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2015;7 (6): 1045-57.

Antibody humanization by structure-based computational protein design.

Yoonjoo Choi, Casey Hua, Charles L Sentman, Margaret E Ackerman, Chris Bailey-Kellogg
Author Information
  1. Yoonjoo Choi: a Department of Computer Science ; Dartmouth College ; Hanover , NH USA.
  2. Casey Hua: b Thayer School of Engineering; Dartmouth College ; Hanover , NH USA.
  3. Charles L Sentman: c Department of Microbiology and Immunology ; Geisel School of Medicine; Dartmouth College ; Lebanon , NH USA.
  4. Margaret E Ackerman: b Thayer School of Engineering; Dartmouth College ; Hanover , NH USA.
  5. Chris Bailey-Kellogg: a Department of Computer Science ; Dartmouth College ; Hanover , NH USA.
PMID: 26252731 DOI: 10.1080/19420862.2015.1076600

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.

Keywords

antibody computational protein design human string content humanization pareto optimization protein structure analysis

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Grants

  1. R01 GM098977/NIGMS NIH HHS
  2. 5P30GM10345/NIGMS NIH HHS
  3. R01-GM-098977/NIGMS NIH HHS

MeSH Term

Animals
Antibodies, Monoclonal, Humanized
Complementarity Determining Regions
Computational Biology
Drug Design
Humans
Immunoglobulin G
Immunoglobulin Variable Region
Mice
Models, Molecular
Prospective Studies
Protein Conformation
Protein Engineering
Retrospective Studies

Chemicals

Antibodies, Monoclonal, Humanized
Complementarity Determining Regions
Immunoglobulin G
Immunoglobulin Variable Region
Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.
Article has an altmetric score of 12

Word Cloud

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