Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery

Front Mol Biosci. 2023 Jul 7:10:1214424. doi: 10.3389/fmolb.2023.1214424. eCollection 2023.

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.

Keywords: antibody structure prediction; antibody therapeutics; deep learning; drug discovery; structural modeling.

Publication types

  • Review

Grants and funding

This work was co-financed by the European Regional Development Fund within the Smart Growth Operational Programme 2014–2020 POIR.01.01.01-00-0962/21 (to KK).