title: VH-VL orientation prediction for antibody humanization candidate selection: A case study.
abstract: Antibody humanization describes the procedure of grafting a non-human antibody's complementarity-determining regions, i.e., the variable loop regions that mediate specific interactions with the antigen, onto a β-sheet framework that is representative of the human variable region germline repertoire, thus reducing the number of potentially antigenic epitopes that might trigger an anti-antibody response. The selection criterion for the so-called acceptor frameworks (one for the heavy and one for the light chain variable region) is traditionally based on sequence similarity. Here, we propose a novel approach that selects acceptor frameworks such that the relative orientation of the 2 variable domains in 3D space, and thereby the geometry of the antigen-binding site, is conserved throughout the process of humanization. The methodology relies on a machine learning-based predictor of antibody variable domain orientation that has recently been shown to improve the quality of antibody homology models. Using data from 3 humanization campaigns, we demonstrate that preselecting humanization variants based on the predicted difference in variable domain orientation with regard to the original antibody leads to subsets of variants with a significant improvement in binding affinity.
authors.affiliation: a Roche Pharmaceutical Research and Early Development, Large Molecule Research, Roche Innovation Center Penzberg , Nonnenwald 2, Penzberg , Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Bujotzek
authors.affiliation: b Roche Pharmaceutical Research and Early Development, Informatics, Roche Innovation Center Penzberg , Nonnenwald 2, Penzberg , Germany.
authors.forename: Florian
authors.initials: F
authors.lastname: Lipsmeier
authors.affiliation: c Genentech, Inc., Structural Biology Department , 1 DNA Way, South San Francisco , California 94080 , USA.
authors.forename: Seth F
authors.initials: SF
authors.lastname: Harris
authors.affiliation: d Roche Pharmaceutical Research and Early Development, Small Molecule Research, Roche Innovation Center Basel , Grenzacherstrasse 124, Basel , Switzerland.
authors.forename: Jörg
authors.initials: J
authors.lastname: Benz
authors.affiliation: d Roche Pharmaceutical Research and Early Development, Small Molecule Research, Roche Innovation Center Basel , Grenzacherstrasse 124, Basel , Switzerland.
authors.forename: Andreas
authors.initials: A
authors.lastname: Kuglstatter
authors.affiliation: a Roche Pharmaceutical Research and Early Development, Large Molecule Research, Roche Innovation Center Penzberg , Nonnenwald 2, Penzberg , Germany.
authors.forename: Guy
authors.initials: G
authors.lastname: Georges
mesh_terms: D061067:Antibodies, Monoclonal, Humanized / Q000737:chemistry*; D022801:Complementarity Determining Regions / Q000737:chemistry*; D006801:Humans; D000069550:Machine Learning; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D040681:Structural Homology, Protein
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D022801:Complementarity Determining Regions
keywords: CDR grafting; antibody humanization; antibody variable domain orientation; monoclonal antibody