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Phytoconstituents of Artemisia Annua as potential inhibitors of SARS CoV2 main protease: an in silico study

Irfan et al., BMC Infectious Diseases, doi:10.1186/s12879-024-09387-w
May 2024  
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Quercetin for COVID-19
24th treatment shown to reduce risk in July 2021, now with p = 0.0031 from 11 studies.
No treatment is 100% effective. Protocols combine treatments.
5,100+ studies for 110 treatments. c19early.org
In Silico study showing that quercetin binds strongly to the SARS-CoV-2 main protease (Mpro) and may be a potential inhibitor of viral replication. Authors screened 25 compounds from Artemisia annua and found that quercetin had one of the best docking scores against Mpro, forming two hydrogen bonds and several hydrophobic interactions with key residues in the protein's active site. Quercetin was identified as one of the top hits along with rutin, casticin, chrysoplenetin, apigenin, artemetin, artesunate, scopolin and sitogluside. Chrysoplenetin was the most promising lead compound after ADMET analysis.
71 preclinical studies support the efficacy of quercetin for COVID-19:
In Silico studies predict inhibition of SARS-CoV-2, or minimization of side effects, with quercetin or metabolites via binding to the spikeA,2,8,9,21,23,24,29,37,38,40,41,61-63, MproB,2,6,8,10,12,14,16,17,19,22,23,29,33,35-37,41,42,44,62-64, RNA-dependent RNA polymeraseC,2,8,31,63, PLproD,2,36,44, ACE2E,21,22,27,36,40,62, TMPRSS2F,21, nucleocapsidG,2, helicaseH,2,28,33, endoribonucleaseI,38, NSP16/10J,5, cathepsin LK,25, Wnt-3L,21, FZDM,21, LRP6N,21, ezrinO,39, ADRPP,37, NRP1Q,40, EP300R,15, PTGS2S,22, HSP90AA1T,15,22, matrix metalloproteinase 9U,30, IL-6V,20,34, IL-10W,20, VEGFAX,34, and RELAY,34 proteins. In Vitro studies demonstrate inhibition of the MproB,14,45,50,58 protein, and inhibition of spike-ACE2 interactionZ,46. In Vitro studies demonstrate efficacy in Calu-3AA,49, A549AB,20, HEK293-ACE2+AC,57, Huh-7AD,24, Caco-2AE,48, Vero E6AF,18,41,48, mTECAG,51, and RAW264.7AH,51 cells. Animal studies demonstrate efficacy in K18-hACE2 miceAI,54, db/db miceAJ,51,60, BALB/c miceAK,59, and rats65. Quercetin reduced proinflammatory cytokines and protected lung and kidney tissue against LPS-induced damage in mice59, inhibits LPS-induced cytokine storm by modulating key inflammatory and antioxidant pathways in macrophages4, and inhibits SARS-CoV-2 ORF3a ion channel activity, which contributes to viral pathogenicity and cytotoxicity53.
Irfan et al., 15 May 2024, peer-reviewed, 7 authors. Contact: dr.erum@cust.edu.pk, abdi@pgu.ac.ir, yasir_waheed_199@hotmail.com.
In Silico studies are an important part of preclinical research, however results may be very different in vivo.
This PaperQuercetinAll
Phytoconstituents of Artemisia Annua as potential inhibitors of SARS CoV2 main protease: an in silico study
Eraj Irfan, Erum Dilshad, Faisal Ahmad, Fahad Nasser Almajhdi, Tajamul Hussain, Gholamreza Abdi, Yasir Waheed
BMC Infectious Diseases, doi:10.1186/s12879-024-09387-w
Background In November 2019, the world faced a pandemic called SARS-CoV-2, which became a major threat to humans and continues to be. To overcome this, many plants were explored to find a cure. Methods Therefore, this research was planned to screen out the active constituents from Artemisia annua that can work against the viral main protease Mpro as this non-structural protein is responsible for the cleavage of replicating enzymes of the virus. Twenty-five biocompounds belonging to different classes namely alpha-pinene, beta-pinene, carvone, myrtenol, quinic acid, caffeic acid, quercetin, rutin, apigenin, chrysoplenetin, arteannunin b, artemisinin, scopoletin, scoparone, artemisinic acid, deoxyartemisnin, artemetin, casticin, sitogluside, beta-sitosterol, dihydroartemisinin, scopolin, artemether, artemotil, artesunate were selected. Virtual screening of these ligands was carried out against drug target Mpro by CB dock. Results Quercetin, rutin, casticin, chrysoplenetin, apigenin, artemetin, artesunate, sopolin and sito-gluside were found as hit compounds. Further, ADMET screening was conducted which represented Chrysoplenetin as a lead compound. Azithromycin was used as a standard drug. The interactions were studied by PyMol and visualized in LigPlot. Furthermore, the RMSD graph shows fluctuations at various points at the start of simulation in Top1 (Azithromycin) complex system due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points resulting in increased RMSD with a time frame of 50 ns. But this change remains stable after the extension of simulation time intervals till 100 ns. On other side, the Top2 complex system remains highly stable throughout the time scale. No such structural dynamics were observed bu the ligand attached to the active site residues binds strongly. Conclusion This study facilitates researchers to develop and discover more effective and specific therapeutic agents against SARS-CoV-2 and other viral infections. Finally, chrysoplenetin was identified as a more potent drug candidate to act against the viral main protease, which in the future can be helpful.
Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s12879-024-09387-w. Supplementary Materials 1: Table S1 . Applicability of Lipinski rule. Table S2 Selected ligands with structural information. Table S3 Absorption properties of the ligands and standard drug. Table S4 Distribution properties of the ligands and standard drug. Table S5 Lipinski's Rule Comparison. Authors' contributions Eraj Irfan: Concept, methodology, formal analysis, data curation, manuscript writing, final approval. Erum Dilshad: Concept, methodology, formal analysis, data curation, manuscript editing, Supervision, final approval. Faisal Ahmad: methodology, formal analysis, data curation, manuscript writing, manuscript editing, final approval. Fahad N Almajhdi: methodology, formal analysis, data curation, manuscript editing, Supervision, resources, final approval. Tajamul Hussain: methodology, formal analysis, data curation, manuscript editing, resources, final approval. Gholamreza Abdi: methodology, formal analysis, data curation, manuscript editing, resources, final approval. Yasir Waheed: Concept, methodology, formal analysis, data curation, manuscript editing, Supervision, resources, final approval. Declarations Ethics approval and consent to participate It's a computational work, ethical approval not required. Consent for publication Not applicable. Competing interests The authors declare no competing interests. ..
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' '2013;13:1273–89.', 'journal-title': 'Curr Top Med Chem'}], 'container-title': 'BMC Infectious Diseases', 'original-title': [], 'language': 'en', 'link': [ { 'URL': 'https://link.springer.com/content/pdf/10.1186/s12879-024-09387-w.pdf', 'content-type': 'application/pdf', 'content-version': 'vor', 'intended-application': 'text-mining'}, { 'URL': 'https://link.springer.com/article/10.1186/s12879-024-09387-w/fulltext.html', 'content-type': 'text/html', 'content-version': 'vor', 'intended-application': 'text-mining'}, { 'URL': 'https://link.springer.com/content/pdf/10.1186/s12879-024-09387-w.pdf', 'content-type': 'application/pdf', 'content-version': 'vor', 'intended-application': 'similarity-checking'}], 'deposited': { 'date-parts': [[2024, 5, 15]], 'date-time': '2024-05-15T11:03:32Z', 'timestamp': 1715771012000}, 'score': 1, 'resource': { 'primary': { 'URL': 'https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-024-09387-w'}}, 'subtitle': [], 'short-title': [], 'issued': {'date-parts': [[2024, 5, 15]]}, 'references-count': 52, 'journal-issue': {'issue': '1', 'published-online': {'date-parts': [[2024, 12]]}}, 'alternative-id': ['9387'], 'URL': 'http://dx.doi.org/10.1186/s12879-024-09387-w', 'relation': {}, 'ISSN': ['1471-2334'], 'subject': [], 'container-title-short': 'BMC Infect Dis', 'published': {'date-parts': [[2024, 5, 15]]}, 'assertion': [ { 'value': '14 February 2024', 'order': 1, 'name': 'received', 'label': 'Received', 'group': {'name': 'ArticleHistory', 'label': 'Article History'}}, { 'value': '8 May 2024', 'order': 2, 'name': 'accepted', 'label': 'Accepted', 'group': {'name': 'ArticleHistory', 'label': 'Article History'}}, { 'value': '15 May 2024', 'order': 3, 'name': 'first_online', 'label': 'First Online', 'group': {'name': 'ArticleHistory', 'label': 'Article History'}}, {'order': 1, 'name': 'Ethics', 'group': {'name': 'EthicsHeading', 'label': 'Declarations'}}, { 'value': 'It’s a computational work, ethical approval not required.', 'order': 2, 'name': 'Ethics', 'group': {'name': 'EthicsHeading', 'label': 'Ethics approval and consent to participate'}}, { 'value': 'Not applicable.', 'order': 3, 'name': 'Ethics', 'group': {'name': 'EthicsHeading', 'label': 'Consent for publication'}}, { 'value': 'The authors declare no competing interests.', 'order': 4, 'name': 'Ethics', 'group': {'name': 'EthicsHeading', 'label': 'Competing interests'}}], 'article-number': '495'}
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