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=Volume 10 - 2023

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=The practical solution to protein structure prediction, in the form of AlphaFold2, promised improvement in computational drug discovery. Particularly in the field of antibodies, improving upon the problem of structure prediction has practical applications for novel therapeutics development. 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. Here, we review the recent advances in antibody structure prediction and relate them to their role in advancing biologics discovery.