title: Antibody humanization by structure-based computational protein design.
abstract: Antibodies derived from non-human sources must be modified for therapeutic use so as to mitigate undesirable immune responses. While complementarity-determining region (CDR) grafting-based humanization techniques have been successfully applied in many cases, it remains challenging to maintain the desired stability and antigen binding affinity upon grafting. We developed an alternative humanization approach called CoDAH ("Computationally-Driven Antibody Humanization") in which computational protein design methods directly select sets of amino acids to incorporate from human germline sequences to increase humanness while maintaining structural stability. Retrospective studies show that CoDAH is able to identify variants deemed beneficial according to both humanness and structural stability criteria, even for targets lacking crystal structures. Prospective application to TZ47, a murine anti-human B7H6 antibody, demonstrates the approach. Four diverse humanized variants were designed, and all possible unique VH/VL combinations were produced as full-length IgG1 antibodies. Soluble and cell surface expressed antigen binding assays showed that 75% (6 of 8) of the computationally designed VH/VL variants were successfully expressed and competed with the murine TZ47 for binding to B7H6 antigen. Furthermore, 4 of the 6 bound with an estimated KD within an order of magnitude of the original TZ47 antibody. In contrast, a traditional CDR-grafted variant could not be expressed. These results suggest that the computational protein design approach described here can be used to efficiently generate functional humanized antibodies and provide humanized templates for further affinity maturation.
authors.affiliation: a Department of Computer Science ; Dartmouth College ; Hanover , NH USA.
authors.forename: Yoonjoo
authors.initials: Y
authors.lastname: Choi
authors.affiliation: b Thayer School of Engineering; Dartmouth College ; Hanover , NH USA.|c Department of Microbiology and Immunology ; Geisel School of Medicine; Dartmouth College ; Lebanon , NH USA.
authors.forename: Casey
authors.initials: C
authors.lastname: Hua
authors.affiliation: c Department of Microbiology and Immunology ; Geisel School of Medicine; Dartmouth College ; Lebanon , NH USA.
authors.forename: Charles L
authors.initials: CL
authors.lastname: Sentman
authors.affiliation: b Thayer School of Engineering; Dartmouth College ; Hanover , NH USA.|c Department of Microbiology and Immunology ; Geisel School of Medicine; Dartmouth College ; Lebanon , NH USA.
authors.forename: Margaret E
authors.initials: ME
authors.lastname: Ackerman
authors.affiliation: a Department of Computer Science ; Dartmouth College ; Hanover , NH USA.
authors.forename: Chris
authors.initials: C
authors.lastname: Bailey-Kellogg
mesh_terms: D000818:Animals; D061067:Antibodies, Monoclonal, Humanized / Q000737:chemistry / Q000235:genetics / Q000276:immunology*; D022801:Complementarity Determining Regions / Q000737:chemistry / Q000235:genetics / Q000276:immunology; D019295:Computational Biology / Q000379:methods*; D015195:Drug Design; D006801:Humans; D007074:Immunoglobulin G / Q000737:chemistry / Q000235:genetics / Q000276:immunology; D007135:Immunoglobulin Variable Region / Q000737:chemistry / Q000235:genetics / Q000276:immunology; D051379:Mice; D008958:Models, Molecular; D011446:Prospective Studies; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods*; D012189:Retrospective Studies
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D022801:Complementarity Determining Regions; D007074:Immunoglobulin G; D007135:Immunoglobulin Variable Region
keywords: antibody; computational protein design; human string content; humanization; pareto optimization; protein structure analysis