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Automated optimisation of solubility and conformational stability of antibodies and proteins

Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning d...

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Autores principales: Rosace, Angelo, Bennett, Anja, Oeller, Marc, Mortensen, Mie M., Sakhnini, Laila, Lorenzen, Nikolai, Poulsen, Christian, Sormanni, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079162/
https://www.ncbi.nlm.nih.gov/pubmed/37024501
http://dx.doi.org/10.1038/s41467-023-37668-6
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author Rosace, Angelo
Bennett, Anja
Oeller, Marc
Mortensen, Mie M.
Sakhnini, Laila
Lorenzen, Nikolai
Poulsen, Christian
Sormanni, Pietro
author_facet Rosace, Angelo
Bennett, Anja
Oeller, Marc
Mortensen, Mie M.
Sakhnini, Laila
Lorenzen, Nikolai
Poulsen, Christian
Sormanni, Pietro
author_sort Rosace, Angelo
collection PubMed
description Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.
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spelling pubmed-100791622023-04-07 Automated optimisation of solubility and conformational stability of antibodies and proteins Rosace, Angelo Bennett, Anja Oeller, Marc Mortensen, Mie M. Sakhnini, Laila Lorenzen, Nikolai Poulsen, Christian Sormanni, Pietro Nat Commun Article Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk. Nature Publishing Group UK 2023-04-06 /pmc/articles/PMC10079162/ /pubmed/37024501 http://dx.doi.org/10.1038/s41467-023-37668-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Rosace, Angelo
Bennett, Anja
Oeller, Marc
Mortensen, Mie M.
Sakhnini, Laila
Lorenzen, Nikolai
Poulsen, Christian
Sormanni, Pietro
Automated optimisation of solubility and conformational stability of antibodies and proteins
title Automated optimisation of solubility and conformational stability of antibodies and proteins
title_full Automated optimisation of solubility and conformational stability of antibodies and proteins
title_fullStr Automated optimisation of solubility and conformational stability of antibodies and proteins
title_full_unstemmed Automated optimisation of solubility and conformational stability of antibodies and proteins
title_short Automated optimisation of solubility and conformational stability of antibodies and proteins
title_sort automated optimisation of solubility and conformational stability of antibodies and proteins
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079162/
https://www.ncbi.nlm.nih.gov/pubmed/37024501
http://dx.doi.org/10.1038/s41467-023-37668-6
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