Identification of lead inhibitors for 3CLpro of SARS-CoV-2 target using machine learning based virtual screening, ADMET analysis, molecular docking and molecular dynamics simulations.

The SARS-CoV-2 3CLpro is a critical target for COVID-19 therapeutics due to its role in viral replication. We employed a screening pipeline to identify novel inhibitors by combining machine learning classification with similarity checks of approved medications. A voting classifier, integrating three machine learning classifiers, was used to filter a large database (∼10 million compounds) for potential inhibitors.