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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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | mAbs |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19420862.2024.2309685 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Wei-Ching Liang |
| collection | DOAJ |
| description | 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 CDRH2 (C50) is often seen as a liability for therapeutic antibody development, despite limited reports of its effect on antibody binding, function, and stability. Here, we describe the discovery and humanization of a human-mouse cross-reactive anti-programmed cell death (PD-1) monoclonal rabbit antibody, termed h1340.CC, which possesses this non-canonical disulfide bond. Initial removal of the non-canonical disulfide resulted in a loss of PD-1 affinity and cross-reactivity, which led us to explore protein engineering approaches to recover these. First, guided by the sequence of a related clone and the crystal structure of h1340.CC in complex with PD-1, we generated variant h1340.SA.LV with a potency and cross-reactivity similar to h1340.CC, but only partially recovered affinity. Side-by-side developability assessment of both h1340.CC and h1340.SA.LV indicate that they possess similar, favorable properties. Next, and prompted by recent developments in machine learning (ML)-guided protein engineering, we used an unbiased ML- and structure-guided approach to rapidly and efficiently generate a different variant with recovered affinity. Our case study thus indicates that, while the non-canonical inter-CDR disulfide bond found in rabbit antibodies does not necessarily constitute an obstacle to therapeutic antibody development, combining structure- and ML-guided approaches can provide a fast and efficient way to improve antibody properties and remove potential liabilities. |
| format | Article |
| id | doaj-art-1a518cc319b3400f9a88d53703dfd80c |
| institution | Kabale University |
| issn | 1942-0862 1942-0870 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | mAbs |
| spelling | doaj-art-1a518cc319b3400f9a88d53703dfd80c2025-01-31T04:19:38ZengTaylor & Francis GroupmAbs1942-08621942-08702024-12-0116110.1080/19420862.2024.2309685Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developabilityWei-Ching Liang0Hongkang Xi1Dawei Sun2Luigi D’Ascenzo3Jonathan Zarzar4Nicole Stephens5Ryan Cook6Yinyin Li7Zhengmao Ye8Marissa Matsumoto9Jian Payandeh10Matthieu Masureel11Yan Wu12Department of Antibody Engineering, Genentech Inc, South San Francisco, CA, USADepartment of Antibody Engineering, Genentech Inc, South San Francisco, CA, USADepartment of Structural Biology, Genentech Inc, South San Francisco, CA, USADepartment of Structural Biology, Genentech Inc, South San Francisco, CA, USADepartment of Pharma Technical Development, Genentech Inc, South San Francisco, CA, USADepartment of Pharma Technical Development, Genentech Inc, South San Francisco, CA, USADepartment of Biochemical and Cellular Pharmacology, Genentech Inc, South San Francisco, CA, USADepartment of Biochemical and Cellular Pharmacology, Genentech Inc, South San Francisco, CA, USADepartment of Biochemical and Cellular Pharmacology, Genentech Inc, South San Francisco, CA, USADepartment of Structural Biology, Genentech Inc, South San Francisco, CA, USADepartment of Structural Biology, Genentech Inc, South San Francisco, CA, USADepartment of Structural Biology, Genentech Inc, South San Francisco, CA, USADepartment of Antibody Engineering, Genentech Inc, South San Francisco, CA, USARabbits 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 CDRH2 (C50) is often seen as a liability for therapeutic antibody development, despite limited reports of its effect on antibody binding, function, and stability. Here, we describe the discovery and humanization of a human-mouse cross-reactive anti-programmed cell death (PD-1) monoclonal rabbit antibody, termed h1340.CC, which possesses this non-canonical disulfide bond. Initial removal of the non-canonical disulfide resulted in a loss of PD-1 affinity and cross-reactivity, which led us to explore protein engineering approaches to recover these. First, guided by the sequence of a related clone and the crystal structure of h1340.CC in complex with PD-1, we generated variant h1340.SA.LV with a potency and cross-reactivity similar to h1340.CC, but only partially recovered affinity. Side-by-side developability assessment of both h1340.CC and h1340.SA.LV indicate that they possess similar, favorable properties. Next, and prompted by recent developments in machine learning (ML)-guided protein engineering, we used an unbiased ML- and structure-guided approach to rapidly and efficiently generate a different variant with recovered affinity. Our case study thus indicates that, while the non-canonical inter-CDR disulfide bond found in rabbit antibodies does not necessarily constitute an obstacle to therapeutic antibody development, combining structure- and ML-guided approaches can provide a fast and efficient way to improve antibody properties and remove potential liabilities.https://www.tandfonline.com/doi/10.1080/19420862.2024.2309685Complementarity determining regions (CDRs)disulfide bondhumanizationML/AI-guided protein designProgrammed cell death (PD-1)Rabbit monoclonal antibody (mab) |
| spellingShingle | 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 Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability mAbs Complementarity determining regions (CDRs) disulfide bond humanization ML/AI-guided protein design Programmed cell death (PD-1) Rabbit monoclonal antibody (mab) |
| title | Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability |
| title_full | Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability |
| title_fullStr | Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability |
| title_full_unstemmed | Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability |
| title_short | Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability |
| title_sort | structure and machine learning guided engineering demonstrate that a non canonical disulfide in an anti pd 1 rabbit antibody does not impede antibody developability |
| topic | Complementarity determining regions (CDRs) disulfide bond humanization ML/AI-guided protein design Programmed cell death (PD-1) Rabbit monoclonal antibody (mab) |
| url | https://www.tandfonline.com/doi/10.1080/19420862.2024.2309685 |
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