Tuning antibody stability and function by rational designs of framework mutations

Tuning antibody stability and function by rational designs of framework mutations

Artificial intelligence and machine learning models have been developed to engineer antibodies for specific recognition of antigens. These approaches, however, often focus on the antibody complementarity-determining region (CDR) whilst ignoring the immunoglobulin framework (FW), which provides struc...

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Bibliographic Details
Main Authors: Joseph C. F. Ng, Alicia Chenoweth, Maria Laura De Sciscio, Melanie Grandits, Anthony Cheung, Tooki Chu, Alexandra McCraw, Jitesh Chauhan, Yi Liu, Dongjun Guo, Semil Patel, Alice Kosmider, Daniela Iancu, Sophia N. Karagiannis, Franca Fraternali
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:mAbs
Subjects:
Antibody framework
Antibody engineering
Antibody effector functions
Antibody stability
Artificial intelligence
Antibody language models
Online Access:https://www.tandfonline.com/doi/10.1080/19420862.2025.2532117
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https://www.tandfonline.com/doi/10.1080/19420862.2025.2532117

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