Prediction of the Effects of Variants and Differential Expression of Key Host Genes ACE2, TMPRSS2, and FURIN in SARS-CoV-2 Pathogenesis: An In Silico Approach

1. Chen, N, Zhou, M, Dong, X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507-513.
Google Scholar | Crossref | Medline2. Shereen, MA, Khan, S, Kazmi, A, Bashir, N, Siddique, R. COVID-19 infection: origin, transmission, and characteristics of human coronaviruses. J Adv Res. 2020;24:91-98. doi:10.1016/j.jare.2020.03.005.
Google Scholar | Crossref | Medline3. Ge, X-Y, Li, J-L, Yang, X-L, et al. Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor. Nature. 2013;503:535-538.
Google Scholar | Crossref | Medline | ISI4. Jartti, T, Jartti, L, Ruuskanen, O, Söderlund-Venermo, M. New respiratory viral infections. Curr Opin Pulm Med. 2012;18:271-278.
Google Scholar | Crossref | Medline | ISI5. Chan, PK, Chan, MC. Tracing the SARS-coronavirus. J Thorac Dis. 2013;5:S118.
Google Scholar6. Vijaykrishna, D, Smith, GJ, Zhang, JX, Peiris, J, Chen, H, Guan, Y. Evolutionary insights into the ecology of coronaviruses. J Virol. 2007;81:4012-4020.
Google Scholar | Crossref | Medline | ISI7. Desforges, M, Le Coupanec, A, Dubeau, P, et al. Human coronaviruses and other respiratory viruses: underestimated opportunistic pathogens of the central nervous system? Viruses. 2020;12:14.
Google Scholar | Crossref8. Chan-Yeung, M, Xu, RH. SARS: epidemiology. Respirology. 2003;8:S9-S14.
Google Scholar | Crossref9. http://www.emro.who.int/pandemic-epidemic-diseases/mers-cov/mers-situation-update-january-2020.html.
Google Scholar10. Chan, JF-W, Yuan, S, Kok, K-H, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395:514-523.
Google Scholar | Crossref | Medline11. Belser, JA, Rota, PA, Tumpey, TM. Ocular tropism of respiratory viruses. Microbiol Mol Biol Rev. 2013;77:144-156. doi:10.1128/MMBR.00058-12.
Google Scholar | Crossref | Medline12. Lan, J, Ge, J, Yu, J, et al. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature. 2020;581:215-220.
Google Scholar | Crossref | Medline13. Paraskevis, D, Kostaki, EG, Magiorkinis, G, Panayiotakopoulos, G, Sourvinos, G, Tsiodras, S. Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event. Infect Genet Evol. 2020;79:104212.
Google Scholar | Crossref | Medline14. Qi, F, Qian, S, Zhang, S, Zhang, Z. Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses. Biochem Biophys Res Commun. 2020;526:135-140.
Google Scholar | Crossref | Medline15. Hoffmann, M, Kleine-Weber, H, Schroeder, S, et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181:271-280.
Google Scholar | Crossref | Medline16. Su, C . Bioinformatics: A Practical Guide to the Analysis of Genes & Proteins. Baxevanis, AD, Ouellette, BFF, eds. 3rd ed. Oxford: Oxford University Press. (original work published 2004); 2006.
Google Scholar17. Bah, SY, Morang’a, CM, Kengne-Ouafo, JA, Amenga-Etego, L, Awandare, GA. Highlights on the application of genomics and bioinformatics in the fight against infectious diseases: challenges and opportunities in Africa. Front Genet. 2018;9:575.
Google Scholar | Crossref | Medline18. Ray, M, Sable, MN, Sarkar, S, Hallur, VK. Essential interpretations of bioinformatics in COVID-19 pandemic. Meta Gene. 2021;27:100844.
Google Scholar | Crossref | Medline19. Bayat, A. Science, medicine, and the future: bioinformatics. BMJ. 2002;324:1018.
Google Scholar | Crossref | Medline20. Thusberg, J, Vihinen, M. Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods. Hum Mutat. 2009;30:703-714.
Google Scholar | Crossref | Medline21. Li, L-P, Wang, Y-B, You, Z-H, Li, Y, An, J-Y. PCLPred: a bioinformatics method for predicting protein–protein interactions by combining relevance vector machine model with low-rank matrix approximation. Int J Mol Sci. 2018;19:1029.
Google Scholar | Crossref22. Yang, S, Fu, C, Lian, X, Dong, X, Zhang, Z. Understanding human-virus protein-protein interactions using a human protein complex-based analysis framework. mSystems. 2019;4:e00303-18. doi:10.1128/mSystems.00303-18.
Google Scholar | Crossref23. Gasteiger, E, Gattiker, A, Hoogland, C, Ivanyi, I, Appel, RD, Bairoch, A. ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003;31:3784-3788. doi:10.1093/nar/gkg563.
Google Scholar | Crossref | Medline | ISI24. Szklarczyk, D, Gable, AL, Lyon, D, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607-D613. doi:10.1093/nar/gky1131.
Google Scholar | Crossref25. Slenter, DN, Kutmon, M, Hanspers, K, et al. WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res.2018;46:D661-D667. doi:10.1093/nar/gkx1064.
Google Scholar | Crossref | Medline26. Ge, SX, Jung, D, Yao, R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics. 2020;36:2628-2629. doi:10.1093/bioinformatics/btz931.
Google Scholar | Crossref | Medline27. Consortium, GT. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45:580-585. doi:10.1038/ng.2653.
Google Scholar | Crossref | Medline28. Yang, S, Kim, CY, Hwang, S, et al. COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH). Nucleic Acids Res. 2017;45:D389-D396. doi:10.1093/nar/gkw868.
Google Scholar | Crossref29. Zhu, Q, Wong, AK, Krishnan, A, et al. Targeted exploration and analysis of large cross-platform human transcriptomic compendia. Nat Methods. 2015;12:211-214. doi:10.1038/nmeth.3249.
Google Scholar | Crossref | Medline | ISI30. Barrett, T, Beck, J, Benson, DA, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2015;43:D6-D17. doi:10.1093/nar/gku1130.
Google Scholar | Crossref | Medline31. Apweiler, R, Bairoch, A, Wu, CH, et al. UniProt: the Universal Protein knowledgebase. Nucleic Acids Res. 2004;32:D115-D119. doi:10.1093/nar/gkh131.
Google Scholar | Crossref32. Hunt, SE, McLaren, W, Gil, L, et al. Ensembl variation resources. Database. 2018;2018:bay119. doi:10.1093/database/bay119.
Google Scholar | Crossref | Medline33. Lek, M, Karczewski, KJ, Minikel, EV, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285-291. doi:10.1038/nature19057.
Google Scholar | Crossref | Medline | ISI34. Goodsell, DS, Zardecki, C, Di Costanzo, L, et al. RCSB Protein Data Bank: enabling biomedical research and drug discovery. Protein Sci. 2020;29:52-65.
Google Scholar | Crossref | Medline35. Wilson, S, Greer, B, Hooper, J, et al. The membrane-anchored serine protease, TMPRSS2, activates PAR-2 in prostate cancer cells. Biochemical J. 2005;388:967-972.
Google Scholar | Crossref | Medline36. Dahms, SO, Arciniega, M, Steinmetzer, T, Huber, R, Than, ME. Structure of the unliganded form of the proprotein convertase furin suggests activation by a substrate-induced mechanism. Proc Natl Acad Sci USA. 2016;113:11196-11201.
Google Scholar | Crossref | Medline37. Henrich, S, Cameron, A, Bourenkov, G. P., et al. The crystal structure of the proprotein processing proteinase furin explains its stringent specificity. Nat Struct Biol. 2003;10:520-526.
Google Scholar | Crossref | Medline38. Madden, TL, Schäffer, AA, Zhang, J, Zheng, Z, Miller, W, Lipman, DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Mol Biol Evol. 1997;25:3389-3402.
Google Scholar39. Kumar, S, Stecher, G, Tamura, K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870-1874.
Google Scholar | Crossref | Medline | ISI40. Zhao, WM, Song, SH, Chen, ML, et al. The 2019 novel coronavirus resource. Yi Chuan. 2020;42:212-221. doi:10.16288/j.yczz.20-030.
Google Scholar | Crossref | Medline41. Rice, P, Longden, L, Bleasby, A. EMBOSS: the European Molecular Biology Open Software suite. Trends Genet. 2000;16:276-277.
Google Scholar | Crossref | Medline | ISI42. Waterhouse, A, Bertoni, M, Bienert, S, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46:W296-W303. doi:10.1093/nar/gky427.
Google Scholar | Crossref | Medline43. Guex, N, Peitsch, MC, Schwede, T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: a historical perspective. Electrophoresis. 2009;30:S162-173.
Google Scholar | Crossref | Medline44. Xue, LC, Rodrigues, JP, Kastritis, PL, Bonvin, AM, Vangone, A. PRODIGY: a web server for predicting the binding affinity of protein-protein complexes. Bioinformatics. 2016;32:3676-3678. doi:10.1093/bioinformatics/btw514.
Google Scholar | Crossref | Medline45. Sali, A, Blundell, T. Comparative modelling by satisfaction of spatial restraints. J Mol Biol. 1994;234:779-815.
Google Scholar | Crossref46. Sheik, SS, Sundararajan, P, Hussain, ASZ, Sekar, K. Ramachandran Plot on the web. Bioinformatics. 2002;18:1548-1549.
Google Scholar | Crossref | Medline47. Dominguez, C, Boelens, R, Bonvin, AMJJ. HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J Am Chem Soc. 2003;125:1731-1737.
Google Scholar | Crossref | Medline48. Hoffmann, M, Kleine-Weber, H, Pohlmann, S. A multibasic cleavage site in the spike protein of SARS-CoV-2 is essential for infection of human lung cells. Mol Cell. 2020;78:779e5-7784. doi:10.1016/j.molcel.2020.04.022.
Google Scholar | Crossref | Medline49. Kim, H, Joe, A, Lee, M, et al. A genome-scale co-functional network of Xanthomonas genes can accurately reconstruct regulatory circuits controlled by two-component signaling systems. Mol Cells. 2019;42:166-174. doi:10.14348/molcells.2018.0403.
Google Scholar | Crossref | Medline50. Hoffmann, M, Kleine-Weber, H, Pöhlmann, S. A multibasic cleavage site in the spike protein of SARS-CoV-2 is essential for infection of human lung cells. Mol Cell. 2020;78:779e5-7784.
Google Scholar | Crossref | Medline51. Fadini, G, Morieri, M, Longato, E, Avogaro, A. Prevalence and impact of diabetes among people infected with SARS-CoV-2

Comments (0)

No login
gif