The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Evaluating the 3C-like protease activity of SARS-Coronavirus: Recommendations for standardized assays for drug discovery
Open accessAbstract
Although the initial outbreaks of the deadly coronavirus that causes severe acute respiratory syndrome (SARS-CoV) were controlled by public health measures, the development of vaccines and antiviral agents for SARS-CoV is essential for improving control and treatment of future outbreaks. One potential target for SARS-CoV antiviral drug development is the 3C-like protease (3CLpro). This enzyme is an attractive target since it is essential for viral replication, and since there are now a number of high resolution X-ray structures of SARS-CoV 3CLpro available making structure-based drug-design possible. As a result, SARS-CoV 3CLpro has become the focus of numerous drug discovery efforts worldwide, but as a consequence, a variety of different 3CLpro expression constructs and kinetic assays have been independently developed making evaluation and comparison between potential inhibitors problematic. Here, we review the literature focusing on different SARS-CoV 3CLpro expression constructs and assays used to measure enzymatic activity. Moreover, we provide experimental evidence showing that the activity of 3CLpro enzymatic is significantly reduced when non-native sequences or affinity-tags are added to the N- or C-termini of the enzyme, or when the enzyme used in assays is at concentrations below the equilibrium dissociation constant of the 3CLpro dimer. We demonstrate for the first time the utility of a highly sensitive and novel Alexa488-QSY7 FRET-based peptide substrate designed for routine analysis and high-throughput screening, and show that kinetic constants determined from FRET-based assays that are uncorrected for inner-filter effects can lead to artifacts. Finally, we evaluated the effects of common assay components including DTT, NaCl, EDTA and DMSO on enzymatic activity, and we recommend standardized assay conditions and constructs for routine SARS-CoV 3CLpro assays to facilitate direct comparisons between SARS-CoV 3CLpro inhibitors under development worldwide.
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
Identification of a novel coronavirus in patients with severe acute respiratory syndrome
Drosten, C., Günther, S., Preiser, W., van der Werf, S., Brodt, H.-R., Becker, S., Rabenau, H., Panning, M., Kolesnikova, L., Fouchier, R. A. M., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa030747 · Cited by 4,574
Cited by
An oral SARS-CoV-2 M pro inhibitor clinical candidate for the treatment of COVID-19
Owen, D. R., Allerton, C. M. N., Anderson, A. S., Aschenbrenner, L., Avery, M., Berritt, S., Boras, B., Cardin, R. D., Carlo, A., Coffman, K. J., et al. (2021) · Science · doi:10.1126/science.abl4784 · Cited by 2,033
The SARS-CoV-2 main protease as drug target
Ullrich, S., & Nitsche, C. (2020) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2020.127377 · Cited by 772
Vankadari, N., & Wilce, J. A. (2020) · Emerging Microbes & Infections · doi:10.1080/22221751.2020.1739565 · Cited by 585
Hoffman, R. L., Kania, R. S., Brothers, M. A., Davies, J. F., Ferre, R. A., Gajiwala, K. S., He, M., Hogan, R. J., Kozminski, K., Li, L. Y., et al. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c01063 · Cited by 507
Flavonoid-mediated inhibition of SARS coronavirus 3C-like protease expressed in Pichia pastoris
Nguyen, T. T. H., Woo, H.-J., Kang, H.-K., Nguyen, V. D., Kim, Y.-M., Kim, D.-W., Ahn, S.-A., Xia, Y., & Kim, D. (2012) · Biotechnology Letters · doi:10.1007/s10529-011-0845-8 · Cited by 347
Metadata
- Authors
- Grum-Tokars, V., Ratia, K., Begaye, A., Baker, S. C., & Mesecar, A. D.
- Venue
- Virus Research
- Publisher
- Elsevier BV
- Published
- 2008-04
- Volume
- 133
- Issue
- 1
- Pages
- 63-73
- ISSN
- 0168-1702 (ISSN-L)
- OpenAlex
- W2014529290
- Cited by
- 190
- References
- 1
- FWCI
- 1.37
- 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: Evaluating the 3C-like protease activity of SARS-Coronavirus: Recommendations for standardized assays for drug discovery. https://app.cochat.ai/papers/10.1016/j.virusres.2007.02.015
- The paper
- Grum-Tokars, V., Ratia, K., Begaye, A., Baker, S. C., & Mesecar, A. D. (2008). Evaluating the 3C-like protease activity of SARS-Coronavirus: Recommendations for standardized assays for drug discovery. Virus Research. https://doi.org/10.1016/j.virusres.2007.02.015
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.