title: Antibody humanization by molecular dynamics simulations-in-silico guided selection of critical backmutations.
abstract: Monoclonal antibodies represent the fastest growing class of biotherapeutic proteins. However, as they are often initially derived from rodent organisms, there is a severe risk of immunogenic reactions, hampering their applicability. The humanization of these antibodies remains a challenging task in the context of rational drug design. "Superhumanization" describes the direct transfer of the complementarity determining regions to a human germline framework, but this humanization approach often results in loss of binding affinity. In this study, we present a new approach for predicting promising backmutation sites using molecular dynamics simulations of the model antibody Ab2/3H6. The simulation method was developed in close conjunction with novel specificity experiments. Binding properties of mAb variants were evaluated directly from crude supernatants and confirmed using established binding affinity assays for purified antibodies. Our approach provides access to the dynamical features of the actual binding sites of an antibody, based solely on the antibody sequence. Thus we do not need structural data on the antibody-antigen complex and circumvent cumbersome methods to assess binding affinities. © 2016 The Authors Journal of Molecular Recognition Published by John Wiley & Sons Ltd.
authors.affiliation: Institute of Molecular Modeling and Simulation, University of Natural Resources and Life Sciences, Muthgasse 18, Vienna, 1190, Austria.
authors.forename: Christian
authors.initials: C
authors.lastname: Margreitter
authors.affiliation: Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, Vienna, 1190, Austria.
authors.forename: Patrick
authors.initials: P
authors.lastname: Mayrhofer
authors.affiliation: Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, Vienna, 1190, Austria.
authors.forename: Renate
authors.initials: R
authors.lastname: Kunert
authors.affiliation: Institute of Molecular Modeling and Simulation, University of Natural Resources and Life Sciences, Muthgasse 18, Vienna, 1190, Austria.
authors.forename: Chris
authors.initials: C
authors.lastname: Oostenbrink
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D061067:Antibodies, Monoclonal, Humanized / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D001665:Binding Sites; D016466:CHO Cells; D022801:Complementarity Determining Regions / Q000737:chemistry / Q000235:genetics*; D003198:Computer Simulation; D003412:Cricetulus; D015195:Drug Design; D057809:HEK293 Cells; D006801:Humans; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D009154:Mutation
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D022801:Complementarity Determining Regions
keywords: GROMOS; antibody humanization; binding affinity; conformational clustering; molecular dynamics