Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted.
Acar, D.D., Witkowski, W., Wejda, M., Wei, R., Desmet, T., Schepens, B., De Cae, S., Sedeyn, K., Eeckhaut, H., Fijalkowska, D., Roose, K., Vanmarcke, S., Poupon, A., Jochmans, D., Zhang, X., Abdelnabi, R., Foo, C.S., Weynand, B., Reiter, D., Callewaert, N., Remaut, H., Neyts, J., Saelens, X., Gerlo, S., Vandekerckhove, L.(2024) EBioMedicine 100: 104960-104960
- PubMed: 38232633 
- DOI: https://doi.org/10.1016/j.ebiom.2023.104960
- Primary Citation of Related Structures:  
8QPR, 8QQ0 - PubMed Abstract: 
SARS-CoV-2-neutralizing antibodies (nABs) showed great promise in the early phases of the COVID-19 pandemic. The emergence of resistant strains, however, quickly rendered the majority of clinically approved nABs ineffective. This underscored the imperative to develop nAB cocktails targeting non-overlapping epitopes.
Organizational Affiliation: 
HIV Cure Research Center, Department of Internal Medicine and Pediatrics, Ghent University Hospital, Ghent University, Ghent 9000, Belgium.