Reliable computer-aided drug repositioning (CADR) technologies require accurate data science and machine learning (ML) support. We integrated clinical and experimental data for SARS-CoV-2 drugs into our CADR workflow, specifically tailored for COVID-19 (“CADR19”). Our goal is to rapidly identify drugs that may be effective in the incubation and symptomatic phases of COVID-19. CADR19 is an iterative cycle of ligand based (2D/3D) similarity starting from 3 known SARS-CoV-2 drugs, followed by in vitro experiments (cytopathic effect assay in VeroE6 cells, plus cytotoxicity assays). Preference is given to off-patent or off-market (previously approved) drugs, enriched by an ML model that estimate anti-SARS-CoV-2 activity from chemical structure. After 4 rounds of CADR19, we identified novel anti-SARS-CoV-2 drugs, including zuclopenthixol and nebivolol. Their antiviral effects are evaluated in the light of human pharmacokinetics and dosing data.
Access key resources such as DrugCentral (drugcentral.org) for information regarding active pharmaceutical ingredients
Learn about the use of computational technologies and artificial intelligence for drug repositioning
Discuss the merits of various anti-SARS-CoV-2 drugs in an effective manner.