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Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors.

Stephen J CapuzziWei SunEugene N MuratovCarles Martínez-RomeroShihua HeWenjun ZhuHao LiGregory TawaEthan G FisherMiao XuPaul ShinnXiangguo QiuAdolfo García-SastreWei ZhengAlexander Trospsha
Published in: Journal of medicinal chemistry (2018)
The Ebola virus (EBOV) causes severe human infection that lacks effective treatment. A recent screen identified a series of compounds that block EBOV-like particle entry into human cells. Using data from this screen, quantitative structure-activity relationship models were built and employed for virtual screening of a ∼17 million compound library. Experimental testing of 102 hits yielded 14 compounds with IC50 values under 10 μM, including several sub-micromolar inhibitors, and more than 10-fold selectivity against host cytotoxicity. These confirmed hits include FDA-approved drugs and clinical candidates with non-antiviral indications, as well as compounds with novel scaffolds and no previously known bioactivity. Five selected hits inhibited BSL-4 live-EBOV infection in a dose-dependent manner, including vindesine (0.34 μM). Additional studies of these novel anti-EBOV compounds revealed their mechanisms of action, including the inhibition of NPC1 protein, cathepsin B/L, and lysosomal function. Compounds identified in this study are among the most potent and well-characterized anti-EBOV inhibitors reported to date.
Keyphrases
  • high throughput
  • endothelial cells
  • structure activity relationship
  • electronic health record
  • early onset
  • big data
  • artificial intelligence
  • mass spectrometry
  • replacement therapy
  • smoking cessation