficial in vivo characteristics, combined with thermal stability, efficient evolution, and small size of the Gp2 domain validate its use as a future class of molecular imaging agents.

Protein ligand charge can impact physiological delivery with charge reduction often benefiting performance. Yet neutralizing mutations can be detrimental to protein function. Herein, three approaches are evaluated to introduce charged-to-neutral mutations of three cations and three anions within an affibody engineered to bind epidermal growth factor receptor. These approaches – combinatorial library sorting or consensus design, based on natural homologs or library-sorted mutants – are used to identify mutations with favorable affinity, stability, and recombinant yield. Consensus design, based on 942 affibody homologs, yielded a mutant of modest function (Kd = 11 ±4 nM, Tm = 62 °C, and yield = 4.0 ±0.8 mg/L as compared to 5.3 ±1.7 nM, 71 °C, and 3.5 ±0.3 mg/L for the parental affibody). Extension of consensus design to ten additional mutants exhibited varied performance including a substantially improved mutant (Kd = 6.9 ±1.4 nM, Tm = 71 °C, and 12.7 ±0.9 mg/L yield). Sorting a homolog-based combinatorial library of 7×105 mutants generated a distribution of mutants with lower stability and yield, but did identify one strongly binding variant (Kd = 1.2 ±0.3 nM, Tm = 69 °C, and 6.0 ±0.4 mg/L yield). Synthetic consensus design, based on the amino acid distribution in functional library mutants, yielded higher affinities (p=0.05) with comparable stabilities and yields. The best of four analyzed clones had Kd = 1.7 ±0.5 nM, Tm = 68 °C, and 7.0 ±0.5 mg/L yield. While all three approaches were effective in creating targeted affibodies with six charged-to-neutral mutations, synthetic consensus design proved to be the most robust. Synthetic consensus design provides a valuable tool for ligand engineering, particularly in the context of charge manipulation.

The Gp2 domain is a protein scaffold for synthetic ligand engineering. However, the native protein function results in a heterogeneous distribution of charge on the conserved surface, which may hinder further development and utility. We aim to modulate charge, without diminishing function, which is challenging in small proteins where each mutation is a significant fraction of protein structure. We constructed rationally guided combinatorial libraries with charge-neutralizing or charge-flipping mutations and sorted them, via yeast display and flow cytometry, for stability and target binding. Deep sequencing of functional variants revealed effective mutations both in clone-dependent contexts and broadly across binders to epidermal growth factor receptor (EGFR), insulin receptor, and immunoglobulin G. Functional mutants averaged 4.3 charge neutralizing mutations per domain while maintaining net negative charge. We evolved an EGFR-targeted Gp2 mutant that reduced charge density by 33%, maintained net charge, and improved charge distribution homogeneity while elevating thermal stability ( T = 87 ± 1 °C), improving binding specificity, and maintaining affinity ( K = 8.8 ± 0.6 nM). This molecule was conjugated with 1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid for Cu chelation and evaluated for physiological distribution in mice with xenografted A431 (EGFR) and MDA-MB-435 (EGFR) tumors. Excised tissue gamma counting and positron emission tomography/computed tomography imaging revealed good EGFR tumor signal (4.7 ± 0.5%ID/g) at 2 h post-injection and molecular specificity evidenced by low uptake in EGFR tumors (0.6 ± 0.1%ID/g, significantly lower than for non-charge-modified Gp2, p = 0.01). These results provide charge mutations for an improved Gp2 framework, validate an effective approach to charge engineering, and advance performance of physiological EGFR targeting for molecular imaging.