Research Data Leeds Repository

Data associated with 'An in vivo platform to select and evolve aggregation-resistant proteins'

Ebo, Jessica S. and Saunders, Janet C. and Devine, Paul W. A. and Gordon, Alice M. and Warwick, Amy S. and Schiffrin, Bob and Chin, Stacey E. and England, Elizabeth and Button, James D. and Lloyd, Christopher and Bond, Nicholas J. and Ashcroft, Alison E. and Radford, Sheena E. and Lowe, David C. and Brockwell, David J., AstraZeneca (2019) Data associated with 'An in vivo platform to select and evolve aggregation-resistant proteins'. University of Leeds. [Dataset]

Dataset description

Protein biopharmaceuticals are highly successful, but their utility is compromised by their propensity to aggregate during manufacture and storage. As aggregation can be triggered by non-native states, whose population is not necessarily related to thermodynamic stability, prediction of poorly-behaving biologics is difficult, and searching for sequences with desired properties is labour-intensive and time-consuming. Here we show that an assay in the periplasm of E. coli linking aggregation directly to antibiotic resistance acts as a sensor for the innate (un-accelerated) aggregation of antibody fragments. Using this assay as a directed evolution screen, we demonstrate the generation of aggregation resistant scFv sequences when reformatted as IgGs. This powerful tool can thus screen and evolve ‘manufacturable’ biopharmaceuticals early in industrial development. By comparing the mutational profiles of three different immunoglobulin scaffolds, we show the applicability of this method to investigate protein aggregation mechanisms important to both industrial manufacture and amyloid disease.

Keywords: Protein aggregation, biopharmaceuticals, directed evolution
Subjects: C000 - Biological sciences > C700 - Molecular biology, biophysics & biochemistry
Divisions: Faculty of Biological Sciences > Astbury Centre for Structural Molecular Biology
Faculty of Biological Sciences > School of Molecular and Cellular Biology
Related resources:
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 03 Dec 2019 14:32



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