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

RUATTA, SANTIAGO M.; PRADA GORI, DENIS N.; FLÓ DÍAZ, MARTÍN; CARLUCCI, RENZO; MEDRÁN, NOELIA S.; LABADIE, GUILLERMO R.; MARTINEZ-AMEZAGA, MAITENA; DELPICCOLO, CARINA M. L.; MATA, ERNESTO G.; TALEVI, ALAN; COMINI, MARCELO A.

Frontiers in Pharmacology

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Año: 2023 vol. 14

The identification of chemical compounds that interfere with SARSCoV-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, these initiatives may yield unrealistic results if the appliedmodels are not inferred from reliable data and theresulting predictions are not confirmed by experimental evidence.