Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery
2023
Igor Jaszczyszyn | Igor Jaszczyszyn | Weronika Bielska | Weronika Bielska | Tomasz Gawlowski | Pawel Dudzic | Tadeusz Satława | Jarosław Kończak | Wiktoria Wilman | Bartosz Janusz | Sonia Wróbel | Dawid Chomicz | Jacob D. Galson | Jinwoo Leem | Sebastian Kelm | Konrad Krawczyk
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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