In Silico Approach for Pro-inflammatory Protein Interleukin 1β and Interleukin-1 Receptor Antagonist Protein Docking as Potential Therapy for COVID-19 Disease
DOI:
https://doi.org/10.3889/oamjms.2022.7405Keywords:
COVID-19, Conditioned Medium Wharton’s Jelly Mesenchymal stem cells, Cytokine, Interleukin-1 receptor antagonist, Interleukin-1βAbstract
Background: Interleukin-1 receptor antagonist (IL-1Ra) also known as Anakinra is a receptor antagonist of IL-1 especially IL-1β. IL-1β increased in infected COVID-19 patient groups. This study aimed that the IL-1Ra contained in Conditioned Medium Wharton’s Jelly Mesenchymal Stem Cells (CM-WJMSCs) has the potential to inhibit IL-1β which is one of the cytokine storms that occur in COVID patients through an in-silico approach. Objective: This study aims to determine the effect of in silico approach pro-inflammatory protein interleukin 1β (IL-1 β) and interleukin-1 receptor antagonist protein as cytokine WJ-MSCs for potential treatment of COVID-19 disease. Methods: 3D structure using the homology modeling method on Swiss Model web-server. Molecular docking was performed to analyze the binding mode of the IL-1β related to COVID-19 with IL-1Ra and the docking results were fixed using FireDock web-server. Results: These results of the docking of proteins between IL-1β and the CM-WJMSCs component, namely IL-1Ra showed that IL-1Ra has criteria for docking on IL-1β such as the good score for QMEAN, good CscoreLB, and BS-score results, and the lowest energy obtained was -585.1 KJ/mol. It can be predicted that IL-1Ra can inhibit IL-1β which causes cytokine storms in COVID-19 patients. Conclusion: So that there is a potential treatment of CM-WJMSCs on the severity of Covid-19 infection.
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Wilson AG, Symons JA, McDowell TL, McDevitt HO, Duff GW. Effects of a polymorphism in the human tumor necrosis factor α promoter on transcriptional activation. Proc Natl Acad Sci. 1997;94(7):3195-9. https://doi.org/10.1073/pnas.94.7.3195 PMid:9096369 DOI: https://doi.org/10.1073/pnas.94.7.3195
Chevalier X, Goupille P, Beaulieu AD, Burch FX, Bensen WG, Conrozier T, et al. Intraarticular injection of anakinra in osteoarthritis of the knee: A multicenter, randomized, double-blind, placebo-controlled study. Arthritis Care Res. 2009;61(3):344-52. https://doi.org/10.1002/art.24096 PMid:19248129 DOI: https://doi.org/10.1002/art.24096
Food and Drug Administration. Available from: https://www.accessdata.fda.gov/drugsatfda_docs/label/2011/103950s5116lbl.pdf [Last accessed on 2021 Jul 13].
Graf T. Differentiation plasticity of hematopoietic cells. Blood. 2002;99(9):3089-101. https://doi.org/10.1182/blood.v99.9.3089 DOI: https://doi.org/10.1182/blood.V99.9.3089
PMid:11964270
Watt FM, Hogan BL. Out of Eden: Stem cells and their niches. Science. 2000;287(5457):1427-30. https://doi.org/10.1126/science.287.5457.1427 PMid:10688781 DOI: https://doi.org/10.1126/science.287.5457.1427
Osugi M, Katagiri W, Yoshimi R, Inukai T, Hibi H, Ueda M, et al. Conditioned media from mesenchymal stem cells enhanced bone regeneration in rat calvarial bone defects. Tissue Eng Part A. 2012;18(13-14):1479-89. https://doi.org/10.1089/ten.TEA.2011.0325 PMid:22443121 DOI: https://doi.org/10.1089/ten.tea.2011.0325
Zagoura DS, Roubelakis MG, Bitsika V, Trohatou O, Pappa KI, Kapelouzou A, et al. Therapeutic potential of a distinct population of human amniotic fluid mesenchymal stem cells and their secreted molecules in mice with acute hepatic failure. Gut. 2012;61(6):894-906. https://doi.org/10.1136/gutjnl-2011-300908 PMid:21997562 DOI: https://doi.org/10.1136/gutjnl-2011-300908
Bermudez MA, Sendon-Lago J, Seoane S, Eiro N, Gonzalez F, Saa J, et al. Anti-inflammatory effect of conditioned medium from human uterine cervical stem cells in uveitis. Exp Eye Res. 2016;149:84-92. https://doi.org/10.1016/j.exer.2016.06.022 PMid:27381329 DOI: https://doi.org/10.1016/j.exer.2016.06.022
McElvaney OJ, McEvoy NL, McElvaney OF, Carroll TP, Murphy MP, Dunlea DM, et al. Characterization of the inflammatory response to severe COVID-19 illness. Am J Respir Crit Care Med. 2020;202(6):812-21. https://doi.org/10.1164/rccm.202005-1583OC PMid:32584597 DOI: https://doi.org/10.1164/rccm.202005-1583OC
Dinarello CA, Simon A, Van Der Meer JW. Treating inflammation by blocking interleukin-1 in a broad spectrum of diseases. Nat Rev Drug Discov. 2012;11(8):633-52. https://doi.org/10.1038/nrd3800 PMid:22850787 DOI: https://doi.org/10.1038/nrd3800
Ekins S, Mestres J, Testa B. In silico pharmacology for drug discovery: Methods for virtual ligand screening and profiling. Br J Pharmacol. 2007;152(1):9-20. https://doi.org/10.1038/sj.bjp.0707305 PMid:17549047 DOI: https://doi.org/10.1038/sj.bjp.0707305
Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: Homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46(1):W296-303. https://doi.org/10.1093/nar/gky427 DOI: https://doi.org/10.1093/nar/gky427
Zhang C, Freddolino PL, Zhang Y. COFACTOR: Improved protein function prediction by combining structure, sequence and protein-protein interaction information. Nucleic Acids Res. 2017;45(1):W291-9. https://doi.org/10.1093/nar/gkx366 PMid:28472402 DOI: https://doi.org/10.1093/nar/gkx366
Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, et al. The ClusPro web server for protein-protein docking. Nat Protoc. 2017;12(2):255. https://doi.org/10.1038/nprot.2016.169 PMid:28079879 DOI: https://doi.org/10.1038/nprot.2016.169
Andrusier N, Nussinov R, Wolfson HJ. FireDock: Fast interaction refinement in molecular docking. Proteins 2007;69(1):139-59. https://doi.org/10.1002/prot.21495 PMid:17598144 DOI: https://doi.org/10.1002/prot.21495
Mashiach E, Schneidman-Duhovny D, Andrusier N, Nussinov R, Wolfson HJ. FireDock: A web server for fast interaction refinement in molecular docking. Nucleic Acids Res 2008;36(2):W229-32. https://doi.org/10.1093/nar/gkn186 PMid:18424796 DOI: https://doi.org/10.1093/nar/gkn186
Lovell SC, Davis IW, Arendall WB, Word JM, Prisant MG, Richardson JS, et al. Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins Struct Funct Bioinform. 2003;50(3):437-50. https://doi.org/10.1002/prot.10286 DOI: https://doi.org/10.1002/prot.10286
UniProt Consortium. UniProt: A worldwide hub of protein knowledge. Nucleic Acids Res. 2019;945:D506-15. DOI: https://doi.org/10.1093/nar/gky1049
Wu CH, Huang H, Arminski L, Castro-Alvear J, Chen Y, Hu ZZ, et al. The protein information resource: An integrated public resource of functional annotation of proteins. Nucleic Acids Res. 2002;30(1):35-7. https://doi.org/10.1093/nar/30.1.35 PMid:11752247 DOI: https://doi.org/10.1093/nar/30.1.35
Boeckmann B, Bairoch A, Apweiler R, Blatter MC, Estreicher A, Gasteiger E, et al. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res. 2003;31(1):365-70. https://doi.org/10.1093/nar/gkg095 PMid:12520024 DOI: https://doi.org/10.1093/nar/gkg095
Bordoli L, Kiefer F, Arnold K, Benkert P, Battey J, Schwede T, et al. Protein structure homology modeling using SWISS-MODEL workspace. Nat Protoc. 2009;4(1):1. https://doi.org/10.1038/nprot.2008.197 PMid:19131951 DOI: https://doi.org/10.1038/nprot.2008.197
Roy A, Yang J, Zhang Y. COFACTOR: An accurate comparative algorithm for structure-based protein function annotation. Nucleic Acids Res. 2012;40(1):W471-7. https://doi.org/10.1093/nar/gks372 PMid:22570420 DOI: https://doi.org/10.1093/nar/gks372
Pi M, Kapoor K, Ye R, Nishimoto SK, Smith JC, Baudry J, et al. Evidence for osteocalcin binding and activation of GPRC6A in β-cells. Endocrinology. 2016;157(5):1866-80. https://doi.org/10.1210/en.2015-2010 PMid:27007074 DOI: https://doi.org/10.1210/en.2015-2010
Lodish H, Berk A, Zipursky SL, Matsudaira P, Baltimore D, Darnell J. Molecular Cell Biology. 4th ed. United States: National Center for Biotechnology Information, Bookshelf; 2000.
Teoh TC, Salmah I, Tang JM. Molecular dynamics and docking of biphenyl: A potential attachment inhibitor for HIV-1 gp120 glycoprotein. Trop J Pharm Res. 2014;13(3):339-46. DOI: https://doi.org/10.4314/tjpr.v13i3.4
Anakinra (Kineret) Prescribing Information. Food and Drug Administration. Available from: https://www.accessdata.fda.gov/drugsatfda_docs/label/2012/103950s5136lbl.pdf [Last accessed on 2021 Jul 20].
Cavalli G, De Luca G, Campochiaro C, Della-Torre E, Ripa M, Canetti D, et al. Interleukin-1 blockade with high-dose anakinra in patients with COVID-19, acute respiratory distress syndrome, and hyperinflammation: A retrospective cohort study. Lancet Rheumatol. 2020;2(6):E325-31. https://doi.org/10.1016/S2665-9913(20)30127-2 DOI: https://doi.org/10.1016/S2665-9913(20)30127-2
Zhang W, Zhao Y, Zhang F, Wang Q, Li T, Liu Z, et al. The use of anti-inflammatory drugs in the treatment of people with severe coronavirus disease 2019 (COVID-19): The Perspectives of clinical immunologists from China. Clin Immun. 2020;214:108393. https://doi.org/10.1016/j.clim.2020.108393 PMid:32222466 DOI: https://doi.org/10.1016/j.clim.2020.108393
Day M. Covid-19: Ibuprofen should not be used for managing symptoms, say doctors and scientists. BMJ. 2020;368:m1086. https://doi.org/10.1136/bmj.m1086 PMid:32184201 DOI: https://doi.org/10.1136/bmj.m1086
FitzGerald GA. Misguided drug advice for COVID-19. Science. 2020;367(6485):1434. https://doi.org/10.1126/science.abb8034 PMid:32198292 DOI: https://doi.org/10.1126/science.abb8034
Little P. Non-steroidal anti-inflammatory drugs and covid-19. Lancet Rheumatol 2020;3(7):E465-6. DOI: https://doi.org/10.1016/S2665-9913(21)00144-2
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Copyright (c) 2022 Wahyu Widowati, Kusworini Handono, Marlina Marlina, Ika Adhani Sholihah, Diana Krisanti Jasaputra, Teresa Liliana Wargasetia, Mawar Subangkit, Ahmad Faried, Ermi Girsang, I Nyoman Lister, Chrismis Novalinda Ginting, Ita Margaretha Nainggolan, Rizal Rizal, Hanna Kusuma, Linda Chiuman (Author)
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