TY - JOUR
T1 - Automated optimisation of solubility and conformational stability of antibodies and proteins
AU - Rosace, Angelo
AU - Bennett, Anja
AU - Oeller, Marc
AU - Mortensen, Mie M.
AU - Sakhnini, Laila
AU - Lorenzen, Nikolai
AU - Poulsen, Christian
AU - Sormanni, Pietro
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85151881163&partnerID=8YFLogxK
U2 - 10.1038/s41467-023-37668-6
DO - 10.1038/s41467-023-37668-6
M3 - Journal article
C2 - 37024501
AN - SCOPUS:85151881163
SN - 2041-1723
VL - 14
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 1937
ER -