The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Broad spectrum antiviral remdesivir inhibits human endemic and zoonotic deltacoronaviruses with a highly divergent RNA dependent RNA polymerase
Open accessAbstract
The genetically diverse Orthocoronavirinae (CoV) family is prone to cross species transmission and disease emergence in both humans and livestock. Viruses similar to known epidemic strains circulating in wild and domestic animals further increase the probability of emergence in the future. Currently, there are no approved therapeutics for any human CoV presenting a clear unmet medical need. Remdesivir (RDV, GS-5734) is a monophosphoramidate prodrug of an adenosine analog with potent activity against an array of RNA virus families including Filoviridae, Paramyxoviridae, Pneumoviridae, and Orthocoronavirinae, through the targeting of the viral RNA dependent RNA polymerase (RdRp). We developed multiple assays to further define the breadth of RDV antiviral activity against the CoV family. Here, we show potent antiviral activity of RDV against endemic human CoVs OC43 (HCoV-OC43) and 229E (HCoV-229E) with submicromolar EC50 values. Of known CoVs, the members of the deltacoronavirus genus have the most divergent RdRp as compared to SARS- and MERS-CoV and both avian and porcine members harbor a native residue in the RdRp that confers resistance in beta-CoVs. Nevertheless, RDV is highly efficacious against porcine deltacoronavirus (PDCoV). These data further extend the known breadth and antiviral activity of RDV to include both contemporary human and highly divergent zoonotic CoV and potentially enhance our ability to fight future emerging CoV.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
SARS and MERS: recent insights into emerging coronaviruses
de Wit, E., van Doremalen, N., Falzarano, D., & Munster, V. J. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.81 · Cited by 3,510
SARS-like WIV1-CoV poised for human emergence
Menachery, V. D., Yount, B. L., Sims, A. C., Debbink, K., Agnihothram, S. S., Gralinski, L. E., Graham, R. L., Scobey, T., Plante, J. A., Royal, S. R., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1517719113 · Cited by 418
Self-citationProteomics Analysis Unravels the Functional Repertoire of Coronavirus Nonstructural Protein 3
Neuman, B. W., Joseph, J. S., Saikatendu, K. S., Serrano, P., Chatterjee, A., Johnson, M. A., Liao, L., Klaus, J. P., Yates, J. R., Wüthrich, K., et al. (2008) · Journal of Virology · doi:10.1128/jvi.02631-07 · Cited by 192
Cited by
Remdesivir for the Treatment of Covid-19 — Final Report
Beigel, J. H., Tomashek, K. M., Dodd, L. E., Mehta, A. K., Zingman, B. S., Kalil, A. C., Hohmann, E., Chu, H. Y., Luetkemeyer, A., Kline, S., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2007764 · Cited by 7,267
Wang, Y., Zhang, D., Du, G., Du, R., Zhao, J., Jin, Y., Fu, S., Gao, L., Cheng, Z., Lu, Q., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31022-9 · Cited by 3,440
SARS-CoV-2 Vaccines: Status Report
Amanat, F., & Krammer, F. (2020) · Immunity · doi:10.1016/j.immuni.2020.03.007 · Cited by 1,120
Shi, Y., Wang, G., Cai, X.-P., Deng, J.-W., Zheng, L., Zhu, H.-H., Zheng, M., Yang, B., & Chen, Z. (2020) · Journal of Zhejiang University-SCIENCE B · doi:10.1631/jzus.b2000083 · Cited by 580
Romano, M., Ruggiero, A., Squeglia, F., Maga, G., & Berisio, R. (2020) · Cells · doi:10.3390/cells9051267 · Cited by 527
Metadata
- Authors
- Brown, A. J., Won, J. J., Graham, R. L., Dinnon, K. H., Sims, A. C., Feng, J. Y., Cihlar, T., Denison, M. R., Baric, R. S., & Sheahan, T. P.
- Venue
- Antiviral Research
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 169
- Pages
- 104541
- ISSN
- 0166-3542 (ISSN-L)
- OpenAlex
- W2953224333
- Cited by
- 510
- References
- 3
- FWCI
- 68.64
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Broad spectrum antiviral remdesivir inhibits human endemic and zoonotic deltacoronaviruses with a highly divergent RNA dependent RNA polymerase. https://app.cochat.ai/papers/10.1016/j.antiviral.2019.104541
- The paper
- Brown, A. J., Won, J. J., Graham, R. L., Dinnon, K. H., Sims, A. C., Feng, J. Y., Cihlar, T., Denison, M. R., Baric, R. S., & Sheahan, T. P. (2019). Broad spectrum antiviral remdesivir inhibits human endemic and zoonotic deltacoronaviruses with a highly divergent RNA dependent RNA polymerase. Antiviral Research. https://doi.org/10.1016/j.antiviral.2019.104541
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.