Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
Igor Jaszczyszyn, Weronika Bielska, Tomasz Gawłowski, Paweł Dudzic, Tadeusz Satława, Jarosław Kończak, Wiktoria Wilman, Bartosz Janusz, Sonia Wróbel, Dawid Chomicz, Jacob D. Galson, Jinwoo Leem, Sebastian Kelm, Konrad Krawczyk
Abstract
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.