ArticleProtein engineering, design & selection : PEDS2023
abYpap: improvements to the prediction of antibody VH/VL packing using gradient boosted regression.
Article in Protein engineering, design & selection : PEDS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Conserved heavy/light contacts and germline preferences revealed by a large-scale analysis of natively paired human antibody sequences and structural data.Communications biology · 2025Article
- Structure-based humanization of a therapeutic antibody for multiple myeloma.Journal of molecular medicine (Berlin, Germany) · 2024Article
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2 authors.
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Abstract
The Fv region of the antibody (comprising VH and VL domains) is the area responsible for target binding and thus the antibody's specificity. The orientation, or packing, of these two domains relative to each other influences the topography of the Fv region, and therefore can influence the antibody's binding affinity. We present abYpap, an improved method for predicting the packing angle between the VH and VL domains. With the large data set now available, we were able to expand greatly the number of features that could be used compared with our previous work. The machine-learning model was tuned for improved performance using 37 selected residues (previously 13) and also by including the lengths of the most variable 'complementarity determining regions' (CDR-L1, CDR-L2 and CDR-H3). Our method shows large improvements from the previous version, and also against other modeling approaches, when predicting the packing angle.
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