Dataset Information

Titratable Avidity Reduction Enhances Affinity Discrimination in Mammalian Cellular Selections of Yeast-Displayed Ligands.

ABSTRACT: 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 the recovery of clones with even micromolar binding affinities. 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 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 of a 2 nM binder yields 16-fold better selectivity than that 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 that of 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.

SUBMITTER: Stern LA

PROVIDER: S-EPMC5521271 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Titratable Avidity Reduction Enhances Affinity Discrimination in Mammalian Cellular Selections of Yeast-Displayed Ligands.

Stern Lawrence A LA Csizmar Clifford M CM Woldring Daniel R DR Wagner Carston R CR Hackel Benjamin J BJ

ACS combinatorial science 20170331 5

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 the recovery of clones with even micromolar binding affinities. 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 to achieve this goal. A series of epidermal growth factor receptor ...[more]

PMID: 28322543

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Project description:Self-association governs the viscosity and solubility of therapeutic antibodies in high-concentration formulations used for subcutaneous delivery, yet it is difficult to reliably identify candidates with low self-association during antibody discovery and early-stage optimization. Here, we report a high-throughput protein engineering method for rapidly identifying antibody candidates with both low self-association and high affinity. We find that conjugating quantum dots to IgGs that strongly self-associate (pH 7.4, PBS), such as lenzilumab and bococizumab, results in immunoconjugates that are highly sensitive for detecting other high self-association antibodies. Moreover, these conjugates can be used to rapidly enrich yeast-displayed bococizumab sub-libraries for variants with low levels of immunoconjugate binding. Deep sequencing and machine learning analysis of the enriched bococizumab libraries, along with similar library analysis for antibody affinity, enabled identification of extremely rare variants with co-optimized levels of low self-association and high affinity. This analysis revealed that co-optimizing bococizumab is difficult because most high-affinity variants possess positively charged variable domains and most low self-association variants possess negatively charged variable domains. Moreover, negatively charged mutations in the heavy chain CDR2 of bococizumab, adjacent to its paratope, were effective at reducing self-association without reducing affinity. Interestingly, most of the bococizumab variants with reduced self-association also displayed improved folding stability and reduced nonspecific binding, revealing that this approach may be particularly useful for identifying antibody candidates with attractive combinations of drug-like properties.Abbreviations: AC-SINS: affinity-capture self-interaction nanoparticle spectroscopy; CDR: complementarity-determining region; CS-SINS: charge-stabilized self-interaction nanoparticle spectroscopy; FACS: fluorescence-activated cell sorting; Fab: fragment antigen binding; Fv: fragment variable; IgG: immunoglobulin; QD: quantum dot; PBS: phosphate-buffered saline; VH: variable heavy; VL: variable light.

Dataset Information

Titratable Avidity Reduction Enhances Affinity Discrimination in Mammalian Cellular Selections of Yeast-Displayed Ligands.

Publications

Titratable Avidity Reduction Enhances Affinity Discrimination in Mammalian Cellular Selections of Yeast-Displayed Ligands.

Similar Datasets

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