Summary Small protein ligands can provide superior physiological distribution versus antibodies and improved stability, production, and specific conjugation. Systematic evaluation of the Protein Data Bank identified a scaffold to push the limits of small size and robust evolution of stable, high-affinity ligands: 45-residue T7 phage gene 2 protein (Gp2) contains an α-helix opposite a β-sheet with two adjacent loops amenable to mutation. De novo ligand discovery from 108 mutants and directed evolution towards four targets yielded target-specific binders with affinities as strong as 200 ±100 pM, Tm’s from 65 ±3 °C to 80 ±1 °C, and retained activity after thermal denaturation. For cancer targeting, a Gp2 domain for epidermal growth factor receptor was evolved with 18 ±8 nM affinity, receptor-specific binding, and high thermal stability with refolding. The efficiency of evolving new binding function and the size, affinity, specificity, and stability of evolved domains render Gp2 a uniquely effective ligand scaffold.
Discovering new binding function via a combinatorial library in small protein scaffolds requires balance between appropriate mutations to introduce favorable intermolecular interactions while maintaining intramolecular integrity. Sitewise constraints exist in a non-spatial gradient from diverse to conserved in evolved antibody repertoires; yet non-antibody scaffolds generally do not implement this strategy in combinatorial libraries. Despite the fact that biased amino acid distributions, typically elevated in tyrosine, serine, and glycine, have gained wider use in synthetic scaffolds, these distributions are still predominantly applied uniformly to diversified sites. While select sites in fibronectin domains and DARPins have shown benefit from sitewise designs, they have not been deeply evaluated. Inspired by this disparity between diversity distributions in natural libraries and synthetic scaffold libraries, we hypothesized that binders resulting from discovery and evolution would exhibit a non-spatial, sitewise gradient of amino acid diversity. To identify sitewise diversities consistent with efficient evolution in the context of a hydrophilic fibronectin domain, >105 binders to six targets were evolved and sequenced. Evolutionarily favorable amino acid distributions at 25 sites reveal Shannon entropies (range: 0.3–3.9; median: 2.1; standard deviation: 1.1) supporting the diversity gradient hypothesis. Sitewise constraints in evolved sequences are consistent with complementarity, stability, and consensus biases. Implementation of sitewise constrained diversity enables direct selection of nanomolar affinity binders validating an efficient strategy to balance inter- and intra-molecular interaction demands at each site.
Yeast surface display selections against mammalian cell monolayers have proven effective in isolating proteins with novel binding activity. Recent advances in this technique allow for recovery of clones with even micromolar binding affinity. However, no efficient method has been shown for affinity based selection in this context. This study demonstrates the effectiveness of titratable avidity reduction using dithiothreitol (DTT) to achieve this goal. A series of epidermal growth factor receptor binding fibronectin domains with a range of affinities are used to quantitatively identify the number of ligands per yeast cell that yield the strongest selectivity between strong, moderate, and weak affinities. Notably, reduction of ligand display to 3,000 – 6,000 ligands per yeast cell yields 16-fold selectivity of a 2 nM binder relative to a 17 nM binder. These lessons are applied to affinity maturation of an EpCAM-binding fibronectin population, yielding an enriched pool of ligands with significantly stronger affinity than an analogous pool sorted by standard cellular selection methods. Collectively, this study offers a facile approach for affinity selection of yeast displayed ligands against full length cellular targets and demonstrates the effectiveness of this method by generating EpCAM-binding ligands that are promising for further applications.
Engineered proteins provide clinically and industrially impactful molecules and utility within fundamental research. Yet, inefficiencies in discovering lead variants with new desired function, while maintaining stability, hinder progress. Improved function, which can result from a few strategic mutations, is fundamentally separate from discovering novel function, which often requires large leaps in sequence space. While a highly diverse combinatorial library covering immense sequence space would empower protein discovery, the ability to sample only a minor subset of sequence space and the typical destabilization of random mutations preclude this strategy. A balance must be reached. At library scale, compounding several destabilizing mutations renders many variants unable to properly fold and devoid of function. Broadly searching sequence space while reducing destabilization may enhance evolution. We exemplify this balance with affibody, a three-helix bundle protein scaffold. Using natural ligand datasets, stability and structural computations, and deep sequencing thousands of binding variants, a protein library was designed on a sitewise basis with a gradient of mutational levels across 29% of the protein. In direct competition of biased and uniform libraries, both with 1×109 variants, for discovery of 6×104 ligands (5×103 clusters) toward seven targets, biased amino acid frequency increased ligand discovery 13±3-fold. Evolutionarily favorable amino acids, both globally and site-specifically, are further elucidated. The sitewise amino acid bias aids evolutionary discovery by reducing mutant destabilization as evidenced by 15°C higher midpoint of denaturation relative to unbiased mutants (62±4°C vs. 47±11°C, p<0.001). Sitewise diversification, identified by high throughput evolution and rational library design, improves discovery efficiency.
Background: Extracellular vesicles (EVs) are attracting interest as a new class of drug delivery vehicles due to their intrinsic nature of biomolecular transport in the body. We previously demonstrated that EV surface modification with tissue-specific molecules accomplished targeted EV-mediated DNA delivery. Methods: Here, we describe reliable methods for (i) generating EGFR tumor-targeting EVs via the display of high-affinity monobodies and (ii) in vitro measurement of EV binding using fluorescence and bioluminescence labeling. Monobodies are a well-suited class of small (10 kDa) non-antibody scaffolds derived from the human fibronectin type III (FN3) domain. Results: The recombinant protein consists of the EGFR-targeting monobody fused to the EV-binding domain of lactadherin (C1C2), enabling the monobody displayed on the surface of the EVs. In addition, the use of bioluminescence or fluorescence molecules on the EV surface allows for the assessment of EV binding to the target cells. Conclusions: In this paper, we describe methods of EV engineering to generate targeted delivery vehicles using monobodies that will have diverse applications to furnish future EV therapeutic development, including qualitative and quantitative in vitro evaluation for their binding capacity.
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