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PreprintCited by 21SARS-CoV-2 and COVID-19 ResearchRNA and protein synthesis mechanismsRNA Research and Splicing

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Mutagenesis and structural studies reveal the basis for the specific binding of SARS-CoV-2 SL3 RNA element with human TIA1 protein

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Zhang, Dong, Qiao, Lulu, Wang, Zhiye, Zhou, Ruhong·2022·Nature Communications
DOI 10.21203/rs.3.rs-2132183/v1PMC PMC10287707

Preprint — published as 10.1038/s41467-023-39410-8 · Paper page

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Abstract

Viral RNA-host protein interactions are indispensable during RNA virus transcription and replication. However, the detailed structural and dynamical features of the interactions between viral RNA and various host proteins remain largely elusive. Here, we characterized the binding interface for the SARS-CoV-2 stem-loop 3 (SL3) cis-acting element to human TIA1 protein with a combined theoretical and experimental approach including molecular modeling, free energy calculations, and electrophoretic mobility shift assays (EMSA). As a highly structured and conserved cis-acting element, SARS-CoV-2 SL3 RNA element was found to have a high binding affinity (Kd ~ 780 nM) to human TIA1 protein, with its hairpin and 3’-terminal loops playing essential roles in a sequence-dependent manner. Our molecular dynamics simulations revealed that the aromatic stacking, specific hydrogen bonds, and hydrophobic interactions collectively direct the specific binding of SL3 RNA element to TIA1, in which notable conformation changes both in protein domain arrangement and RNA 3D structure adaptation were observed. Further evaluations of in silico mutagenesis predictions with electrophoretic assays validated our proposed 3D binding model and also revealed SL3 A68U variant has an enhanced binding affinity (~ 1.7-fold) to TIA1 protein than the wild type. Finally, we found that the human TIA1 protein could interact with conserved SL3 RNA elements within other betacoronavirus lineages as well. These findings open a new avenue to explore the viral RNA-host protein interactions for SARS-CoV-2 infection and provide a pioneering structural basis for novel RNA-targeting antiviral drug design.

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  1. Wu,F., Zhao,S., Yu,B., Chen,Y.M., Wang,W., Song,Z.G., Hu,Y., Tao,Z.W., Tian,J.H., Pei,Y.Y., et al. (2020). A new coronavirus associated with human respiratory disease in China. Nature, 579, 265–269. · DOI · Paper page
  2. Perlman, S. (2020). Another Decade, Another Coronavirus. N. Engl. J. Med., 382, 760–762. · DOI
  3. Li,Z. and Nagy,P.D. (2011) Diverse roles of host RNA-binding proteins in RNA virus replication. RNA Biol., 8, 305–315. · DOI
  4. Sola,I., Mateos-Gomez,P.A., Almazan,F., Zuñiga,S. and Enjuanes,L. (2011) RNA-RNA and RNA-protein interactions in coronavirus replication and transcription. RNA Biol., 8, 237–248. · DOI
  5. Nagy,P.D. and Pogany,J. (2012) The dependence of viral RNA replication on co-opted host factors. Nat. Rev. Microbiol., 10, 137–149. · DOI
  6. Flynn,R.A., Belk,J.A., Qi,Y., Yasumoto,Y., Wei,J., Alfajaro,M.M., Shi,Q., Mumbach,M.R., Limaye,A., DeWeirdt,P.C., et al. (2021) Discovery and functional interrogation of SARS-CoV-2 RNA-host protein interactions. Cell, 184, 2394–2411. · DOI
  7. Schmidt,N., Lareau,C.A., Keshishian,H., Ganskih,S., Schneider,C., Hennig,T., Melanson,R., Werner,S., Wei,Y., Zimmer,M., et al. (2021) The SARS-CoV-2 RNA-protein interactome in infected human cells. Nat. Microbiol., 6, 339–353. · DOI · Paper page
  8. Kamel,W., Noerenberg,M., Cerikan,B., Chen,H., Järvelin,A.I., Kammoun,M., Lee,J.Y., Shuai,N., Garcia-Moreno,M., Andrejeva,A., et al. (2021) Global analysis of protein-RNA interactions in SARS-CoV-2-infected cells reveals key regulators of infection. Mol. Cell, 81, 2851–2867. · DOI
  9. Baggen,J., Vanstreels,E., Jansen,S. and Daelemans,D. (2021) Cellular host factors for SARS-CoV-2 infection. Nat. Microbiol., 6, 1219–1232. · DOI
  10. Chen,S.C. and Olsthoorn,R.C.L. (2010) Group-specific structural features of the 5′-proximal sequences of coronavirus genomic RNAs. Virology, 401, 29–41. · DOI
  11. Yang,D. and Leibowitz,J.L. (2015) The structure and functions of coronavirus genomic 3’ and 5’ ends. Virus Res., 206, 120–133. · DOI
  12. Madhugiri,R., Fricke,M., Marz,M. and Ziebuhr,J. (2016) Coronavirus cis-acting RNA elements. Adv. Virus Res., 96, 127–163. · DOI
  13. Huston,N.C., Wan,H., Strine,M.S., Tavares,R.d.C.A., Wilen,C.B. and Pyle,A.M. (2021) Comprehensive in vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms. Mol. Cell, 81, 584–598. · DOI
  14. Sun,L., Li,P., Ju,X., Rao,J., Huang,W., Ren,L., Zhang,S., Xiong,T., Xu,K., Zhou,X., et al. (2021) In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs. Cell, 184, 1865–1883. · DOI
  15. Wacker,A., Weigand,J.E., Akabayov,S.R., Altincekic,N., Bains,J.K., Banijamali,E., Binas,O., Castillo-Martinez,J., Cetiner,E., Ceylan,B., et al. (2020) Secondary structure determination of conserved SARS-CoV-2 RNA elements by NMR spectroscopy. Nucleic Acids Res., 48, 12415–12435. · DOI
  16. Andrews,R.J., O’Leary,C.A., Tompkins,V.S., Peterson,J.M., Haniff,H.S., Williams,C., Disney,M.D. and Moss,W.N. (2021) A map of the SARS-CoV-2 RNA structurome. NAR Genom. Bioinform., 3, lqab043. · DOI
  17. Manfredonia,I., Nithin,C., Ponce-Salvatierra,A., Ghosh,P., Wirecki,T.K., Marinus,T., Ogando,N.S., Snijder,E.J., van Hemert,M.J., Bujnicki,J.M., et al. (2020) Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements. Nucleic Acids Res., 48, 12436–12452. · DOI
  18. Rangan,R., Zheludev,I.N., Hagey,R.J., Pham,E.A., Wayment-Steele,H.K., Glenn,J.S. and Das,R. (2020) RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look. RNA, 26, 937–959. · DOI
  19. Miao,Z., Tidu,A., Eriani,G. and Martin,F. (2021) Secondary structure of the SARS-CoV-2 5′-UTR. RNA Biol., 18, 1–10. · DOI · Paper page
  20. Beck,A.R., Medley,Q.G., O’Brien,S., Anderson,P. and Streuli,M. (1996) Structure, tissue distribution and genomic organization of the murine RRM-type RNA binding proteins TIA-1 and TIAR. Nucleic Acids Res., 24, 3829–3835. · DOI
  21. Sánchez-Jiménez,C. and Izquierdo,J.M. (2015) T-cell intracellular antigens in health and disease. Cell Cycle, 14, 2033–2043. · DOI
  22. Dember,L.M., Kim,N.D., Liu,K.Q. and Anderson,P. (1996) Individual RNA recognition motifs of TIA-1 and TIAR have different RNA binding specificities. J. Biol. Chem., 271, 2783–2788. · DOI
  23. Wang,I., Hennig,J., Jagtap,P.K., Sonntag,M., Valcarcel,J. and Sattler,M. (2014) Structure, dynamics and RNA binding of the multi-domain splicing factor TIA-1. Nucleic Acids Res., 42, 5949–5966. · DOI
  24. Waris,S., García-Mauriño,S.M., Sivakumaran,A., Beckham,S.A., Loughlin,F.E., Gorospe,M., Díaz-Moreno,I., Wilce,M.C.J. and Wilce,J.A. (2017) TIA-1 RRM23 binding and recognition of target oligonucleotides. Nucleic Acids Res., 45, 4944–4957. · DOI
  25. Li,W., Li,Y., Kedersha,N., Anderson,P., Emara,M., Swiderek,K.M., Moreno,G.T. and Brinton,M.A. (2002) Cell proteins TIA-1 and TIAR interact with the 3’ stem-loop of the West Nile virus complementary minus-strand RNA and facilitate virus replication. J. Virol., 76, 11989–12000. · DOI
  26. Emara,M.M., Liu,H., Davis,W.G. and Brinton,M.A. (2008) Mutation of mapped TIA-1/TIAR binding sites in the 3’ terminal stem-loop of West Nile virus minus-strand RNA in an infectious clone negatively affects genomic RNA amplification. J. Virol., 82, 10657–10670. · DOI
  27. Emara,M.M. and Brinton,M.A. (2007) Interaction of TIA-1/TIAR with West Nile and dengue virus products in infected cells interferes with stress granule formation and processing body assembly. Proc. Natl. Acad. Sci. U.S.A., 104, 9041–9046.
  28. Albornoz,A., Carletti,T., Corazza,G. and Marcello,A. (2014) The stress granule component TIA-1 binds tick-borne encephalitis virus RNA and is recruited to perinuclear sites of viral replication to inhibit viral translation. J. Virol., 88, 6611–6622. · DOI
  29. Zafferani,M., Haddad,C., Luo,L., Davila-Calderon,J., Chiu,L.Y., Mugisha,C.S., Monaghan,A.G., Kennedy,A.A., Yesselman,J.D., Gifford,R.J. et al. (2021) Amilorides inhibit SARS-CoV-2 replication in vitro by targeting RNA structures. Sci. Adv., 7, eabl6096. · DOI
  30. Park,S.J., Kim,Y.G. and Park,H.J. (2011) Identification of RNA pseudoknot-binding ligand that inhibits the – 1 ribosomal frameshifting of SARS-coronavirus by structure-based virtual screening. J. Am. Chem. Soc., 133, 10094–10100. · DOI
  31. Zhang,D., Chen,S.J. and Zhou,R. (2021) Modeling noncanonical RNA base pairs by a coarse-grained IsRNA2 model. J. Phys. Chem. B, 125, 11907–11915. · DOI
  32. Zhang,D., Li,J. and Chen,S.J. (2021) IsRNA1: de novo prediction and blind screening of RNA 3D structures. J. Chem. Theory Comput., 17, 1842–1857. · DOI
  33. Cao,S. and Chen,S.J. (2011) Physics-based de novo prediction of RNA 3D structures. J. Phys. Chem. B, 115, 4216–4226. · DOI
  34. Xu,X. and Chen,S.J. (2018) Hierarchical assembly of RNA three-dimensional structures based on loop templates. J. Phys. Chem. B, 122, 5327–5335. · DOI
  35. Páll,S., Zhmurov,A., Bauer,P., Abraham,M., Lundborg,M., Gray,A., Hess,B. and Lindahl,E. (2020) Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS. J. Chem. Phys., 153, 134110. · DOI
  36. Maier,J.A., Martinez,C., Kasavajhala,K., Wickstrom,L., Hauser,K.E. and Simmerling,C. (2015) ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. J. Chem. Theory Comput., 11, 8, 3696–3713. · DOI
  37. Jorgensen,W.L., Chandrasekhar,J., Madura,J.D., Impey,R.W. and Klein,M.L. (1983) Comparison of simple potential functions for simulating liquid water. J. Chem. Phys., 79, 926–935. · DOI
  38. Li,P., Song,L.F. and Merz,Jr.K.M. (2015) Systematic parameterization of monovalent ions employing the nonbonded model. J. Chem. Theory Comput., 11, 1645–1657. · DOI
  39. Hess,B., Bekker,H., Berendsen,H.J.C. and Fraaije,J.G.E.M. (1997) LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem., 18, 1463–1472. · DOI
  40. Bussi,G., Donadio,D. and Parrinello,M. (2007) Canonical sampling through velocity rescaling. J. Chem. Phys., 126, 014101. · DOI
  41. Daura,X., Gademann,K., Jaun,B., Seebach,D., van Gunsteren,W.F. and Mark,A.E. (1999) Peptide folding: When simulation meets experiment. Angew. Chem., Int. Ed., 38, 236–240. · DOI
  42. Humphrey,W., Dalke,A. and Schulten,K. (1996) VMD: Visual molecular dynamics. J. Mol. Graphics, 14, 33–38. · DOI · Paper page
  43. Pettersen,E.F., Goddard,T.D., Huang,C.C., Couch,G.S., Greenblatt,D.M., Meng,E.C. and Ferrin,T.E. (2004) UCSF Chimera–a visualization system for exploratory research and analysis. J. Comput. Chem., 25, 1605–1612. · DOI
  44. Oubridge,C., Ito,N., Evans,P.R., Teo,C.H. and Nagai,K. (1994) Crystal structure at 1.92 Å resolution of the RNA-binding domain of the U1A spliceosomal protein complexed with an RNA hairpin. Nature, 372, 432–438. · DOI
  45. Sali,A. and Blundell,T.L. (1993) Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol., 234, 779–815. · DOI · Paper page
  46. Zhou,R., Das,P. and Royyuru,A.K. (2008) Single mutation induced H3N2 hemagglutinin antibody neutralization: A free energy perturbation study. J. Phys. Chem. B, 112, 15813–15820. · DOI
  47. Das,P., Li,J., Royyuru,A.K. and Zhou,R. (2009) Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity. J. Comput. Chem., 30, 1654–1663. · DOI
  48. Xia,Z., Huynh,T., Kang,S.G. and Zhou,R. (2012) Free-energy simulations reveal that both hydrophobic and polar interactions are important for influenza hemagglutinin antibody binding. Biophys. J., 102, 1453–1461. · DOI
  49. Bennett,C.H. (1976) Efficient estimation of free energy differences from Monte Carlo data. J. Comput. Phys., 22, 245–268. · DOI
  50. Zhao,B., Shu,C., Gao,X., Sankaran,B., Du,F., Shelton,C.L., Herr,A.B., Ji,J.Y. and Li,P. (2016) Structural basis for concerted recruitment and activation of IRF-3 by innate immune adaptor proteins. Proc. Natl. Acad. Sci. U. S. A., 113, E3403-E3412.
  51. Wang,Z., Ma,Z., Castillo-Gonzalez,C., Sun,D., Li,Y., Yu,B., Zhao,B., Li,P. and Zhang,X. (2018) SWI2/SNF2 ATPase CHR2 remodels pri-miRNAs via Serrate to impede miRNA production. Nature, 557, 516–521. · DOI
  52. Lee,C.W., Li,L. and Giedroc,D.P. (2011) The solution structure of coronaviral stem-loop 2 (SL2) reveals a canonical CUYG tetraloop fold. FEBS Lett., 585, 1049–1053. · DOI
  53. Rangan,R., Watkins,A.M., Chacon,J., Kretsch,R., Kladwang,W., Zheludev,I.N., Townley,J., Rynge,M., Thain,G. and Das,R. (2021) De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures. Nucleic Acids Res., 49, 3092–3108. · DOI
  54. Bottaro,S., Bussi,G. and Lindorff-Larsen,K. (2021) Conformational ensembles of noncoding elements in the SARS-CoV–2 genome from molecular dynamics simulations. J. Am. Chem. Soc., 143, 8333–8343. · DOI
  55. Afroz,T., Cienikova,Z., Cléry,A. and Allain,F.H. (2015) One, Two, Three, Four! How multiple rrms read the genome sequence. Methods Enzymol., 558, 235–278. · DOI · Paper page
  56. Reuter,J.S. and Mathews,D.H. (2010) RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinformatics, 11, 129. · DOI
  57. Clery,A., Blatter,M. and Allain,F.H. (2008) RNA recognition motifs: boring? Not quite. Curr. Opin. Struct. Biol., 18, 290–298. · DOI
  58. Kuhn,M., Firth-Clark,S., Tosco,P., Mey,A.S.J.S, Mackey,M. and Michel,J. (2020) Assessment of binding affinity via alchemical free-energy calculations. J. Chem. Inf. Model., 60, 3120–3130. · DOI · Paper page
  59. Fu,H., Chen,H., Blazhynska,M., de Lacam,E.G.C., Szczepaniak,F., Pavlova,A., Shao,X., Gumbart,J.C., Dehez,F., Roux,B., et al. (2022) Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations. Nat. Protoc., 17, 1114–1141. · DOI
  60. Gapsys,V. and de Groot,B.L. (2017) Alchemical free energy calculations for nucleotide mutations in protein – DNA complexes. J. Chem. Theory Comput., 13, 6275–6289. · DOI
  61. Peiris,J.S., Lai,S.T., Poon,L.L., Guan,Y., Yam,L.Y., Lim,W., Nicholls,J., Yee,W.K., Yan,W.W., Cheung,M.T., et al.; SARS study group. (2003) Coronavirus as a possible cause of severe acute respiratory syndrome. Lancet, 361, 1319–1325. · DOI
  62. Zaki,A.M., van Boheemen,S., Bestebroer,T.M., Osterhaus,A.D. and Fouchier,R.A. (2012) Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. N. Engl. J. Med., 367, 1814–1820. · DOI
  63. van den Born,E., Posthuma,C.C., Gultyaev,A.P. and Snijder,E.J. (2005) Discontinuous subgenomic RNA synthesis in arteriviruses is guided by an RNA hairpin structure located in the genomic leader region. J. Virol., 79, 6312–6324. · DOI
  64. Moore,M.J. (2005) From birth to death: the complex lives of eukaryotic mRNAs. Science, 309, 1514–1518. · DOI
  65. Keene,J.D. (2007) RNA regulons: coordination of post-transcriptional events. Nat. Rev. Genet., 8, 533–543. · DOI · Paper page
  66. Baek,M., DiMaio,F., Anishchenko,I., Dauparas,J., Ovchinnikov,S., Lee,G.R., Wang,J., Cong,Q., Kinch,L.N., Schaeffer,R.D., et al. (2021) Accurate prediction of protein structures and interactions using a three-track neural network. Science, 373, 871–876. · DOI · Paper page
  67. Dawson,W.K. and Bujnicki,J.M. (2016) Computational modeling of RNA 3D structures and interactions. Curr. Opin. Struct. Biol., 37, 22–28. · DOI
  68. Sun,L.Z., Zhang,D. and Chen,S.J. (2017) Theory and modeling of RNA structure and interactions with metal ions and small molecules. Annu. Rev. Biophys., 46, 227–246. · DOI
  69. Miao,Z., Adamiak,R.W., Antczak,M., Boniecki,M.J., Bujnicki,J., Chen,S.J., Cheng,C.Y., Cheng,Y., Chou,F.C., Das,R., et al. (2020) RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers. RNA, 26, 982–995. · DOI
  70. Best,R.B., Zhu,X., Shim,J., Lopes,P.E.M., Mittal,J., Feig,M. and MacKerell Jr.,A.D. (2012) Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone phi, psi and side-chain chi1 and chi2 dihedral angles. J. Chem. Theory Comput., 8, 3257–3273. · DOI
  71. Denning,E.J., Priyakumar,U.D., Nilsson,L. and MacKerell,Jr.A.D. (2011) Impact of 2'-hydroxyl sampling on the conformational properties of RNA: Update of the CHARMM all-atom additive force field for RNA. J. Comput. Chem., 32, 1929–1943. · DOI
  72. Fang,S., Li,K., Shen,J., Liu,S., Liu,J., Yang,L., Hu,C.D. and Wan,J. (2021) GESS: A database of global evaluation of SARS-CoV-2/hCoV-19 sequences. Nucleic Acids Res., 49, D706-D714. · DOI
  73. Greaney,A.J., Loes,A.N., Crawford,K.H.D., Starr,T.N., Malone,K.D., Chu,H.Y. and Bloom,J.D. (2021) Comprehensive mapping of mutations in the SARS-CoV-2 receptor-binding domain that affect recognition by polyclonal human plasma antibodies. Cell Host Microbe, 29, 463–476.e6. · DOI · Paper page
  74. Sreeramulu,S., Richter,R., Berg,H., Martin,M.A.M., Ceylan,B., Matzel,T., Adam,J., Altincekic,N., Azzaoui,K., Bains,J.K., et al. (2021) Exploring the druggability of conserved RNA regulatory elements in the SARS-CoV-2 genome. Angew. Chem. Int. Ed., 60, 19191–19200. · DOI
  75. Zhang,S., Huang,W., Ren,L., Ju,X., Gong,M., Rao,J., Sun,L., Li,P., Ding,Q., Wang,J., et al. (2022) Comparison of viral RNA-host protein interactomes across pathogenic RNA viruses informs rapid antiviral drug discovery for SARS-CoV-2. Cell Res., 32, 9–23. · DOI
  76. Gumna,J., Antczak,M., Adamiak,W.A., Bujnicki,J.M., Chen,S.J., Ding,F., Ghosh,P., Li,J., Mukherjee,S., Nithin,C., et al. (2022) Computational pipeline for reference-free comparative analysis of RNA 3D structures applied to SARS-CoV-2 UTR models. Int. J. Mol. Sci., 23, 9630. · DOI

Metadata

Authors
Zhang, D., Qiao, L., Wang, Z., & Zhou, R.
Affiliations
  • Zhejiang University (CN)
  • State Key Laboratory of Plant Physiology and Biochemistry (CN)
  • First Affiliated Hospital Zhejiang University (CN)
Corresponding author
  • Wang, Zhiye
  • Zhou, Ruhong
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2022-10-24
Volume
14
Issue
1
Pages
3715-3715
ISSN
2041-1723 (ISSN-L)
DOI
10.21203/rs.3.rs-2132183/v1
PMC
PMC10287707
OpenAlex
W4381683186
Cited by
21
References
1
Citations by year
2026: 6 · 2025: 7 · 2024: 7 · 2023: 1
FWCI
4.35
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (SN-ZJU-SIAS-003, U1967217, 81930063, 12104396, 2021YFF1200404, 12104396, U1967217, 81930063, BR-ZJU-SIAS-001, ZJZX2020014, 226-2022-00192, 226-2022-00043)
  • Zhejiang University (SN-ZJU-SIAS009, SN-ZJU-SIAS-003)
  • Fundamental Research Funds for the Central Universities (226-2022-00043, 226-2022-00192)
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords
SARS-CoV-2, RNA-protein interactions, cis-acting RNA elements, binding interface, mutagenesis, antisense oligonucleotides, Betacoronavirus
MeSH terms
T-Cell Intracellular Antigen-1, COVID-19, SARS-CoV-2, Humans, Protein Binding, RNA, Viral, Mutagenesis

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