Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

在 SARS-CoV-2 抗体发现流程中整合基于人工智能的表位预测:需谨慎行事

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作者:Delphine Diana Acar, Wojciech Witkowski, Magdalena Wejda, Ruifang Wei, Tim Desmet, Bert Schepens, Sieglinde De Cae, Koen Sedeyn, Hannah Eeckhaut, Daria Fijalkowska, Kenny Roose, Sandrine Vanmarcke, Anne Poupon, Dirk Jochmans, Xin Zhang, Rana Abdelnabi, Caroline S Foo, Birgit Weynand, Dirk Reiter, Ni

Background

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.

Methods

Undertaking a nAB discovery program, we employed a classical workflow, while integrating artificial intelligence (AI)-based prediction to select non-competing nABs very early in the pipeline. We identified and in vivo validated (in female Syrian hamsters) two highly potent nABs. Findings: Despite the promising

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