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Sitagliptin: a potential drug for the treatment of COVID-19?


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1. C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, L. Zhang, G. Fan, J. Xu and X. Gu, Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China, Lancet395 (2020) 497–506; https://doi.org/10.1016/S0140-673610.1016/S0140-6736(20)30183-5Search in Google Scholar

2. H. Lu, C. W. Stratton and Y. W. Tang, Outbreak of pneumonia of unknown etiology in Wuhan China: the mystery and the miracle, J. Med. Virol.92 (2020) 401–402; https://doi.org/10.1002/jmv.2567810.1002/jmv.25678716662831950516Search in Google Scholar

3. P. Colson, J. M. Rolain and D. Raoult, Chloroquine for the 2019 novel coronavirus SARS Cov2, Int. J. Antimicrob. Agents 55 (2020) Article ID 105923 (3 pages); https://doi.org/10.1016/j.ijantimicag.2020.10592310.1016/j.ijantimicag.2020.105923713486632070753Search in Google Scholar

4. M. Wang, R. Cao, L. Zhang, X. Yang, J. Liu, M. Xu, Z. Shi, Z. Hu, W. Zhong and G. Xiao, Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro, Cell Res.30 (2020) 269–271; https://doi.org/10.1038/s41422-020-0282-010.1038/s41422-020-0282-0705440832020029Search in Google Scholar

5. W. Ko, J. Rolain, N. Lee, P. Chen, C. Huang and P. Lee, Arguments in favour of remdesivir for treating SARS-CoV-2 infections, Int. J. Antimicrob. Agents (2020) Article ID 105933 (4 pages); https://doi.org/10.1016/j.ijantimicag.2020.10593310.1016/j.ijantimicag.2020.105933713536432147516Search in Google Scholar

6. N. Vankadari and J. A. Wilce, Emerging WuHan (COVID-19) coronavirus: glycan shield and structure prediction of spike glycoprotein and its interaction with human CD26, Emerg. Microbes Infect.9 (2020) 601–604; https://doi.org/10.1080/22221751.2020.173956510.1080/22221751.2020.1739565710371232178593Search in Google Scholar

7. W. Song, M. Gui, X. Wang and Y. Xiang, Cryo-EM structure of the SARS coronavirus spike glyco-protein in complex with its host cell receptor ACE2, PLoS Pathog.14 (2018) e1007236 (19 pages); https://doi.org/10.1371/journal.ppat.100723610.1371/journal.ppat.1007236610729030102747Search in Google Scholar

8. Y. Zhou, Y. Hou, J. Shen, Y. Huang, W. Martin and F. Cheng, Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2, Cell Discov.6 (2020) 1–18; https://doi.org/10.1038/s41421-020-0153-310.1038/s41421-020-0153-3707333232194980Search in Google Scholar

9. A. A. Al-Qahtani, K. Lyroni, M. Aznaourova, M. Tseliou, M. R. Al-Anazi, M. N. Al-Ahdal, S. Alkahtani, G. Sourvinos and C. Tsatsanis, Middle east respiratory syndrome corona virus spike glycoprotein suppresses macrophage responses via DPP4-mediated induction of IRAK-M and PPARγ, Oncotarget8 (2017) 9053–9066; https://doi.org/10.18632/oncotarget.1475410.18632/oncotarget.14754535471428118607Search in Google Scholar

10. A. Makdissi, H. Ghanim, M. Vora, K. Green, S. Abuaysheh, A. Chaudhuri, S. Dhindsa and P. Dandona, Sitagliptin exerts an antinflammatory action, J. Clin. Endocrinol. Metab.97 (2012) 3333–3341; https://doi.org/10.1210/jc.2012-154410.1210/jc.2012-1544343158022745245Search in Google Scholar

11. J. R. Ussher and D. J. Drucker, Cardiovascular biology of the incretin system, Endocr. Rev.33 (2012) 187–215; https://doi.org/10.1210/er.2011-105210.1210/er.2011-1052352878522323472Search in Google Scholar

12. H. Yanai, Dipeptidyl peptidase-4 inhibitor sitagliptin significantly reduced hepatitis C virus replication in a diabetic patient with chronic hepatitis C virus infection, Hepatobiliary Pancreat. Dis. Int.13 (2014) 556; https://doi.org/10.1016/S1499-3872(14)60308-810.1016/S1499-3872(14)60308-8Search in Google Scholar

13. M. P. Dubé, E. S. Chan, J. E. Lake, B. Williams, J. Kinslow, A. Landay, R. W. Coombs, M. Floris-Moore, H. J. Ribaudo and K. E. Yarasheski, A randomized, double-blinded, placebo-controlled trial of sitagliptin for reducing inflammation and immune activation in treated and suppressed human immunodeficiency virus infection, Clin. Infect. Dis.69 (2019) 1165–1172; https://doi.org/10.1093/cid/ciy105110.1093/cid/ciy1051674381430535188Search in Google Scholar

14. M. Liao, Y. Liu, J. Yuan, Y. Wen, G. Xu, J. Zhao, L. Chen, J. Li, X. Wang, F. Wang, L. Liu, S. Zhang and Z. Zhang, The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing, medRxiv preprint, posted February 26, 2020 (23 pages); https://doi.org/10.1101/2020.02.23.2002669010.1101/2020.02.23.20026690Search in Google Scholar

15. P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, N. Amin, B. Schwikowski and T. Ideker, Cytoscape: a software environment for integrated models of biomolecular interaction networks, Genome Res.13 (2013) 2498–2504; https://doi.org/10.1101/gr.123930310.1101/gr.123930340376914597658Search in Google Scholar

16. D. Szklarczyk, A. L. Gable, D. Lyon, A. Junge, S. Wyder, J. Huerta-Cepas, M. Simonovic, N. T. Doncheva, J. H. Morris, P. Bork, L. J. Jensen and C. V. Mering, STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets, Nucleic Acids Res.47 (2019) D607–D613; https://doi.org/10.1093/nar/gky113110.1093/nar/gky1131632398630476243Search in Google Scholar

17. A. Chatr-Aryamontri, A. Ceol, L. M. Palazzi, G. Nardelli, M. V. Schneider, L. Castagnoli and G. Cesareni, MINT: the Molecular INTeraction database, Nucleic Acids Res.35 (2007) D572–D574; https://doi.org/10.1093/nar/gkl95010.1093/nar/gkl950175154117135203Search in Google Scholar

18. S. Peri, J. D. Navarro, T. Z. Kristiansen, R. Amanchy, V. Surendranath, B. Muthusamy, T. Gandhi, K. Chandrika, N. Deshpande and S. Suresh, Human protein reference database as a discovery resource for proteomics, Nucleic Acids Res.32 (2004) D497–D501; https://doi.org/10.1093/nar/gkh07010.1093/nar/gkh07030880414681466Search in Google Scholar

19. R. Wang, X. Fang, Y. Lu and S. Wang, The PDBbind database: Collection of binding affinities for protein- ligand complexes with known three-dimensional structures, J. Med. Chem.47 (2004) 2977–2980; https://doi.org/10.1021/jm030580l10.1021/jm030580l15163179Search in Google Scholar

20. L. Salwinski, C. S. Miller, A. J. Smith, F. K. Pettit, J. U. Bowie and D. Eisenberg, The database of interacting proteins: 2004 update, Nucleic Acids Res.32 (2004) D449–D451; https://doi.org/10.1093/nar/gkh08610.1093/nar/gkh08630882014681454Search in Google Scholar

21. B. J. Breitkreutz, C. Stark, T. Reguly, L. Boucher, A. Breitkreutz, M. Livstone, R. Oughtred, D. H. Lackner, J. Bähler and V. Wood, The BioGRID interaction database: 2008 update, Nucleic Acids Res.36 (2008) D637–D640; https://doi.org/10.1093/nar/gkm100110.1093/nar/gkm1001223887318000002Search in Google Scholar

22. M. Kanehisa, M. Araki, S. Goto, M. Hattori, M. Hirakawa, M. Itoh, T. Katayama, S. Kawashima, S. Okuda and T. Tokimatsu, KEGG for linking genomes to life and the environment, Nucleic Acids Res.36 (2007) D480–D484; https://doi.org/10.1093/nar/gkm88210.1093/nar/gkm882Search in Google Scholar

23. D. Croft, A. F. Mundo, R. Haw, M. Milacic, J. Weiser, G. Wu, M. Caudy, P. Garapati, M. Gillespie and M. R. Kamdar, The Reactome pathway knowledgebase, Nucleic Acids Res.42 (2014) D472–D477; https://doi.org/10.1093/nar/gkt110210.1093/nar/gkt1102Search in Google Scholar

24. I. M. Keseler, J. Collado-Vides, S. Gama-Castro, J. Ingraham, S. Paley, I. T. Paulsen, M. Peralta-Gil and P. D. Karp, EcoCyc: a comprehensive database resource for Escherichia coli, Nucleic Acids Res.33 (2005) D334–D337; https://doi.org/10.1093/nar/gkq114310.1093/nar/gkq1143Search in Google Scholar

25. S. Krupa, K. Anthony, J. Buchoff, M. Day, T. Hannay and C. Schaefer, Pathway Interaction Database: A cell signaling resource, Nature446 (2007) 153–158; https://doi.org/10.1038/npre.2007.1311.110.1038/npre.2007.1311.1Search in Google Scholar

26. Gene Ontology Consortium, The Gene Ontology (GO) database and informatics resource, Nucleic Acids Res.32 (2004) D258–D261; https://doi.org/10.1093/nar/gkh03610.1093/nar/gkh036Search in Google Scholar

27. D. Kim, L. Wang, M. Beconi, G. J. Eiermann, M. H. Fisher, H. He, G. J. Hickey, J. E. Kowalchick, B. Leiting and K. Lyons, (2R)-4-oxo-4-[3-(trifluoromethyl)-5,6-dihydro[1,2,4]triazolo[4,3-a] pyrazin-7(8H)-yl]-1-(2,4,5-trifluorophenyl)butan-2-amine: a potent, orally active dipeptidyl peptidase IV inhibitor for the treatment of type 2 diabetes, J. Med. Chem.48 (2005) 141–151; https://doi.org/10.1021/jm049315610.1021/jm0493156Search in Google Scholar

28. H. Berman, K. Henrick and H. Nakamura, Announcing the worldwide protein data bank, Nat. Struct. Mol. Biol.10 (2003) 980; https://doi.org/10.1038/nsb1203-98010.1038/nsb1203-980Search in Google Scholar

29. R. Lu, X. Zhao, J. Li, P. Niu, B. Yang, H. Wu, W. Wang, H. Song, B. Huang and N. Zhu, Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding, Lancet395 (2020) 565–574; https://doi.org/10.1016/S0140-6736(20)30251-810.1016/S0140-6736(20)30251-8Search in Google Scholar

30. M. Hoffmann, H. Kleine-Weber, N. Krüger, M. Mueller, C. Drosten and S. Pöhlmann, The novel coronavirus 2019 (2019-nCoV) uses the SARS-coronavirus receptor ACE2 and the cellular protease TMPRSS2 for entry into target cells, bioRxiv preprint, posted January 31, 2020 (23 pages); https://doi.org/10.1101/2020.01.31.92904210.1101/2020.01.31.929042Search in Google Scholar

31. X. Zou, K. Chen, J. Zou, P. Han, J. Hao and Z. Han, Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection, Front. Med. (2020) (8 pages); https://doi.org/10.1007/s11684-020-0754-010.1007/s11684-020-0754-0708873832170560Search in Google Scholar

32. F. Qi, S. Qian, S. Zhang and Z. Zhang, Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses, Biochem. Biophys. Res. Commun. (2020) (7 pages); https://doi.org/10.1016/j.bbrc.2020.03.04410.1016/j.bbrc.2020.03.044715611932199615Search in Google Scholar

33. M. Abouelkheir and T. H. El-Metwally, Dipeptidyl peptidase-4 inhibitors can inhibit angiotensin converting enzyme, Eur. J. Pharmacol.862 (2019) Article ID 172638; https://doi.org/10.1016/j.ejphar.2019.17263810.1016/j.ejphar.2019.17263831491403Search in Google Scholar

34. A. S. Rose, A. R. Bradley, Y. Valasatava, L. M. Duarte, A. Prlić and P. W. Rose, NGL viewer: web-based molecular graphics for large complexes, Bioinformatics34 (2018) 3755–3758; https://doi.org/10.1093/bioinformatics/bty41910.1093/bioinformatics/bty419619885829850778Search in Google Scholar

35. N. Yang and H.-M. Shen, Targeting the endocytic pathway and autophagy process as a novel therapeutic strategy in COVID-19, Int. J. Biol. Sci.16 (2020) 1724–1731; https://doi.org/10.7150/ijbs.4549810.7150/ijbs.45498709802732226290Search in Google Scholar

36. H. Wang, P. Yang, K. Liu, F. Guo, Y. Zhang, G. Zhang and C. Jiang, SARS coronavirus entry into host cells through a novel clathrin-and caveolae-independent endocytic pathway, Cell Res.18 (2008) 290–301; https://doi.org/10.1038/cr.2008.1510.1038/cr.2008.15709189118227861Search in Google Scholar

37. Y. Inoue, N. Tanaka, Y. Tanaka, S. Inoue, K. Morita, M. Zhuang, T. Hattori and K. Sugamura, Clathrin-dependent entry of severe acute respiratory syndrome coronavirus into target cells expressing ACE2 with the cytoplasmic tail deleted, J. Virol.81 (2007) 8722–8729; https://doi.org/10.1128/JVI.00253-0710.1128/JVI.00253-07195134817522231Search in Google Scholar

38. C. Callebaut, B. Krust, E. Jacotot and A. G. Hovanessian, T cell activation antigen, CD26, as a cofactor for entry of HIV in CD4+ cells, Science262 (1993) 2045–2050; https://doi.org/10.1126/science.790347910.1126/science.79034797903479Search in Google Scholar

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