Automated optimisation of solubility and conformational stability of antibodies and proteins.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
06 04 2023
06 04 2023
Historique:
received:
22
10
2022
accepted:
24
03
2023
medline:
10
4
2023
entrez:
6
4
2023
pubmed:
7
4
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37024501
doi: 10.1038/s41467-023-37668-6
pii: 10.1038/s41467-023-37668-6
pmc: PMC10079162
doi:
Substances chimiques
Antibodies
0
Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1937Informations de copyright
© 2023. The Author(s).
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