1. Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery.
- Author
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Jaszczyszyn I, Bielska W, Gawlowski T, Dudzic P, Satława T, Kończak J, Wilman W, Janusz B, Wróbel S, Chomicz D, Galson JD, Leem J, Kelm S, and Krawczyk K
- 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., Competing Interests: IJ, WB, TG, PD, TS, JK, WW, BJ, SW, DC, and KK are employees of NaturalAntibody that develops data, software and machine learning solutions for the therapeutic antibody industry. JG and JL are employees of Alchemab. SK is an employee of UCB Pharma., (Copyright © 2023 Jaszczyszyn, Bielska, Gawlowski, Dudzic, Satława, Kończak, Wilman, Janusz, Wróbel, Chomicz, Galson, Leem, Kelm and Krawczyk.)
- Published
- 2023
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