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Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations

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...

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Autores principales: Margreitter, Christian, Mayrhofer, Patrick, Kunert, Renate, Oostenbrink, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4948679/
https://www.ncbi.nlm.nih.gov/pubmed/26748949
http://dx.doi.org/10.1002/jmr.2527
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author Margreitter, Christian
Mayrhofer, Patrick
Kunert, Renate
Oostenbrink, Chris
author_facet Margreitter, Christian
Mayrhofer, Patrick
Kunert, Renate
Oostenbrink, Chris
author_sort Margreitter, Christian
collection PubMed
description 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.
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spelling pubmed-49486792016-07-18 Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations Margreitter, Christian Mayrhofer, Patrick Kunert, Renate Oostenbrink, Chris J Mol Recognit Research Articles 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. John Wiley and Sons Inc. 2016-01-08 2016-06 /pmc/articles/PMC4948679/ /pubmed/26748949 http://dx.doi.org/10.1002/jmr.2527 Text en © 2016 The Authors Journal of Molecular Recognition Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Margreitter, Christian
Mayrhofer, Patrick
Kunert, Renate
Oostenbrink, Chris
Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
title Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
title_full Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
title_fullStr Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
title_full_unstemmed Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
title_short Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
title_sort antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4948679/
https://www.ncbi.nlm.nih.gov/pubmed/26748949
http://dx.doi.org/10.1002/jmr.2527
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