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Garbage in, garbage out: how reliable training data improved a virtual screening approach against SARS-CoV-2 MPro

Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have the power to integrate, process and analyze multiple data in a short time. However...

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Detalles Bibliográficos
Autores principales: Ruatta, Santiago M., Prada Gori, Denis N., Fló Díaz, Martín, Lorenzelli, Franca, Perelmuter, Karen, Alberca, Lucas N., Bellera, Carolina L., Medeiros, Andrea, López, Gloria V., Ingold, Mariana, Porcal, Williams, Dibello, Estefanía, Ihnatenko, Irina, Kunick, Conrad, Incerti, Marcelo, Luzardo, Martín, Colobbio, Maximiliano, Ramos, Juan Carlos, Manta, Eduardo, Minini, Lucía, Lavaggi, María Laura, Hernández, Paola, Šarlauskas, Jonas, Huerta García, César Sebastian, Castillo, Rafael, Hernández-Campos, Alicia, Ribaudo, Giovanni, Zagotto, Giuseppe, Carlucci, Renzo, Medrán, Noelia S., Labadie, Guillermo R., Martinez-Amezaga, Maitena, Delpiccolo, Carina M. L., Mata, Ernesto G., Scarone, Laura, Posada, Laura, Serra, Gloria, Calogeropoulou, Theodora, Prousis, Kyriakos, Detsi, Anastasia, Cabrera, Mauricio, Alvarez, Guzmán, Aicardo, Adrián, Araújo, Verena, Chavarría, Cecilia, Mašič, Lucija Peterlin, Gantner, Melisa E., Llanos, Manuel A., Rodríguez, Santiago, Gavernet, Luciana, Park, Soonju, Heo, Jinyeong, Lee, Honggun, Paul Park, Kyu-Ho, Bollati-Fogolín, Mariela, Pritsch, Otto, Shum, David, Talevi, Alan, Comini, Marcelo A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10323144/
https://www.ncbi.nlm.nih.gov/pubmed/37426813
http://dx.doi.org/10.3389/fphar.2023.1193282