Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,478

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease

Open access
Dai, Wenhao, Zhang, Bing, Jiang, Xia-Ming, Su, Haixia, Li, Jian, Zhao, Yao, Xie, Xiong, Jin, Zhenming, Peng, Jingjing, Liu, Fengjiang, Li, Chunpu, Li, You, Bai, Fang, Wang, Haofeng, Cheng, Xi, Cen, Xiaobo, Hu, Shulei, Yang, Xiuna, Wang, Jiang, Liu, Xiang, Xiao, Gengfu, Jiang, Hualiang, Rao, Zihe, Zhang, Lei-Ke, Xu, Yechun, Yang, Haitao, Liu, Hong·2020·Science

Abstract

Promising antiviral protease inhibitors: With no vaccine or proven effective drug against the virus that causes coronavirus disease 2019 (COVID-19), scientists are racing to find clinical antiviral treatments. A promising drug target is the viral main protease M pro , which plays a key role in viral replication and transcription. Dai et al. designed two inhibitors, 11a and 11b, based on analyzing the structure of the M pro active site. Both strongly inhibited the activity of M pro and showed good antiviral activity in cell culture. Compound 11a had better pharmacokinetic properties and low toxicity when tested in mice and dogs, suggesting that this compound is a promising drug candidate. Science , this issue p. 1331

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1126/science.abb4489

Cites

8 of 8 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 8 references

Cited by

See all 1,478

Metadata

Authors
Dai, W., Zhang, B., Jiang, X.-M., Su, H., Li, J., Zhao, Y., Xie, X., Jin, Z., Peng, J., Liu, F., Li, C., Li, Y., Bai, F., Wang, H., Cheng, X., Cen, X., Hu, S., Yang, X., Wang, J., Liu, X., Xiao, G., Jiang, H., Rao, Z., Zhang, L.-K., Xu, Y., Yang, H., & Liu, H.
Venue
Science
Published
2020-06-19
Volume
368
Issue
6497
Pages
1331-1335
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W3020300207
Cited by
1,478
References
8
FWCI
35.58
Type
journal article
Language
en
Open access
hybrid

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: Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease. https://app.cochat.ai/papers/10.1126/science.abb4489
The paper
Dai, W., Zhang, B., Jiang, X.-M., Su, H., Li, J., Zhao, Y., Xie, X., Jin, Z., Peng, J., Liu, F., Li, C., Li, Y., Bai, F., Wang, H., Cheng, X., Cen, X., Hu, S., Yang, X., Wang, J., . . . Liu, H. (2020). Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease. Science. https://doi.org/10.1126/science.abb4489

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.