Quercetin as a potential treatment for COVID-19-induced acute kidney injury: Based on network pharmacology and molecular docking study
Open accessAbstract
Kidneys are one of the targets for SARS-CoV-2, it is reported that up to 36% of patients with SARS-CoV-2 infection would develop into acute kidney injury (AKI). AKI is associated with high mortality in the clinical setting and contributes to the transition of AKI to chronic kidney disease (CKD). Up to date, the underlying mechanisms are obscure and there is no effective and specific treatment for COVID-19-induced AKI. In the present study, we investigated the mechanisms and interactions between Quercetin and SARS-CoV-2 targets proteins by using network pharmacology and molecular docking. The renal protective effects of Quercetin on COVID-19-induced AKI may be associated with the blockade of the activation of inflammatory, cell apoptosis-related signaling pathways. Quercetin may also serve as SARS-CoV-2 inhibitor by binding with the active sites of SARS-CoV-2 main protease 3CL and ACE2, therefore suppressing the functions of the proteins to cut the viral life cycle. In conclusion, Quercetin may be a novel therapeutic agent for COVID-19-induced AKI. Inhibition of inflammatory, cell apoptosis-related signaling pathways may be the critical mechanisms by which Quercetin protects kidney from SARS-CoV-2 injury.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Quercetin may have beneficial renal-protective and senolytic-independent effects during SARS-CoV-2 infection.
“Quercetin may also have beneficial renal-protective and senolytic-independent effects during SARS-CoV-2 infection181.”
From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [181]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884 · see citing works
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890 · see citing works
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246 · see citing works
cytoHubba: identifying hub objects and sub-networks from complex interactome
Chin, C.-H., Chen, S., Wu, H.-H., Ho, C.-W., Ko, M., & Lin, C. (2014) · BMC Systems Biology · doi:10.1186/1752-0509-8-s4-s11 · Cited by 6,635 · see citing works
TCMSP: a database of systems pharmacology for drug discovery from herbal medicines
Ru, J., Li, P., Wang, J., Zhou, W., Li, B., Huang, C., Li, P., Guo, Z., Tao, W., Yang, Y., et al. (2014) · Journal of Cheminformatics · doi:10.1186/1758-2946-6-13 · Cited by 5,092 · see citing works
Cytoscape 2.8: new features for data integration and network visualization
Smoot, M. E., Ono, K., Ruscheinski, J., Wang, P., & Ideker, T. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq675 · Cited by 4,770 · see citing works
VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R
Chen, H., & Boutros, P. C. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-35 · Cited by 3,150 · see citing works
Kidney disease is associated with in-hospital death of patients with COVID-19
Cheng, Y., Luo, R., Wang, K., Zhang, M., Wang, Z., Dong, L., Li, J., Yao, Y., Ge, S., & Xu, G. (2020) · Kidney International · doi:10.1016/j.kint.2020.03.005 · Cited by 2,957 · see citing works
Self-citationSTRING: a database of predicted functional associations between proteins
von Mering, C. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg034 · Cited by 2,942 · see citing works
Piñero, J., Bravo, À., Queralt-Rosinach, N., Gutiérrez-Sacristán, A., Deu-Pons, J., Centeno, E., García-García, J., Sanz, F., & Furlong, L. I. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw943 · Cited by 2,680 · see citing works
Molecular Docking: Shifting Paradigms in Drug Discovery
Pinzi, L., & Rastelli, G. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20184331 · Cited by 2,450 · see citing works
UniProt: the universal protein knowledgebase
The UniProt Consortium (2018) · Nucleic Acids Research · doi:10.1093/nar/gky092 · Cited by 2,043 · see citing works
SwissTargetPrediction: a web server for target prediction of bioactive small molecules
Gfeller, D., Grosdidier, A., Wirth, M., Daina, A., Michielin, O. A., & Zoete, V. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku293 · Cited by 1,811 · see citing works
Renal histopathological analysis of 26 postmortem findings of patients with COVID-19 in China
Su, H., Yang, M., Wan, C., Yi, L.-X., Tang, F., Zhu, H.-Y., Yi, F., Yang, H.-C., Fogo, A. B., Nie, X., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.04.003 · Cited by 1,763 · see citing works
Acute kidney injury in patients hospitalized with COVID-19
Hirsch, J. S., Ng, J. H., Ross, D. W., Sharma, P., Shah, H. H., Barnett, R. L., Hazzan, A. D., Fishbane, S., Jhaveri, K. D., Abate, M., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.05.006 · Cited by 1,523 · see citing works
Hickson, L. J., Langhi Prata, L. G. P., Bobart, S. A., Evans, T. K., Giorgadze, N., Hashmi, S. K., Herrmann, S. M., Jensen, M. D., Jia, Q., Jordan, K. L., et al. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.08.069 · Cited by 1,383 · see citing works
The role of ligand efficiency metrics in drug discovery
Hopkins, A. L., Keserü, G. M., Leeson, P. D., Rees, D. C., & Reynolds, C. H. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4163 · Cited by 1,181 · see citing works
Han, H. W., Ma, Q., Li, C., Liu, R., Zhao, L. Y., Wang, W., Zhang, P., Liu, X., Gao, G., Liu, F., et al. (2020) · Emerging Microbes & Infections · doi:10.1080/22221751.2020.1770129 · Cited by 1,177 · see citing works
Self-citationYang, Y., Islam, M. S., Wang, J., Li, Y., & Chen, X. (2020) · International Journal of Biological Sciences · doi:10.7150/ijbs.45538 · Cited by 965 · see citing works
GeneCards: integrating information about genes, proteins and diseases
Rebhan, M. (1997) · Trends in Genetics · doi:10.1016/s0168-9525(97)01103-7 · Cited by 776 · see citing works
Amberger, J. S., & Hamosh, A. (2017) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.27 · Cited by 741 · see citing works
Kidney involvement in COVID-19 and rationale for extracorporeal therapies
Ronco, C., & Reis, T. D. A. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0284-7 · Cited by 531 · see citing works
Acute kidney injury in critically ill patients with COVID-19
Gabarre, P., Dumas, G., Dupont, T., Darmon, M., Azoulay, É., & Zafrani, L. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-06153-9 · Cited by 526 · see citing works
Biancatelli, R. M. L. C., Berrill, M., Catravas, J. D., & Marik, P. E. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.01451 · Cited by 512 · see citing works
Feline coronavirus drug inhibits the main protease of SARS-CoV-2 and blocks virus replication
Vuong, W., Khan, M. B., Fischer, C., Arutyunova, E. I., Lamer, T., Shields, J. A., Saffran, H. A., McKay, R. T., van Belkum, M. J., Joyce, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18096-2 · Cited by 455 · see citing works
An Overview of Scoring Functions Used for Protein–Ligand Interactions in Molecular Docking
Li, J., Fu, A., & Zhang, L. (2019) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-019-00327-w · Cited by 440 · see citing works
Ultrastructural Evidence for Direct Renal Infection with SARS-CoV-2
Farkash, E. A., Wilson, A. M., & Jentzen, J. M. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020040432 · Cited by 350 · see citing works
The case of complement activation in COVID-19 multiorgan impact
Noris, M., Benigni, A., & Remuzzi, G. (2020) · Kidney International · doi:10.1016/j.kint.2020.05.013 · Cited by 337 · see citing works
Roles of flavonoids against coronavirus infection
Russo, M., Moccia, S., Spagnuolo, C., Tedesco, I., & Russo, G. L. (2020) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2020.109211 · Cited by 326 · see citing works
SARS-CoV-2 renal tropism associates with acute kidney injury
Braun, F., Lütgehetmann, M., Pfefferle, S., Wong, M. N., Carsten, A., Lindenmeyer, M. T., Nörz, D. S., Heinrich, F., Meißner, K., Wichmann, D., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31759-1 · Cited by 308 · see citing works
Ursu, O., Rayan, A., Goldblum, A., & Oprea, T. I. (2011) · WIREs Computational Molecular Science · doi:10.1002/wcms.52 · Cited by 276 · see citing works
Huang, Y., Bai, C., He, F., Xie, Y., & Zhou, H. (2020) · Pharmacological Research · doi:10.1016/j.phrs.2020.104939 · Cited by 261 · see citing works
Quercetin ameliorates kidney injury and fibrosis by modulating M1/M2 macrophage polarization
Lu, H., Wu, L., Liu, L., Ruan, Q., Zhang, X., Hong, W., Wu, S., Jin, G., & Bai, Y. (2018) · Biochemical Pharmacology · doi:10.1016/j.bcp.2018.05.007 · Cited by 252 · see citing works
Coronaviruses pathogenesis, comorbidities and multi-organ damage – A review
Renu, K., Prasanna, P. L., & Gopalakrishnan, A. V. (2020) · Life Sciences · doi:10.1016/j.lfs.2020.117839 · Cited by 244 · see citing works
Abián, O., Ortega-Alarcón, D., Jiménez-Alesanco, A., Ceballos-Laita, L., Vega, S., Reyburn, H., Rizzuti, B., & Velázquez-Campoy, A. (2020) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2020.07.235 · Cited by 223 · see citing works
Getting the most out of PubChem for virtual screening
Kim, S. (2016) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2016.1216967 · Cited by 218 · see citing works
Tao, Q., Du, J., Li, X., Zeng, J., Tan, B., Xu, J., Lin, W., & Chen, X. (2020) · Drug Development and Industrial Pharmacy · doi:10.1080/03639045.2020.1788070 · Cited by 215 · see citing works
Renal complications in COVID-19: a systematic review and meta-analysis
Kunutsor, S. K., & Laukkanen, J. A. (2020) · Annals of Medicine · doi:10.1080/07853890.2020.1790643 · Cited by 209 · see citing works
Ding, T., Wang, S., Zhang, X., Zai, W., Fan, J., Chen, W., Bian, Q., Luan, J., Shen, Y., Zhang, Y., et al. (2018) · Phytomedicine · doi:10.1016/j.phymed.2018.01.026 · Cited by 198 · see citing works
Analysis on herbal medicines utilized for treatment of COVID-19
Luo, L., Jiang, J., Wang, C., et al. (2020) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2020.05.007 · Cited by 176 · see citing works
Glinsky, G. V. (2020) · Biomedicines · doi:10.3390/biomedicines8050129 · Cited by 162 · see citing works
Vijayakumar, B. G., Ramesh, D., Joji, A., prakasan, J. J., & Kannan, T. (2020) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2020.173448 · Cited by 147 · see citing works
Tan, R., Wang, C., Deng, C., Zhong, X., Yan, Y., Luo, Y., Lan, H., He, T., & Wang, L. (2019) · Phytotherapy Research · doi:10.1002/ptr.6507 · Cited by 125 · see citing works
Self-citationMa, Q., Pan, W., Li, R., et al. (2020) · Pharmacological Research · doi:10.1016/j.phrs.2020.104850 · Cited by 119 · see citing works
Hu, Y., Song, Y., Liang, Y., & Li, R. (2018) · Medical Science Monitor · doi:10.12659/msm.909259 · Cited by 96 · see citing works
Aucoin, M., Cooley, K., Saunders, P. R., Cardozo, V., Remy, D., Cramer, H., Abad, C. N., & Hannan, N. (2020) · Advances in Integrative Medicine · doi:10.1016/j.aimed.2020.07.007 · Cited by 86 · see citing works
Duret, P., Sebbag, E., Mallick, A., et al. (2020) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2020-217362 · Cited by 82 · see citing works
Williamson, G., & Kerimi, A. (2020) · Biochemical Pharmacology · doi:10.1016/j.bcp.2020.114123 · Cited by 81 · see citing works
Ahmed, S. S. S. J., & Veerabathiran, R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040654 · Cited by 77 · see citing works
Liu, X., Sun, N., Mo, N., Lu, S., Song, E., Ren, C., & Li, Z. (2019) · Food & Function · doi:10.1039/c9fo00373h · Cited by 76 · see citing works
Self-citationFatal Outcomes of COVID-19 in Patients with Severe Acute Kidney Injury
Lim, J., Park, S.-H., Jeon, Y., Cho, J., Jung, H., Choi, J., Kim, C., Lee, Y.-H., Seo, H., Lee, J., et al. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9061718 · Cited by 73 · see citing works
Gu, Y.-Y., Chen, M., May, B. H., et al. (2018) · Phytomedicine · doi:10.1016/j.phymed.2018.10.004 · Cited by 64 · see citing works
Self-citationPathogenetic profiling of COVID-19 and SARS-like viruses
Nain, Z., Rana, H. K., Lió, P., Islam, S. M. S., Summers, M. A., & Moni, M. A. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa173 · Cited by 64 · see citing works
Ruan, X., Du, P. F., Zhao, K. F., Huang, J., Xia, H., Dai, D., Huang, S., Cui, X., Liu, L., & Zhang, J. (2020) · Chinese Medicine · doi:10.1186/s13020-020-00346-6 · Cited by 64 · see citing works
Leija-Martínez, J. J., Huang, F.-Y., Del-Río-Navarro, B., Sánchez-Muñoz, F., Muñoz-Hernández, O., Giacoman-Martínez, A., Hall-Mondragon, M. S., & Espinosa-Velazquez, D. (2020) · Medical Hypotheses · doi:10.1016/j.mehy.2020.109935 · Cited by 54 · see citing works
Angiotensin-converting enzyme 2 and renal disease
Williams, V. R., & Scholey, J. W. (2017) · Current Opinion in Nephrology & Hypertension · doi:10.1097/mnh.0000000000000378 · Cited by 53 · see citing works
Severe Acute Kidney Injury in Patients with COVID-19 and Acute Respiratory Distress Syndrome
Chaïbi, K., Dao, M., Pham, T. O., et al. (2020) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202005-1524le · Cited by 41 · see citing works
Fatoki, T. H., Ibraheem, O., Ogunyemi, I. O., et al. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1794971 · Cited by 39 · see citing works
Wang, M., Fu, D., Yao, L., & Li, J. (2020) · Combinatorial Chemistry & High Throughput Screening · doi:10.2174/1386207323666200806164635 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
SARS-CoV-2, COVID-19 and the aging immune system
Bartleson, J. M., Radenkovic, D., Covarrubias, A. J., Furman, D., Winer, D. A., & Verdin, E. (2021) · Nature Aging · doi:10.1038/s43587-021-00114-7 · Cited by 359 · see citing works
- Authors
- Gu, Y.-Y., Zhang, M., Cen, H., Wu, Y.-F., Lu, Z., Lu, F., Liu, X.-S., & Lan, H.-Y.
- Affiliations
- Guangdong Provincial Hospital of Chinese Medicine (CN)
- Chinese University of Hong Kong (HK)
- Corresponding author
- Liu, Xu-Sheng
- Lan, Hui-Yao
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2021-01-14
- Volume
- 16
- Issue
- 1
- Pages
- e0245209
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7808608
- OpenAlex
- W3120353614
- Cited by
- 75
- References
- 59
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 14 · 2023: 16 · 2022: 20 · 2021: 15
- FWCI
- 8.53
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Lui Che Woo Institute of Innovative Medicine (14117418, 14104019)
- National Natural Science Foundation of China (R4012-18, 81903956, 14117418, 14104019)
- Chinese Academy of Medical Sciences
- Health and Medical Research Fund (14152321, Grants HMRF 05161326, 05161326, 06173986, HMRF 05161326)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Keywords
- quercetin, COVID-19 pandemic, acute kidney injury, SARS-CoV-2, main protease, ACE2, apoptosis, renal protection, antiviral agents, chronic kidney disease
- MeSH terms
- COVID-19, SARS-CoV-2, COVID-19 Drug Treatment, Humans, Quercetin, Databases, Factual, Protein Interaction Mapping, Databases, Genetic, Acute Kidney Injury, Protein Interaction Maps, Molecular Docking Simulation
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
