Back to Search
Start Over
Antibody humanization by molecular dynamics simulations-in-silico guided selection of critical backmutations
- Source :
- Journal of Molecular Recognition
- Publication Year :
- 2015
-
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.
- Subjects :
- Models, Molecular
Binding Sites
conformational clustering
antibody humanization
CHO Cells
Molecular Dynamics Simulation
Antibodies, Monoclonal, Humanized
Complementarity Determining Regions
molecular dynamics
GROMOS
Cricetulus
HEK293 Cells
Drug Design
Mutation
binding affinity
Animals
Humans
Computer Simulation
Amino Acid Sequence
Research Articles
Research Article
Subjects
Details
- ISSN :
- 10991352
- Volume :
- 29
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Journal of molecular recognition : JMR
- Accession number :
- edsair.pmid..........87d4fcb00658ecf3ddec6fc599829c8d