Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation. Issue 1 (27th December 2021)

• Record Type: Journal Article
• Authors: Serra, Angela; Fratello, Michele; Federico, Antonio; Ojha, Ravi; Provenzani, Riccardo; Tasnadi, Ervin; Cattelani, Luca; del Giudice, Giusy; Kinaret, Pia A S; Saarimäki, Laura A; Pavel, Alisa; Kuivanen, Suvi; Cerullo, Vincenzo; Vapalahti, Olli; Horvath, Peter; Lieto, Antonio Di; Yli-Kauhaluoma, Jari; Balistreri, Giuseppe; Greco, Dario
• Is Part Of: Briefings in bioinformatics. Volume 23:Issue 1(2022)
• Publication Date: 2021-12-27
• Subjects: COVID-19 -- SARS-CoV-2 -- drug repositioning -- drug design -- virtual screening -- 7-hydroxystaurosporine -- bafetinib -- syncytia -- kinase inhibitors -- delta variant; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbab507
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: The pharmacological arsenal against the COVID-19 pandemic is largely based on generic anti-inflammatory strategies or poorly scalable solutions. Moreover, as the ongoing vaccination campaign is rolling slower than wished, affordable and effective therapeutics are needed. To this end, there is increasing attention toward computational methods for drug repositioning and de novo drug design. Here, multiple data-driven computational approaches are systematically integrated to perform a virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the list of prioritized drugs, a subset of representative candidates to test in human cells is selected. Two compounds, 7-hydroxystaurosporine and bafetinib, show synergistic antiviral effects in vitro and strongly inhibit viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, the relevant chemical substructures of the identified drugs are extracted to provide a chemical vocabulary that may help to design new effective drugs.