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 

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

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1214424

DOI=10.3389/fmolb.2023.1214424

ISSN=2296-889X

ABSTRACT=<p>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.</p>