The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing
Open accessAbstract
Coronaviruses are animal and human pathogens that can cause lethal zoonotic infections like SARS and MERS. They have polycistronic plus-stranded RNA genomes and belong to the order Nidovirales, a diverse group of viruses for which common ancestry was inferred from the common principles underlying their genome organization and expression, and from the conservation of an array of core replicase domains, including key RNA-synthesizing enzymes. Coronavirus genomes (~ 26–32 kilobases) are the largest RNA genomes known to date and their expansion was likely enabled by acquiring enzyme functions that counter the commonly high error frequency of viral RNA polymerases. The primary functions that direct coronavirus RNA synthesis and processing reside in nonstructural protein (nsp) 7 to nsp16, which are cleavage products of two large replicase polyproteins translated from the coronavirus genome. Significant progress has now been made regarding their structural and functional characterization, stimulated by technical advances like improved methods for bioinformatics and structural biology, in vitro enzyme characterization, and site-directed mutagenesis of coronavirus genomes. Coronavirus replicase functions include more or less universal activities of plus-stranded RNA viruses, like an RNA polymerase (nsp12) and helicase (nsp13), but also a number of rare or even unique domains involved in mRNA capping (nsp14, nsp16) and fidelity control (nsp14). Several smaller subunits (nsp7–nsp10) act as crucial cofactors of these enzymes and contribute to the emerging “nsp interactome.” Understanding the structure, function, and interactions of the RNA-synthesizing machinery of coronaviruses will be key to rationalizing their evolutionary success and the development of improved control strategies.
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
Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor
Ge, X.-Y., Li, J.-L., Yang, X.-L., Chmura, A. A., Zhu, G., Epstein, J. H., Mazet, J. K., Hu, B., Zhang, W., Peng, C., et al. (2013) · Nature · doi:10.1038/nature12711 · Cited by 1,778
A general two-metal-ion mechanism for catalytic RNA
Steitz, T. A., & Steitz, J. A. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.14.6498 · Cited by 1,171
Mutation rates among RNA viruses
Drake, J. W., & Holland, J. J. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.24.13910 · Cited by 1,143
Cited by
Coronavirus biology and replication: implications for SARS-CoV-2
V’kovski, P., Kratzel, A., Steiner, S., Stalder, H., & Thiel, V. (2021) · Nature Reviews Microbiology · doi:10.1038/s41579-020-00468-6 · Cited by 3,197
The Architecture of SARS-CoV-2 Transcriptome
Kim, D., Lee, J.-Y., Yang, J.-S., Kim, J. W., Kim, V. N., & Chang, H. (2020) · Cell · doi:10.1016/j.cell.2020.04.011 · Cited by 2,123
The coding capacity of SARS-CoV-2
Finkel, Y., Mizrahi, O., Nachshon, A., Weingarten-Gabbay, S., Morgenstern, D., Yahalom-Ronen, Y., Tamir, H., Achdout, H., Stein, D., Israeli, O., et al. (2021) · Nature · doi:10.1038/s41586-020-2739-1 · Cited by 644
A molecular pore spans the double membrane of the coronavirus replication organelle
Wolff, G., Limpens, R. W. A. L., Zevenhoven-Dobbe, J. C., Laugks, U., Zheng, S., de Jong, A. W. M., Koning, R. I., Agard, D. A., Grünewald, K., Koster, A. J., et al. (2020) · Science · doi:10.1126/science.abd3629 · Cited by 527
Self-citationOrigins and Evolution of the Global RNA Virome
Wolf, Y. I., Kazlauskas, D., Iranzo, J., Lucía-Sanz, A., Kuhn, J. H., Krupovic, M., Dolja, V. V., & Koonin, E. V. (2018) · mBio · doi:10.1128/mbio.02329-18 · Cited by 508
Metadata
- Authors
- Snijder, E. J., Decroly, E., & Ziebuhr, J.
- Venue
- Advances in Virus Research
- Publisher
- Elsevier
- Published
- 2016
- Volume
- 96
- Pages
- 59-126
- ISSN
- 0065-3527 (ISSN-L)
- OpenAlex
- W2519928122
- Cited by
- 558
- References
- 3
- FWCI
- 26.69
- Type
- book chapter
- 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: The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing. https://app.cochat.ai/papers/10.1016/bs.aivir.2016.08.008
- The paper
- Snijder, E. J., Decroly, E., & Ziebuhr, J. (2016). The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing. Advances in Virus Research. https://doi.org/10.1016/bs.aivir.2016.08.008
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.