2019
DOI: 10.1021/acsomega.8b02948
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Ebola Virus Bayesian Machine Learning Models Enable New in Vitro Leads

Abstract: We have previously described the first Bayesian machine learning models from FDA-approved drug screens, for identifying compounds active against the Ebola virus (EBOV). These models led to the identification of three active molecules in vitro: tilorone, pyronaridine, and quinacrine. A follow-up study demonstrated that one of these compounds, tilorone, has 100% in vivo efficacy in mice infected with mouse-adapted EBOV at 30 mg/kg/day intraperitoneal. This suggested that we can learn from the published data on E… Show more

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Cited by 55 publications
(67 citation statements)
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References 80 publications
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“…This model predicted Ebola inhibitory activity for tilorone, which was then tested using an in vitro anti-Ebola assay for activity. Tilorone gave a 50% effective concentration (EC 50 ) in this assay of 230 nM (Table II), making it one of the most potent small-molecule inhibitors of EBOV reported at the time (31,35,36). After a series of toxicity and pharmacokinetic studies, the compound was tested in a mouse model of EBOV infection where it was associated with 90-100% survival in a mouse EBOV efficacy study at three different doses.…”
Section: Introductionmentioning
confidence: 99%
“…This model predicted Ebola inhibitory activity for tilorone, which was then tested using an in vitro anti-Ebola assay for activity. Tilorone gave a 50% effective concentration (EC 50 ) in this assay of 230 nM (Table II), making it one of the most potent small-molecule inhibitors of EBOV reported at the time (31,35,36). After a series of toxicity and pharmacokinetic studies, the compound was tested in a mouse model of EBOV infection where it was associated with 90-100% survival in a mouse EBOV efficacy study at three different doses.…”
Section: Introductionmentioning
confidence: 99%
“…Efforts to improve the efficiency and cost effectiveness of EBOV drug discovery have involved our efforts to identify several molecules using ML which have progressed through in vitro and in vivo testing (12-15, 17, 51). We have also previously used these ML models to predict in vitro efficacy for drugs that were then tested against EBOV (12,22). The mechanism for these three compounds against EBOV is unknown.…”
Section: Discussionmentioning
confidence: 99%
“…The Assay Central software has been previously described (23)(24)(25)(26)(27)(28)(29)(30)(31)(32) which uses the source code management system Git to gather and store structure-activity datasets collated in Molecular Notebook (Molecular Materials Informatics, Inc. in Montreal, Canada). The output is a high-quality dataset and a Bayesian model using extendedconnectivity fingerprints of maximum diameter 6 (ECFP6) descriptors.…”
Section: Lysosomotropic Machine Learning Modelmentioning
confidence: 99%
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“…All of these molecules inhibited EBOV in HeLa cells but not Vero cells, and they all demonstrated significant in vivo activity in the mouse-adapted EBOV (ma-EBOV) efficacy model (2325). Pyronaridine (EC 50 range of 420 nM-1.14 µ M (22, 26)) has been previously described in detail (27). It is the major component of the EU-approved antimalarial Pyramax, which is a combination antimalarial therapy with artesunate and pyronaridine and is approved for this use in the Democratic Republic of the Congo as well as other countries (e.g.…”
Section: Introductionmentioning
confidence: 99%