Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors
Open accessAbstract
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 IC 50 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.
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QSAR models have become an integral component of the drug discovery process, providing substantial guidance in planning experiments.
“Thus, models have become an integral component of the drug discovery process, providing substantial guidance in planning experiments.3,8”
From QSAR without borders (2020) · cites this paper as [8]
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Handbook of Molecular Descriptors
Todeschini, R., & Consonni, V. (2000) · Methods and Principles in Medicinal Chemistry · doi:10.1002/9783527613106 · Cited by 4,107 · see citing works
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Self-citation<i>Per Aspera Ad Astra</i> : Application of Simplex Qsar Approach in Antiviral Research
Muratov, E. N., Artemenko, A. G., Varlamova, E. V., Polischuk, P. G., Lozitsky, V. P., Fedchuk, A. S., Lozitska, R. L., Gridina, T. L., Koroleva, L. S., Sil’nikov, V. N., et al. (2010) · Future Medicinal Chemistry · doi:10.4155/fmc.10.194 · Cited by 64 · see citing works
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Muratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00098a · Cited by 913 · see citing works
Self-citationEbola Virus Bayesian Machine Learning Models Enable New in Vitro Leads
Anantpadma, M., Lane, T., Zorn, K. M., Lingerfelt, M. A., Clark, A. M., Freundlich, J. S., Davey, R. A., Madrid, P. B., & Ekins, S. (2019) · ACS Omega · doi:10.1021/acsomega.8b02948 · Cited by 54 · see citing works
- Authors
- Capuzzi, S. J., Sun, W., Muratov, E. N., Martínez-Romero, C., He, S., Zhu, W., Li, H., Tawa, G., Fisher, E. G., Xu, M., Shinn, P., Qiu, X., García-Sastre, A., Zheng, W., & Tropsha, A.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- National Institutes of Health (US)
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- Public Health Agency of Canada (CA)
- Corresponding author
- Zheng, Wei
- Tropsha, Alexander
- ORCID
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-04-06
- Volume
- 61
- Issue
- 8
- Pages
- 3582-3594
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- PMC
- PMC6548547
- OpenAlex
- W2795853169
- Cited by
- 35
- References
- 3
- Citations by year
- 2025: 3 · 2024: 1 · 2023: 3 · 2022: 5 · 2021: 9 · 2020: 10 · 2019: 3 · 2018: 1
- FWCI
- 4.35
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Medicinal Chemistry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Center for Advancing Translational Sciences
- National Cancer Institute (1U01CA207160, R01-GM114015)
- Eshelman Institute for Innovation, University of North Carolina
- National Institute of General Medical Sciences (R01 GM114015)
- Topics
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Vectors
- Keywords
- Ebola virus, antiviral drug discovery, viral entry inhibitors, QSAR, virtual screening, lysosomal function, vindesine, host-directed antiviral therapy
- MeSH terms
- Animals, Antiviral Agents, Chlorocebus aethiops, Drug Evaluation, Preclinical, HeLa Cells, Humans, Vero Cells, Molecular Structure, Quantitative Structure-Activity Relationship, Ebolavirus, Virus Internalization, Small Molecule Libraries, Drug Discovery
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