bioRxivPharmacology & Toxicology
Characterization of raloxifene as potential pharmacological agent against SARS-CoV-2 and its variants
D. Iaconis, C. Talarico, C. Manelfi, M. C. Cesta, M. Zippoli, F. Caccuri, G. Matusali, L. Bordi, L. Scorzolini, E. M. Bucci, A. Caruso, E. Nicastri, M. Allegretti, A. R. Beccari
Abstract
The new coronavirus that emerged, called SARS-CoV-2, is the causative agent of the COVID-19 pandemic. The identification of potential drug candidates that can rapidly enter clinical trials for the prevention and treatment of COVID-19 is an urgent need, despite the recent introduction of several new vaccines for the prevention and protection of this infectious disease, which in many cases becomes severe. Drug repurposing (DR), a process for studying existing pharmaceutical products for new therapeutic indications, represents one of the most effective potential strategies employed to increase the success rate in the development of new drug therapies. We identified raloxifene, a known Selective Estrogen Receptor Modulator (SERM), as a potential pharmacological agent for the treatment of COVID-19 patients. Following a virtual screening campaign on the most relevant viral protein targets, in this work we report the results of the first pharmacological characterization of raloxifene in relevant cellular models of COVID-19 infection. The results obtained on all the most common viral variants originating in Europe, United Kingdom, Brazil, South Africa and India, currently in circulation, are also reported, confirming the efficacy of raloxifene and, consequently, the relevance of the proposed approach. Taken together, all the information gathered supports the clinical development of raloxifene and confirms that the drug can be proposed as a viable new option to fight the pandemic in at least some patient populations. The results obtained so far have paved the way for a first clinical study to test the safety and efficacy of raloxifene, just concluded in patients with mild to moderate COVID-19.
- organism: human
- assay: proteomics
- research focus: drug response / drug discovery
- approach: deep learning
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