Simulations and active learning enable efficient identification of an experimentally-validated broad coronavirus inhibitor

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Detalhes bibliográficos
Publicado no:	Nature Communications vol. 16, no. 1 (2025), p. 6949-6961
Autor principal:	Elez, Katarina
Outros Autores:	Hempel, Tim, Shrimp, Jonathan H., Moor, Nicole, Raich, Lluís, Rocha, Cheila, Winter, Robin, Le, Tuan, Pöhlmann, Stefan, Hoffmann, Markus, Hall, Matthew D., Noé, Frank
Publicado em:	Nature Publishing Group
Assuntos:	Coronaviruses Simulation Datasets Learning Inhibitors Computational efficiency Effectiveness Computing costs Drug development Severe acute respiratory syndrome coronavirus 2 Computer applications Drug screening Viral diseases Drugs Libraries Molecular dynamics Candidates COVID-19 Proteins Therapeutic applications Environmental
Acesso em linha:	Citation/Abstract Full Text Full Text - PDF
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