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.
CITATION STYLE
Jaszczyszyn, I., Bielska, W., Gawlowski, T., Dudzic, P., Satława, T., Kończak, J., … Krawczyk, K. (2023). Structural modeling of antibody variable regions using deep learning—progress and perspectives on drug discovery. Frontiers in Molecular Biosciences. Frontiers Media SA. https://doi.org/10.3389/fmolb.2023.1214424
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