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Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery

AlphaFold2 has hallmarked a generational improvement in protein structure prediction. In particular, advances in antibody structure prediction have provided a highly translatable impact on drug discovery. Though AlphaFold2 laid the groundwork for all proteins, antibody-specific applications require...

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Autores principales: Jaszczyszyn, Igor, Bielska, Weronika, Gawlowski, Tomasz, Dudzic, Pawel, Satława, Tadeusz, Kończak, Jarosław, Wilman, Wiktoria, Janusz, Bartosz, Wróbel, Sonia, Chomicz, Dawid, Galson, Jacob D., Leem, Jinwoo, Kelm, Sebastian, Krawczyk, Konrad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361724/
https://www.ncbi.nlm.nih.gov/pubmed/37484529
http://dx.doi.org/10.3389/fmolb.2023.1214424
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author Jaszczyszyn, Igor
Bielska, Weronika
Gawlowski, Tomasz
Dudzic, Pawel
Satława, Tadeusz
Kończak, Jarosław
Wilman, Wiktoria
Janusz, Bartosz
Wróbel, Sonia
Chomicz, Dawid
Galson, Jacob D.
Leem, Jinwoo
Kelm, Sebastian
Krawczyk, Konrad
author_facet Jaszczyszyn, Igor
Bielska, Weronika
Gawlowski, Tomasz
Dudzic, Pawel
Satława, Tadeusz
Kończak, Jarosław
Wilman, Wiktoria
Janusz, Bartosz
Wróbel, Sonia
Chomicz, Dawid
Galson, Jacob D.
Leem, Jinwoo
Kelm, Sebastian
Krawczyk, Konrad
author_sort Jaszczyszyn, Igor
collection PubMed
description AlphaFold2 has hallmarked a generational improvement in protein structure prediction. In particular, advances in antibody structure prediction have provided a highly translatable impact on drug discovery. Though AlphaFold2 laid the groundwork for all proteins, antibody-specific applications require adjustments tailored to these molecules, which has resulted in a handful of deep learning antibody structure predictors. Herein, we review the recent advances in antibody structure prediction and relate them to their role in advancing biologics discovery.
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spelling pubmed-103617242023-07-22 Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery Jaszczyszyn, Igor Bielska, Weronika Gawlowski, Tomasz Dudzic, Pawel Satława, Tadeusz Kończak, Jarosław Wilman, Wiktoria Janusz, Bartosz Wróbel, Sonia Chomicz, Dawid Galson, Jacob D. Leem, Jinwoo Kelm, Sebastian Krawczyk, Konrad Front Mol Biosci Molecular Biosciences AlphaFold2 has hallmarked a generational improvement in protein structure prediction. In particular, advances in antibody structure prediction have provided a highly translatable impact on drug discovery. Though AlphaFold2 laid the groundwork for all proteins, antibody-specific applications require adjustments tailored to these molecules, which has resulted in a handful of deep learning antibody structure predictors. Herein, we review the recent advances in antibody structure prediction and relate them to their role in advancing biologics discovery. Frontiers Media S.A. 2023-07-07 /pmc/articles/PMC10361724/ /pubmed/37484529 http://dx.doi.org/10.3389/fmolb.2023.1214424 Text en Copyright © 2023 Jaszczyszyn, Bielska, Gawlowski, Dudzic, Satława, Kończak, Wilman, Janusz, Wróbel, Chomicz, Galson, Leem, Kelm and Krawczyk. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Jaszczyszyn, Igor
Bielska, Weronika
Gawlowski, Tomasz
Dudzic, Pawel
Satława, Tadeusz
Kończak, Jarosław
Wilman, Wiktoria
Janusz, Bartosz
Wróbel, Sonia
Chomicz, Dawid
Galson, Jacob D.
Leem, Jinwoo
Kelm, Sebastian
Krawczyk, Konrad
Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
title Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
title_full Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
title_fullStr Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
title_full_unstemmed Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
title_short Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
title_sort structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361724/
https://www.ncbi.nlm.nih.gov/pubmed/37484529
http://dx.doi.org/10.3389/fmolb.2023.1214424
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