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SARS-CoV-2 Spike Glikoproteinlerinin Farklı Ülkelerde Karşılaştırmalı Biyoinformatik Analizleri

Year 2022, Volume: 6 Issue: 1, 68 - 74, 30.06.2022
https://doi.org/10.31594/commagene.1079045

Abstract

Bu çalışmada, biyoinformatik yaklaşımlar kullanılarak 23 farklı ülkeden SARS-CoV-2 spike (S) glikoproteininin 27 protein dizisi analiz edildi. Bu kapsamda saçak glikoproteinlerinin post-translasyonel modifikasyonları, sekans ve domain analizleri, filogenetik analizleri ve 3 boyutlu yapı analizleri gerçekleştirilmiştir. Ayrıca, insan ACE2 proteini ile SARS-CoV-2 saçak proteini S1 reseptör bağlama alanının (SS1) moleküler yerleştirme analizi yapıldı. Tüm SARS-CoV-2'lerin Spike_rec_bind (PF09408) ve Corona_S2 (PF01601) alan yapılarını içermesine rağmen, C-terminal S2 bölgesinin S1 bölgesinden daha çeşitli olduğu bulundu. Öngörülen N-glikosilasyon ve fosforilasyon bölgelerinin sırasıyla 17 ve 19, 136 ve 168 arasında olduğu belirlendi. Filogenetik analizde, SARS-CoV-2'lerin yarasa RaTG13 ve pangolin CoV-2 ile MERS CoV ve yarasa SARS CoV'den daha fazla benzerliğe sahip olduğu bulundu. İnsan SARS-CoV-2 ve yarasa RaTG13'ün tahmin edilen 3D protein yapıları, 0.76 ile 0.78 arasında değişen yüksek benzerlik gösterdi. Yerleştirme analizleri, Asp30, Lys31, His34, Glu35, Glu37, Asp38, Asn330 ve Gln325 rezidülerinin, SARS-CoV-2'nin N-terminal S1 alt birimi için ACE2 proteininde bağlayıcı kalıntılar olduğunu ortaya çıkardı. Bulgular özellikle ilaç geliştirme ve ilaç tasarımı çalışmaları için önemlidir.

References

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  • Lu, G., Wang, Q., & Gao, G.F. (2015). Bat-to-human: spike features determining ‘host jump’ of coronaviruses SARS-CoV, MERS-CoV, and beyond. Trends in Microbiology, 23(8), 468–478. https://doi.org/10.1016/j.tim.2015.06.003
  • Johnson, M., Zaretskaya, I., Raytselis, Y., Merezhuk, Y., McGinnis, S., & Madden, T.L. (2008). NCBI BLAST: a better web interface. Nucleic Acids Research, 36, 5–9. https://doi.org/10.1093/nar/gkn201
  • Ou, X., Liu, Y., Lei, X., Li, P., Mi, D., Ren, L., … & Qian, Z. (2020). Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV. Nature Communications, 11(1), 1620. https://doi.org/10.1038/s41467-020-15562-9
  • Masters, P.S., & Perlman, S. (2013). in Fields Virology Vol. 2 (eds Knipe, D. M. & Howley, P. M.) 825–858.
  • NCBI National Library of Medicine (US). (1988). National Center for Biotechnology Information. Retrieved from https://www.ncbi.nlm.nih.gov/
  • Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., & Ferrin, T.E. (2004). UCSF Chimera: A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
  • Ritchie, G., Harvey, D.J., Feldmann, F., Stroeher, U., Feldmann, H., Royle, L., … & Rudd, P.M. (2010). Identification of N-linked carbohydrates from severe acute respiratory syndrome (SARS) spike glycoprotein. Virology, 399(2), 257–269. https://doi.org/10.1016/j.virol.2009.12.020
  • Siddell, S.G., & Ziebuhr, J,S.E. (2005). Coronaviruses, Toroviruses, and Arteriviruses. In V. T. M. B.W.J. Mahy (Ed.), Topley and Wilson’s microbiology and microbial infections (pp. 823–856). Hodder Arnold, London.
  • van Zundert, G.C.P., Rodrigues, J.P.G.L.M., Trellet, M., Schmitz, C., Kastritis, P.L., Karaca, E., … & Bonvin, A.M.J.J. (2016). The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes. Journal of Molecular Biology, 428(4), 720–725. https://doi.org/10.1016/j.jmb.2015.09.014
  • Walls, A.C., Park, Y.-J., Tortorici, M.A., Wall, A., McGuire, A.T., & Veesler, D. (2020). Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell, 183(6), 1735. https://doi.org/10.1016/j.cell.2020.11.032
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Comparative Bioinformatics Analyses of SARS-CoV-2 Spike Glycoproteins in Different Countries

Year 2022, Volume: 6 Issue: 1, 68 - 74, 30.06.2022
https://doi.org/10.31594/commagene.1079045

Abstract

In this study, 27 protein sequences of SARS-CoV-2 spike (S) glycoprotein from 23 different countries were analyzed using bioinformatics approaches. In this context, post-translational modifications, sequence and domain analyses, phylogenetic analysis, and 3D structure analysis of the spike glycoprotein proteins were performed. Also, molecular docking analysis of the SARS-CoV-2 spike protein S1 receptor-binding domain (SS1) with human ACE2 protein was conducted. It was found that although all SARS-CoV-2s include Spike_rec_bind (PF09408) and Corona_S2 (PF01601) domain structures, the C-terminal S2 region was more diverse than the S1 region. The predicted N-glycosylation and phosphorylation sites were determined to be between 17 and 19 and 136 and 168, respectively. In phylogenetic analysis, SARS-CoV-2s were found to have more similarity with bat RaTG13 and pangolin CoV-2 than MERS CoV and bat SARS CoV. The predicted 3D protein structures of human SARS-CoV-2 and bat RaTG13 showed high similarity, ranging from 0.76 to 0.78. The docking analyses revealed that Asp30, Lys31, His34, Glu35, Glu37, Asp38, Asn330, and Gln325 residues were binding residues in the ACE2 protein for the N-terminal S1 subunit of SARS-CoV-2. The findings are particularly important for the studies of drug development and drug design.

References

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  • Blom, N., Sicheritz-Pontén, T., Gupta, R., Gammeltoft, S., & Brunak, S. (2004). Prediction of post-translational glycosylation and phosphorylation of proteins from the amino acid sequence. Proteomics, 4(6), 1633–1649. https://doi.org/10.1002/pmic.200300771
  • Cui, J., Li, F., & Shi, Z.-L. (2019). Origin and evolution of pathogenic coronaviruses. Nature Reviews Microbiology, 17(3), 181–192. https://doi.org/10.1038/s41579-018-0118-9
  • Drosten, C., Günther, S., Preiser, W., van der Werf, S., Brodt, H.-R., Becker, S., … & Doerr, H. W. (2003). Identification of a Novel Coronavirus in Patients with Severe Acute Respiratory Syndrome. New England Journal of Medicine, 348(20), 1967–1976. https://doi.org/10.1056/NEJMoa030747
  • Fehr, A.R., & Perlman, S. (2015). Coronaviruses: An Overview of Their Replication and Pathogenesis. Nature Public Health Emergency Collection, 1–23. https://doi.org/10.1007/978-1-4939-2438-7_1
  • Felsenstein, J. (1985). Confidence Limits on Phylogenies: An Approach Using the Bootstrap. Evolution, 39(4), 783. https://doi.org/10.2307/2408678
  • Fung, T.S., & Liu, D.X. (2018). Post-translational modifications of coronavirus proteins: roles and function. Future Virology, 13(6), 405–430. https://doi.org/10.2217/fvl-2018-0008
  • Hall, T.A. (1999). BioEdit: A User-Friendly Biological Sequence Alignment Editor and Analysis Program for Windows 95/98/NT. Nucleic Acids Symposium Series, 41, 95-98.
  • El-Gebali, S., Mistry, J., Bateman, A., Eddy, S.R., Luciani, A., Potter, S.C., ... & Finn, R.D. (2019). The Pfam protein families database in 2019. Nucleic Acids Research, 47, 427-432. https://doi.org/10.1093/nar/gky995
  • Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., & Bourne, P.E. (2000). The Protein Data Bank. Nucleic Acids Research, 28, 235-242. https://doi.org/10.1093/nar/28.1.235 and Retrieved From: https://www.rcsb.org
  • Kandeel, M., Ibrahim, A., Fayez, M., & Al-Nazawi, M. (2020). From SARS and MERS CoVs to SARS-CoV-2: Moving toward more biased codon usage in viral structural and nonstructural genes. Journal of Medical Virology, 92(6), 660–666. https://doi.org/10.1002/jmv.25754
  • Karaca, E., Melquiond, A.S.J., de Vries, S.J., Kastritis, P.L., & Bonvin, A.M.J.J. (2010). Building macromolecular assemblies by information-driven docking: introducing the HADDOCK multibody docking server. Molecular & Cellular Proteomics : MCP, 9(8), 1784–1794. https://doi.org/10.1074/mcp.M000051-MCP201
  • Kumar, S., Stecher, G., Li, M., Knyaz, C., & Tamura, K. (2018). MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular Biology and Evolution, 35(6), 1547–1549. https://doi.org/10.1093/molbev/msy096
  • Lan, J., Ge, J., Yu, J., Shan, S., Zhou, H., Fan, S., … & Wang, X. (2020). Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature, 581(7807), 215–220. https://doi.org/10.1038/s41586-020-2180-5
  • Laskowski, R.A., Jabłońska, J., Pravda, L., Vařeková, R.S., & Thornton, J.M. (2018). PDBsum: Structural summaries of PDB entries. Protein Science: A Publication of the Protein Society, 27(1), 129–134. https://doi.org/10.1002/pro.3289
  • Laskowski, R.A., & Swindells, M.B. (2011). LigPlot+: Multiple Ligand–Protein Interaction Diagrams for Drug Discovery. Journal of Chemical Information and Modeling, 51(10), 2778–2786. https://doi.org/10.1021/ci200227u
  • Lefkowitz, E.J., Dempsey, D.M., Hendrickson, R.C., Orton, R.J., Siddell, S.G., & Smith, D.B. (2018). Virus taxonomy: the database of the International Committee on Taxonomy of Viruses (ICTV). Nucleic Acids Research, 46, 708-717. https://doi.org/10.1093/nar/gkx932
  • Lovell, S.C., Davis, I.W., Arendall, W.B., de Bakker, P.I.W., Word, J.M., Prisant, M.G., … & Richardson, D.C. (2003). Structure validation by Cα geometry: ϕ,ψ and Cβ deviation. Proteins: Structure, Function, and Bioinformatics, 50(3), 437–450.
  • Lu, G., Wang, Q., & Gao, G.F. (2015). Bat-to-human: spike features determining ‘host jump’ of coronaviruses SARS-CoV, MERS-CoV, and beyond. Trends in Microbiology, 23(8), 468–478. https://doi.org/10.1016/j.tim.2015.06.003
  • Johnson, M., Zaretskaya, I., Raytselis, Y., Merezhuk, Y., McGinnis, S., & Madden, T.L. (2008). NCBI BLAST: a better web interface. Nucleic Acids Research, 36, 5–9. https://doi.org/10.1093/nar/gkn201
  • Ou, X., Liu, Y., Lei, X., Li, P., Mi, D., Ren, L., … & Qian, Z. (2020). Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV. Nature Communications, 11(1), 1620. https://doi.org/10.1038/s41467-020-15562-9
  • Masters, P.S., & Perlman, S. (2013). in Fields Virology Vol. 2 (eds Knipe, D. M. & Howley, P. M.) 825–858.
  • NCBI National Library of Medicine (US). (1988). National Center for Biotechnology Information. Retrieved from https://www.ncbi.nlm.nih.gov/
  • Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., & Ferrin, T.E. (2004). UCSF Chimera: A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
  • Ritchie, G., Harvey, D.J., Feldmann, F., Stroeher, U., Feldmann, H., Royle, L., … & Rudd, P.M. (2010). Identification of N-linked carbohydrates from severe acute respiratory syndrome (SARS) spike glycoprotein. Virology, 399(2), 257–269. https://doi.org/10.1016/j.virol.2009.12.020
  • Siddell, S.G., & Ziebuhr, J,S.E. (2005). Coronaviruses, Toroviruses, and Arteriviruses. In V. T. M. B.W.J. Mahy (Ed.), Topley and Wilson’s microbiology and microbial infections (pp. 823–856). Hodder Arnold, London.
  • van Zundert, G.C.P., Rodrigues, J.P.G.L.M., Trellet, M., Schmitz, C., Kastritis, P.L., Karaca, E., … & Bonvin, A.M.J.J. (2016). The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes. Journal of Molecular Biology, 428(4), 720–725. https://doi.org/10.1016/j.jmb.2015.09.014
  • Walls, A.C., Park, Y.-J., Tortorici, M.A., Wall, A., McGuire, A.T., & Veesler, D. (2020). Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell, 183(6), 1735. https://doi.org/10.1016/j.cell.2020.11.032
  • Xu, J., & Zhang, Y. (2010). How significant is a protein structure similarity with TM-score = 0.5? Bioinformatics, 26(7), 889–895. https://doi.org/10.1093/bioinformatics/btq066
  • Zaki, A.M., van Boheemen, S., Bestebroer, T.M., Osterhaus, A.D.M.E., & Fouchier, R.A.M. (2012). Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. The New England Journal of Medicine, 367(19), 1814–1820. https://doi.org/10.1056/NEJMoa1211721
  • Zhang, Y., & Skolnick, J. (2004). Scoring function for automated assessment of protein structure template quality. Proteins, 57(4), 702–710. https://doi.org/10.1002/prot.20264
  • Zhou, P., Yang, X.-L., Wang, X.-G., Hu, B., Zhang, L., Zhang, W., … & Shi, Z.-L. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579(7798), 270–273. https://doi.org/10.1038/s41586-020-2012-7
  • Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., … & Tan, W. (2020). A Novel Coronavirus from Patients with Pneumonia in China, 2019. New England Journal of Medicine, 382(8), 727–733. https://doi.org/10.1056/NEJMoa2001017
  • Wu, A., Peng, Y., Huang, B., Ding, X., Wang, X., Niu, P., … & Jiang, T. (2020). Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China. Cell Host & Microbe, 27(3), 325–328. https://doi.org/10.1016/j.chom.2020.02.001
  • Xue, L.C., Rodrigues, J.P., Kastritis, P.L., Bonvin, A.M., & Vangone, A. (2016). PRODIGY: a web server for predicting the binding affinity of protein-protein complexes. Bioinformatics (Oxford, England), 32(23), 3676–3678. https://doi.org/10.1093/bioinformatics/btw514
  • Kelley, L. A., Mezulis, S., Yates, C.M., Wass, M. N., & Sternberg, M.J.E. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. Nature Protocols, 10(6), 845–858. https://doi.org/10.1038/nprot.2015.053
  • Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123(3), 585–95.
There are 37 citations in total.

Details

Primary Language English
Subjects Structural Biology
Journal Section Research Articles
Authors

Barış Kurt 0000-0002-1406-0915

Publication Date June 30, 2022
Submission Date February 25, 2022
Acceptance Date May 1, 2022
Published in Issue Year 2022 Volume: 6 Issue: 1

Cite

APA Kurt, B. (2022). Comparative Bioinformatics Analyses of SARS-CoV-2 Spike Glycoproteins in Different Countries. Commagene Journal of Biology, 6(1), 68-74. https://doi.org/10.31594/commagene.1079045