Literature DB >> 28130326

Engineering the expression of an anti-interleukin-13 antibody through rational design and mutagenesis.

Bojana Popovic1, Suzanne Gibson2, Tarik Senussi2, Sara Carmen1, Sara Kidd1, Tim Slidel3, Ian Strickland4, Xu Jianqing1, Jennifer Spooner1, Amanda Lewis2, Nathan Hudson1, Lorna Mackenzie1, Jennifer Keen1, Ben Kemp1, Colin Hardman3, Diane Hatton2, Trevor Wilkinson1, Tristan Vaughan1, David Lowe1.   

Abstract

High levels of protein expression are key to the successful development and manufacture of a therapeutic antibody. Here, we describe two related antibodies, Ab001 and Ab008, where Ab001 shows a markedly lower level of expression relative to Ab008 when stably expressed in Chinese hamster ovary cells. We use single-gene expression vectors and structural analysis to show that the reduced titer is associated with the VL CDR2 of Ab001. We adopted two approaches to improve the expression of Ab001. First, we used mutagenesis to change single amino-acid residues in the Ab001 VL back to the equivalent Ab008 residues but this resulted in limited improvements in expression. In contrast when we used an in silico structure-based design approach to generate a set of five individual single-point variants in a discrete region of the VL, all exhibited significantly improved expression relative to Ab001. The most successful of these, D53N, exhibited a 25-fold increase in stable transfectants relative to Ab001. The functional potency of these VL-modified antibodies was unaffected. We expect that this in silico engineering strategy can be used to improve the expression of other antibodies and proteins.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  antibody dynamics; antibody engineering; antibody expression; antibody structure; structure-guided design

Mesh:

Substances:

Year:  2017        PMID: 28130326     DOI: 10.1093/protein/gzx001

Source DB:  PubMed          Journal:  Protein Eng Des Sel        ISSN: 1741-0126            Impact factor:   1.650


  4 in total

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Authors:  Claire Marks; Charlotte M Deane
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Authors:  Matthew I J Raybould; Charlotte M Deane
Journal:  Methods Mol Biol       Date:  2022

3.  Lessons learned from merging wet lab experiments with molecular simulation to improve mAb humanization.

Authors:  L Schwaigerlehner; M Pechlaner; P Mayrhofer; C Oostenbrink; R Kunert
Journal:  Protein Eng Des Sel       Date:  2018-07-01       Impact factor: 1.952

4.  Rational optimization of a monoclonal antibody improves the aggregation propensity and enhances the CMC properties along the entire pharmaceutical process chain.

Authors:  Joschka Bauer; Sven Mathias; Sebastian Kube; Kerstin Otte; Patrick Garidel; Martin Gamer; Michaela Blech; Simon Fischer; Anne R Karow-Zwick
Journal:  MAbs       Date:  2020 Jan-Dec       Impact factor: 5.857

  4 in total

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