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Background: The ongoing COVID-19 pandemic has caused more than 193,825 deaths during the past few months. A quick-to-be-identified cure for the disease will be a therapeutic medicine that has prior use experiences in patients in order to resolve the current pandemic situation before it could become worsening. Artificial intelligence (AI) technology is hereby applied to identify the marketed drugs with potential for treating COVID-19. Methods: An AI platform was established to identify potential old drugs with anti-coronavirus activities by using two different learning databases; one consisted of the compounds reported or proven active against SARS-CoV, SARS-CoV-2, human immunodeficiency virus, influenza virus, and the other one containing the known 3C-like protease inhibitors. All AI predicted drugs were then tested for activities against a feline coronavirus in in vitro cell-based assay. These assay results were feedbacks to the AI system for relearning and thus to generate a modified AI model to search for old drugs again. Results: After a few runs of AI learning and prediction processes, the AI system identified 80 marketed drugs with potential. Among them, 8 drugs (bedaquiline, brequinar, celecoxib, clofazimine, conivaptan, gemcitabine, tolcapone, and vismodegib) showed in vitro activities against the proliferation of a feline infectious peritonitis (FIP) virus in Fcwf-4 cells. In addition, 5 other drugs (boceprevir, chloroquine, homoharringtonine, tilorone, and salinomycin) were also found active during the exercises of AI approaches. Conclusion: Having taken advantages of AI, we identified old drugs with activities against FIP coronavirus. Further studies are underway to demonstrate their activities against SARS-CoV-2 in vitro and in vivo at clinically achievable concentrations and doses. With prior use experiences in patients, these old drugs if proven active against SARS-CoV-2 can readily be applied for fighting COVID-19 pandemic.

Background: New therapeutic options to address the ongoing coronavirus disease 2019 (COVID-19) pandemic are urgently needed. One possible strategy is the repurposing of existing drugs approved for other indications as antiviral agents for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Due to the commercial unavailability of SARS-CoV-2 drugs for treating COVID-19, we screened approximately 250 existing drugs or pharmacologically active compounds for their inhibitory activities against feline infectious peritonitis coronavirus (FIPV) and human coronavirus OC43 (HCoV-OC43), a human coronavirus in the same genus (Betacoronavirus) as SARS-CoV-2. Methods: FIPV was proliferated in feline Fcwf-4 cells and HCoV-OC43 in human HCT-8 cells. Viral proliferation was assayed by visualization of cytopathic effects on the infected Fcwf-4 cells and immunofluorescent assay for detection of the nucleocapsid proteins of HCoV-OC43 in the HCT-8 cells. The concentrations (EC50) of each drug necessary to diminish viral activity to 50% of that for the untreated controls were determined. The viabilities of Fcwf-4 and HCT-8 cells were measured by crystal violet staining and MTS/PMS assay, respectively. Results: Fifteen out of the 252 drugs or pharmacologically active compounds screened were found to be active against both FIPV and HCoV-OC43, with EC50 values ranging from 11 nM to 75 μM. They are all old drugs as follows, anisomycin, antimycin A, atovaquone, chloroquine, conivaptan, emetine, gemcitabine, homoharringtonine, niclosamide, nitazoxanide, oligomycin, salinomycin, tilorone, valinomycin, and vismodegib. Conclusion: All of the old drugs identified as having activity against FIPV and HCoV-OC43 have seen clinical use in their respective indications and are associated with known dosing schedules and adverse effect or toxicity profiles in humans. Those, when later confirmed to have an anti-viral effect on SARS-CoV-2, should be considered for immediate uses in COVID-19 patients.

Remdesivir, a prodrug targeting RNA-dependent-RNA-polymerase, and cyclosporine, a calcineurin inhibitor, individually exerted inhibitory activity against human coronavirus OC43 (HCoV-OC43) in HCT-8 and MRC-5 cells at EC50 values of 96 ± 34 ∼ 85 ± 23 nM and 2,920 ± 364 ∼ 4,419 ± 490 nM, respectively. When combined, these two drugs synergistically inhibited HCoV-OC43 in both HCT-8 and MRC-5 cells assayed by immunofluorescence assay (IFA). Remdesivir and cyclosporine also separately reduced IL-6 production induced by HCoV-OC43 in human lung fibroblasts MRC-5 cells with EC50 values of 224 ± 53 nM and 1,292 ± 352 nM, respectively; and synergistically reduced it when combined. Similar trends were observed for SARS-CoV-2, which were 1) separately inhibited by remdesivir and cyclosporine with respective EC50 values of 3,962 ± 303 nM and 7,213 ± 143 nM by IFA, and 291 ± 91 nM and 6,767 ± 1,827 nM by a plaque-formation assay; and 2) synergistically inhibited by their combination, again by IFA and plaque-formation assay. Collectively, these results suggest that the combination of remdesivir and cyclosporine merits further study as a possible treatment for COVID-19 complexed with a cytokine storm.

Tylophorine-based compounds and natural cardiotonic steroids (cardenolides and bufadienolides) are two classes of transmissible gastroenteritis coronavirus inhibitors, targeting viral RNA and host cell factors, respectively. We tested both types of compounds against two types of coronaviruses, to compare and contrast their antiviral properties, and with view to their further therapeutic development. Examples of both types of compounds potently inhibited the replication of both feline infectious peritonitis virus and human coronavirus OC43 with EC50 values of up to 8 and 16 nM, respectively. Strikingly, the tylophorine-based compounds tested inhibited viral yields of HCoV-OC43 to a much greater extent (7–8 log magnitudes of p.f.u./ml) than the cardiotonic steroids (about 2–3 log magnitudes of p.f.u./ml), as determined by end point assays. Based on these results, three tylophorine-based compounds were further examined for their anti-viral activities on two other human coronaviruses, HCoV-229E and SARS-CoV-2. These three tylophorine-based compounds inhibited HCoV-229E with EC50 values of up to 6.5 nM, inhibited viral yields of HCoV-229E by 6–7 log magnitudes of p.f.u./ml, and were also found to inhibit SARS-CoV-2 with EC50 values of up to 2.5–14 nM. In conclusion, tylophorine-based compounds are potent, broad-spectrum inhibitors of coronaviruses including SARS-CoV-2, and could be used for the treatment of COVID-19.

Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE_Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE_Scale) score derived from the LE_Scale function, the database compounds were reranked (PH_FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 µM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 µM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner. [ABSTRACT FROM AUTHOR]