Sammanfattning

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.

Originalspråkengelska
Artikelnummer507
TidskriftBriefings in Bioinformatics
Volym23
Nummer1
Antal sidor20
ISSN1467-5463
DOI
StatusPublicerad - jan. 2022
MoE-publikationstypA1 Tidskriftsartikel-refererad

Vetenskapsgrenar

  • 317 Farmaci
  • 3121 Allmänmedicin, inre medicin och annan klinisk medicin
  • 113 Data- och informationsvetenskap

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