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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Hlavní autoři:	Santiago M. Ruatta, Denis N. Prada Gori, Martín Fló Díaz, Franca Lorenzelli, Karen Perelmuter, Lucas N. Alberca, Carolina L. Bellera, Andrea Medeiros, Gloria V. López, Mariana Ingold, Williams Porcal, Estefanía Dibello, Irina Ihnatenko, Conrad Kunick, Marcelo Incerti, Martín Luzardo, Maximiliano Colobbio, Juan Carlos Ramos, Eduardo Manta, Lucía Minini, María Laura Lavaggi, Paola Hernández, Jonas Šarlauskas, César Sebastian Huerta García, Rafael Castillo, Alicia Hernández-Campos, Giovanni Ribaudo, Giuseppe Zagotto, Renzo Carlucci, Noelia S. Medrán, Guillermo R. Labadie, Maitena Martinez-Amezaga, Carina M. L. Delpiccolo, Ernesto G. Mata, Laura Scarone, Laura Posada, Gloria Serra, Theodora Calogeropoulou, Kyriakos Prousis, Anastasia Detsi, Mauricio Cabrera, Guzmán Alvarez, Adrián Aicardo, Verena Araújo, Cecilia Chavarría, Lucija Peterlin Mašič, Melisa E. Gantner, Manuel A. Llanos, Santiago Rodríguez, Luciana Gavernet, Soonju Park, Jinyeong Heo, Honggun Lee, Kyu-Ho Paul Park, Mariela Bollati-Fogolín, Otto Pritsch, David Shum, Alan Talevi, Marcelo A. Comini
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Frontiers Media S.A. 2023-06-01
Edice:	Frontiers in Pharmacology
Témata:	in silico screening coronavirus COVID-19 protease target-based drug discovery
On-line přístup:	https://www.frontiersin.org/articles/10.3389/fphar.2023.1193282/full
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