Tuning antibody stability and function by rational designs of framework mutations Article Swipe
Joseph Ng
,
Alicia M. Chenoweth
,
Maria Laura De Sciscio
,
Melanie Grandits
,
Anthony Cheung
,
T. Ming Chu
,
Alexandra McCraw
,
Jitesh Chauhan
,
Yi Liu
,
Dongjun Guo
,
S. Patel
,
Alice Kosmider
,
Daniela Iancu
,
Sophia N. Karagiannis
,
Franca Fraternali
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1080/19420862.2025.2532117
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1080/19420862.2025.2532117
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 structural rigidity and support for the flexible CDR loops. Here we present an integrated computational-experimental workflow, combining static structure analyses, molecular dynamics simulations and in vitro physicochemical and functional assays to generate rational designs of FW mutations for modulating antibody stability and activity. We first showed that recent antibody-specific language models lacked insights in FW mutagenesis, in comparison to approaches that use antibody structure information. Using the widely used breast cancer therapeutic trastuzumab as a use case, we designed stabilizing mutants which were distal to the CDR and preserved the antibody's functionality to engage its cognate antigen (HER2) and induce antibody-dependent cellular cytotoxicity. Interestingly, guided by local backbone motions predicted using molecular dynamics simulations, we designed a FW mutation on the trastuzumab light chain that retained antigen-binding effects, but lost Fab-mediated and Fc-mediated effector functions. This highlighted the effects of FW on immunological functions engendered in distal areas of the antibody, and the importance of considering attributes other than binding affinity when assessing antibody function. Our approach incorporates interdomain dynamics and distal effects between FW and the Fc domains, expands the scope of antibody engineering beyond the CDR, and underscores the importance of a holistic perspective that considers the entire antibody structure in optimizing antibody stability, developability and function.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/19420862.2025.2532117
- OA Status
- gold
- References
- 90
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412382030
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4412382030Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/19420862.2025.2532117Digital Object Identifier
- Title
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Tuning antibody stability and function by rational designs of framework mutationsWork title
- Type
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articleOpenAlex work type
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-13Full publication date if available
- Authors
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Joseph Ng, Alicia M. Chenoweth, Maria Laura De Sciscio, Melanie Grandits, Anthony Cheung, T. Ming Chu, Alexandra McCraw, Jitesh Chauhan, Yi Liu, Dongjun Guo, S. Patel, Alice Kosmider, Daniela Iancu, Sophia N. Karagiannis, Franca FraternaliList of authors in order
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https://doi.org/10.1080/19420862.2025.2532117Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1080/19420862.2025.2532117Direct OA link when available
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Function (biology), Rational design, Stability (learning theory), Antibody, Computational biology, Computer science, Chemistry, Biology, Genetics, Machine learningTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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