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Garbage In, Garbage Out: How Reliable Training Data Improved a Virtual Screening Approach Against SARS-CoV-2 MPro.

Santiago M. Ruatta,Denis Prada N. Gori, Martin Flo Diaz,Franca Lorenzelli,Karen Perelmuter,Lucas N. Alberca,Carolina L. Bellera,Andrea Medeiros,Gloria V. Lopez,Mariana Ingold,Williams Porcal,Estefania Dibello,Irina Ihnatenko,Conrad Kunick,Marcelo Incerti,Martin Luzardo,Maximiliano Colobbio,Juan Carlos Ramos,Eduardo Manta,Lucia Minini,Maria Laura Lavaggi,Paola Hernandez,Jonas Sarlauskas, Cesar Sebastian Huerta Garcia,Rafael Castillo,Alicia Hernandez-Campos,Giovanni Ribaudo,Giuseppe Zagotto,Renzo Carlucci,Noelia S. Medran,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,Guzman Alvarez,Adrian Aicardo, Verena Araujo,Cecilia Chavarria,Lucija Peterlin Masic,Melisa E. Gantner,Manuel A. Llanos,Santiago Rodriguez,Luciana Gavernet,Soonju Park,Jinyeong Heo,Honggun Lee,Kyu-Ho Paul Park,Mariela Bollati-Fogolin,Otto Pritsch,David Shum,Alan Talevi,Marcelo A. Comini

FRONTIERS IN PHARMACOLOGY（2023）

Cited 2|Views38
Key words
in silico screening,coronavirus,COVID-19,protease,target-based,drug discovery,rubbish in rubbish out,artificial intelligence
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