The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

Peroxisome proliferator-activated receptors (PPARs) play a crucial role in regulating carbohydrate and lipid metabolism and are considered as significant targets for treating metabolic syndrome and cancers. There is a need to identify new bioactive ligands that can activate specific PPAR subtypes, particularly PPARβ/δ, which is less studied compared to other PPAR isoforms (α and γ). Here, the ZINC database of clinically approved drugs was screened to target PPARβ/δ receptor, through virtual screening followed by molecular docking and molecular dynamics (MD) simulation. Among the screened ligands, the top five ligands with strong binding affinity towards the PPARβ/δ were canagliflozin, empagliflozin, lumacaftor, eprosartan, dapagliflozin. The top-scoring ligands showed stable protein-ligand complexation (PLC)with PPARβ/δ, as revealed by RMSD / RMSF analysis. The in silico ADMET prediction analysis assessed the pharmacokinetic profiles of these top five ligands, wherein they showed favourable drug-likeness properties. These promising results indicate scope for developing and validating the top-scoring PPARβ/δ agonists in specific disease models.

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