10.22025/CAMSTAG2.54629
Norman, Richard A
Ambrosetti, Francesco
Bonvin, Alexandre M J J
Colwell, Lucy J
Kelm, Sebastian
Kumar, Sandeep
Krawczyk, Konrad
Computational approaches to therapeutic antibody design: established methods and emerging trends.
Apollo - University of Cambridge Repository (staging)
2019
antibody–antigen complexes
databases
docking
homology modelling
therapeutic antibodies
Apollo - University of Cambridge Repository (staging)
Apollo - University of Cambridge Repository (staging)
2019-12-04
2019-12-04
2019-10-18
2019-04-25
2019-12-04
Article
https://dspace-staging.lib.cam.ac.uk/handle/1810/307361
1477-4054
31626279
5581643
10.1093/bib/bbz095
Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics. [Abstract copyright: © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.]