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Five computational developability guidelines for therapeutic antibody profiling

Therapeutic mAbs must not only bind to their target but must also be free from “developability issues” such as poor stability or high levels of aggregation. While small-molecule drug discovery benefits from Lipinski’s rule of five to guide the selection of molecules with appropriate biophysical prop...

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Autores principales: Raybould, Matthew I. J., Marks, Claire, Krawczyk, Konrad, Taddese, Bruck, Nowak, Jaroslaw, Lewis, Alan P., Bujotzek, Alexander, Shi, Jiye, Deane, Charlotte M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410772/
https://www.ncbi.nlm.nih.gov/pubmed/30765520
http://dx.doi.org/10.1073/pnas.1810576116
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author Raybould, Matthew I. J.
Marks, Claire
Krawczyk, Konrad
Taddese, Bruck
Nowak, Jaroslaw
Lewis, Alan P.
Bujotzek, Alexander
Shi, Jiye
Deane, Charlotte M.
author_facet Raybould, Matthew I. J.
Marks, Claire
Krawczyk, Konrad
Taddese, Bruck
Nowak, Jaroslaw
Lewis, Alan P.
Bujotzek, Alexander
Shi, Jiye
Deane, Charlotte M.
author_sort Raybould, Matthew I. J.
collection PubMed
description Therapeutic mAbs must not only bind to their target but must also be free from “developability issues” such as poor stability or high levels of aggregation. While small-molecule drug discovery benefits from Lipinski’s rule of five to guide the selection of molecules with appropriate biophysical properties, there is currently no in silico analog for antibody design. Here, we model the variable domain structures of a large set of post-phase-I clinical-stage antibody therapeutics (CSTs) and calculate in silico metrics to estimate their typical properties. In each case, we contextualize the CST distribution against a snapshot of the human antibody gene repertoire. We describe guideline values for five metrics thought to be implicated in poor developability: the total length of the complementarity-determining regions (CDRs), the extent and magnitude of surface hydrophobicity, positive charge and negative charge in the CDRs, and asymmetry in the net heavy- and light-chain surface charges. The guideline cutoffs for each property were derived from the values seen in CSTs, and a flagging system is proposed to identify nonconforming candidates. On two mAb drug discovery sets, we were able to selectively highlight sequences with developability issues. We make available the Therapeutic Antibody Profiler (TAP), a computational tool that builds downloadable homology models of variable domain sequences, tests them against our five developability guidelines, and reports potential sequence liabilities and canonical forms. TAP is freely available at opig.stats.ox.ac.uk/webapps/sabdab-sabpred/TAP.php.
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spelling pubmed-64107722019-03-13 Five computational developability guidelines for therapeutic antibody profiling Raybould, Matthew I. J. Marks, Claire Krawczyk, Konrad Taddese, Bruck Nowak, Jaroslaw Lewis, Alan P. Bujotzek, Alexander Shi, Jiye Deane, Charlotte M. Proc Natl Acad Sci U S A Physical Sciences Therapeutic mAbs must not only bind to their target but must also be free from “developability issues” such as poor stability or high levels of aggregation. While small-molecule drug discovery benefits from Lipinski’s rule of five to guide the selection of molecules with appropriate biophysical properties, there is currently no in silico analog for antibody design. Here, we model the variable domain structures of a large set of post-phase-I clinical-stage antibody therapeutics (CSTs) and calculate in silico metrics to estimate their typical properties. In each case, we contextualize the CST distribution against a snapshot of the human antibody gene repertoire. We describe guideline values for five metrics thought to be implicated in poor developability: the total length of the complementarity-determining regions (CDRs), the extent and magnitude of surface hydrophobicity, positive charge and negative charge in the CDRs, and asymmetry in the net heavy- and light-chain surface charges. The guideline cutoffs for each property were derived from the values seen in CSTs, and a flagging system is proposed to identify nonconforming candidates. On two mAb drug discovery sets, we were able to selectively highlight sequences with developability issues. We make available the Therapeutic Antibody Profiler (TAP), a computational tool that builds downloadable homology models of variable domain sequences, tests them against our five developability guidelines, and reports potential sequence liabilities and canonical forms. TAP is freely available at opig.stats.ox.ac.uk/webapps/sabdab-sabpred/TAP.php. National Academy of Sciences 2019-03-05 2019-02-14 /pmc/articles/PMC6410772/ /pubmed/30765520 http://dx.doi.org/10.1073/pnas.1810576116 Text en Copyright © 2019 the Author(s). Published by PNAS. http://creativecommons.org/licenses/by/4.0/ This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Physical Sciences
Raybould, Matthew I. J.
Marks, Claire
Krawczyk, Konrad
Taddese, Bruck
Nowak, Jaroslaw
Lewis, Alan P.
Bujotzek, Alexander
Shi, Jiye
Deane, Charlotte M.
Five computational developability guidelines for therapeutic antibody profiling
title Five computational developability guidelines for therapeutic antibody profiling
title_full Five computational developability guidelines for therapeutic antibody profiling
title_fullStr Five computational developability guidelines for therapeutic antibody profiling
title_full_unstemmed Five computational developability guidelines for therapeutic antibody profiling
title_short Five computational developability guidelines for therapeutic antibody profiling
title_sort five computational developability guidelines for therapeutic antibody profiling
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410772/
https://www.ncbi.nlm.nih.gov/pubmed/30765520
http://dx.doi.org/10.1073/pnas.1810576116
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