Zhang N, Zuo Y, Jiang L, Peng Y, Huang X, Zuo L (2022) Epstein-Barr Virus and Neurological Diseases, vol. 8, no. January, pp. 1–13, https://doi.org/10.3389/fmolb.2021.816098

Frappier L (2021) Epstein-Barr virus: current questions and challenges. Tumour Virus Res 12:200218. https://doi.org/10.1016/j.tvr.2021.200218

Article  PubMed  PubMed Central  Google Scholar 

Kliszczewska E, Jarzyński A, Boguszewska A, Pasternak J (2017) Epstein-Barr virus – pathogenesis, latency and cancers. 11 2142–146. https://doi.org/10.26444/jpccr/81214

Chen J, Longnecker R (2018) Epithelial cell infection by Epstein – Barr virus CELLS INVOLVES MULTIPLE VIRAL ENVELOP, no. December pp. 674–683, 2019, https://doi.org/10.1093/femsre/fuz023

Fugl A, Andersen CL (2019) Epstein-Barr virus and its association with disease - a review of relevance to general practice. 3:1–8

Frappier L (2012) The Epstein-Barr Virus EBNA1 Protein, vol. 2012

Malki A (2018) Epstein – Barr Virus-Associated Malignancies: Roles of Viral Oncoproteins in Carcinogenesis, vol. 8, no. August, pp. 1–13, https://doi.org/10.3389/fonc.2018.00265

Rød BE et al (June, 2023) Humoral response to Epstein-Barr virus in patients with multiple sclerosis treated with B cell depletion therapy. Mult Scler Relat Disord 79. https://doi.org/10.1016/j.msard.2023.105037

Pender MP, Burrows SR (2014) Epstein – Barr virus and multiple sclerosis: potential opportunities for immunotherapy. No September. https://doi.org/10.1038/cti.2014.25

Article  Google Scholar 

Bjornevik K et al (2022) Longitudinal analysis reveals high prevalence of Epstein-Barr virus associated with multiple sclerosis, vol. 301, no. January, pp. 296–301

Thomas OG et al (2023) Cross-reactive EBNA1 immunity targets alpha-crystallin B and is associated with multiple sclerosis. Sci Adv 9(20):1–13. https://doi.org/10.1126/sciadv.adg3032

Article  CAS  Google Scholar 

Dana H et al (2017) Molecular mechanisms and Biological functions of siRNA. 13(2):48–57

Mahfuz AMUB et al (2022) Designing potential siRNA molecules for silencing the gene of the nucleocapsid protein of Nipah virus: a computational investigation. Infect Genet Evol 102:105310. https://doi.org/10.1016/j.meegid.2022.105310

Article  CAS  PubMed  Google Scholar 

Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11, vol. 38, no. 7, pp. 3022–3027, https://doi.org/10.1093/molbev/msab120

Hu B, Zhong L, Weng Y, Peng L, Huang Y (2020) Therapeutic siRNA: state of the art. No Febr. https://doi.org/10.1038/s41392-020-0207-x

Article  Google Scholar 

Ichihara M et al (2007) Thermodynamic instability of siRNA duplex is a prerequisite for dependable prediction of siRNA activities. 35(18). https://doi.org/10.1093/nar/gkm699

Ui-tei K, Naito Y, Takahashi F, Haraguchi T (2004) Guidelines for the selection of highly effective siRNA sequences for mammalian guidelines for the selection of highly effective siRNA sequences for mammalian and chick RNA interference. No June 2014. https://doi.org/10.1093/nar/gkh247

Article  Google Scholar 

Amarzguioui M, Prydz H (2004) An algorithm for selection of functional siRNA sequences. 316:1050–1058. https://doi.org/10.1016/j.bbrc.2004.02.157

Reynolds A et al (2004) Rational siRNA design for RNA interference. 22(3):326–330. https://doi.org/10.1038/nbt936

Oladipo EK et al (2022) Immunoinformatics design of multi-epitope peptide for the diagnosis of Schistosoma haematobium infection Immunoinformatics design of multi-epitope peptide for the diagnosis of. J Biomol Struct Dyn 0(0):1–8. https://doi.org/10.1080/07391102.2022.2111358

Article  CAS  Google Scholar 

Ding Y, Chan CY, Lawrence CE (2004) S fold web server for statistical folding and rational design of nucleic acids. 32:135–141. https://doi.org/10.1093/nar/gkh449

Rahman A, Das Gupta S, Rahman MA, Tamanna S (2021) An in-silico approach to design potential siRNAs against the ORF57 of Kaposi’s sarcoma-associated herpesvirus. Genomics Inf 19(4). https://doi.org/10.5808/gi.21057

Muckstein U, Tafer H, Hackermuller J, Bernhart SH, Stadler PF, Hofacker IL (2006) Thermodynamics of RNA–RNA binding. 22(10):1177–1182. https://doi.org/10.1093/bioinformatics/btl024

Gruber AR, Lorenz R, Bernhart SH, Neubo R (2008) The Vienna RNA Websuite. 36 no April 70–74. https://doi.org/10.1093/nar/gkn188

Sciabola S, Cao Q, Orozco M, Faustino I, Stanton RV (2013) Improved nucleic acid descriptors for siRNA efficacy prediction. 41(3):1383–1394. https://doi.org/10.1093/nar/gks1191

Pan W, Chen C, Chu Y (2011) siPRED: Predicting siRNA efficacy using various characteristic methods. 6(11):1–7. https://doi.org/10.1371/journal.pone.0027602

Antczak M et al (2016) New functionality of RNAComposer: an application to shape the axis of miR160 precursor structure. 63(4):737–744

Markham NR, Zuker M (2005) DINAMelt web server for nucleic acid melting prediction. 33:577–581. https://doi.org/10.1093/nar/gki591

Qi F, Frishman D (2017) Melting temperature highlights functionally important RNA structure and sequence elements in yeast mRNA coding regions. 45(10):6109–6118. https://doi.org/10.1093/nar/gkx161

Muppirala UK, Honavar VG, Dobbs D (2011) Predicting RNA-Protein interactions using only sequence information. BMC Bioinformatics 12(1). https://doi.org/10.1186/1471-2105-12-489

Schirle NT, Kinberger GA, Murray HF, Lima WF, Prakash TP, Macrae IJ (2016) Structural analysis of human Argonaute-2 bound to a modified siRNA guide. https://doi.org/10.1021/jacs.6b04454

Pratt AJ, Macrae IJ (2010) The RNA-induced silencing complex: a versatile gene-silencing machine. 284:17897–17901. https://doi.org/10.1074/jbc.R900012200

Adasme MF et al (2021) PLIP., : expanding the scope of the protein – ligand interaction profiler to DNA and RNA, vol. 49, no. May, pp. 530–534, 2021

Bar-or A et al (2020) Epstein – Barr Virus in multiple sclerosis: theory and emerging immunotherapies. Trends Mol Med 26(3):296–310. https://doi.org/10.1016/j.molmed.2019.11.003

Article  CAS  PubMed  Google Scholar 

Soldan SS, Lieberman PM (2023) Epstein–Barr virus and multiple sclerosis. Nat Rev Microbiol 21(1):51–64. https://doi.org/10.1038/s41579-022-00770-5

Article  CAS  PubMed  Google Scholar 

Goldacre MJ, Wotton CJ, Seagroatt V, Yeates D (2004) Multiple sclerosis after infectious Mononucleosis: record linkage study. J Epidemiol Community Health 58(12):1032–1035. https://doi.org/10.1136/jech.2003.018366

Article  PubMed  PubMed Central  Google Scholar 

Pender MP, Burrows SR (2014) Epstein–Barr virus and multiple sclerosis: potential opportunities for immunotherapy. Clin Transl Immunol 3(10). https://doi.org/10.1038/cti.2014.25

Schönrich G, Abdelaziz MO, Raftery MJ (2022) Epstein-Barr virus, interleukin-10 and multiple sclerosis: A ménage à trois, Front. Immunol, vol. 13, no. October, pp. 1–9, https://doi.org/10.3389/fimmu.2022.1028972

Abrahamyan S et al (2020) Complete Epstein-Barr virus seropositivity in a large cohort of patients with early multiple sclerosis. J Neurol Neurosurg Psychiatry 91(7):681–686. https://doi.org/10.1136/jnnp-2020-322941

Article  PubMed  Google Scholar 

Tengvall K et al (2019) Molecular mimicry between Anoctamin 2 and Epstein-Barr virus nuclear antigen 1 associates with multiple sclerosis risk, Proc. Natl. Acad. Sci. U. S. A., vol. 116, no. 34, pp. 16955–16960, https://doi.org/10.1073/pnas.1902623116

Hauser SL, Cree BAC (2020) Treatment of multiple sclerosis: a review. Am J Med 133(12):1380–1390. https://doi.org/10.1016/j.amjmed.2020.05.049

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ziemssen T (2011) Symptom management in patients with multiple sclerosis, J. Neurol. Sci, vol. 311, no. SUPPL. 1, pp. S48–S52, https://doi.org/10.1016/S0022-510X(11)70009-0

Lam JKW, Chow MYT, Zhang Y, Leung SWS (2015) siRNA Versus miRNA as Therapeutics for Gene Silencing, no. September, pp. 1–20, https://doi.org/10.1038/mtna.2015.23

Sarkar B, Ullah A, Araf Y, Shahedur M (2020) Informatics in Medicine Unlocked Engineering a novel subunit vaccine against SARS-CoV-2 by exploring immunoinformatics approach. Inf Med Unlocked 21:100478. no. November10.1016/j.imu.2020.100478

Article  Google Scholar 

Bera MN, Riera A, Lewenstein M, Winter A (2017) Generalized laws of thermodynamics in the presence of correlations. Nat Commun 8–13. https://doi.org/10.1038/s41467-017-02370-x

Gredell JA, Berger AK, Walton SP (2009) Impact of target mRNA structure on siRNA silencing efficiency: a large-scale study. 100(4):744–755. https://doi.org/10.1002/bit.21798.Impact

Kurreck J (2006) siRNA efficiency: structure or sequence - that is the question. J Biomed Biotechnol 2006:1–7. https://doi.org/10.1155/JBB/2006/83757

Article  CAS  Google Scholar 

Pantsar T, Poso A (2018) Binding affinity via docking: Fact and fiction, Molecules, vol. 23, no. 8, p. 1DUMMY, https://doi.org/10.3390/molecules23081899

Wang J, Pan X, Liang X (2016) Assessment for Melting Temperature Measurement of Nucleic Acid by HRM. J Anal Methods Chem 2016. https://doi.org/10.1155/2016/5318935

Abdeen TO et al (2023) Journal of Molecular Graphics and Modelling structure-based computational design of novel covalent binders for the treatment of sickle cell disease. J Mol Graph Model 124:108549. https://doi.org/10.1016/j.jmgm.2023.108549

Article  CAS  Google Scholar 

Oladipo EK et al (2023) Proteome based analysis of circulating SARS – CoV – 2 variants: approach to a universal vaccine candidate. Genes Genomics no 012345678910.1007/s13258-023-01426-1

Ayyagari VS (2022) Design of siRNA molecules for silencing of membrane glycoprotein, nucleocapsid phosphoprotein, and surface glycoprotein genes of SARS-CoV2. J Genet Eng Biotechnol 20(1). https://doi.org/10.1186/s43141-022-00346-z

Santhekadur PK, Kumar DP (2020) RISC assembly and post-transcriptional gene regulation in Hepatocellular Carcinoma. Genes Dis 7(2):199–204. https://doi.org/10.1016/j.gendis.2019.09.009

Article  CAS  PubMed  Google Scholar