Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability

Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability

Rabbits produce robust antibody responses and have unique features in their antibody repertoire that make them an attractive alternative to rodents for in vivo discovery. However, the frequent occurrence of a non-canonical disulfide bond between complementarity-determining region (CDR) H1 (C35a) and...

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Bibliographic Details
Main Authors: Wei-Ching Liang, Hongkang Xi, Dawei Sun, Luigi D’Ascenzo, Jonathan Zarzar, Nicole Stephens, Ryan Cook, Yinyin Li, Zhengmao Ye, Marissa Matsumoto, Jian Payandeh, Matthieu Masureel, Yan Wu
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:mAbs
Subjects:
Complementarity determining regions (CDRs)
disulfide bond
humanization
ML/AI-guided protein design
Programmed cell death (PD-1)
Rabbit monoclonal antibody (mab)
Online Access:https://www.tandfonline.com/doi/10.1080/19420862.2024.2309685
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https://www.tandfonline.com/doi/10.1080/19420862.2024.2309685

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