Design of Potential RNAi (miRNA and siRNA) Molecules for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Gene Silencing by Computational Method

Interdisciplinary Sciences – Computational Life Sciences

Volumn 7, Issue 3, 2015, Pages 257-265

  Nur, Suza Mohammad ^a   Hasan, Md Anayet ^a   Amin, Mohammad Al ^a   Hossain, Mehjabeen ^a   Sharmin, Tahmina ^b  

^a UNIVERSITY OF CHITTAGONG   (Bangladesh)

^b MAWLANA BHASHANI SCIENCE AND TECHNOLOGY UNIVERSITY   (Bangladesh)

Author keywords

Antiviral; Computational method; Gene silencing; MERS CoV; RNAi

Indexed keywords

MICRORNA; SMALL INTERFERING RNA;

ALGORITHM; BIOLOGY; CONFORMATION; DNA BASE COMPOSITION; GENE SILENCING; GENETICS; METABOLISM; MIDDLE EAST RESPIRATORY SYNDROME CORONAVIRUS; NUCLEOTIDE SEQUENCE; PROCEDURES; THERMODYNAMICS;

ALGORITHMS; BASE COMPOSITION; BASE SEQUENCE; COMPUTATIONAL BIOLOGY; GENE SILENCING; MICRORNAS; MIDDLE EAST RESPIRATORY SYNDROME CORONAVIRUS; NUCLEIC ACID CONFORMATION; RNA, SMALL INTERFERING; THERMODYNAMICS;

EID: 84942319853     PISSN: 19132751     EISSN: 18671462     Source Type: Journal    
DOI: 10.1007/s12539-015-0266-9     Document Type: Article

References (39)

1. Orbalenya AE, Enjuanes L, Ziebuhr J, Snijder EJ (2006) Nidovirales: evolving the largest RNA virus genome. Virus Res 117:17–37
2. Wertheim JO, Chu DK, Peiris JS, Kosakovsky Pond SL, Poon LL (2013) A case for the ancient origin of coronaviruses. J Virol 87:7039–7045
3. De Groot RJ, Bake SC, Baric RS, Brown CS, Drosten C, Enjuanes L (2013) Middle East respiratory syndrome coronavirus (MERS-CoV): announcement of the Coronavirus Study Group. J Virol 87:7790–7792
4. Memish ZA, Zumla Al, Assiri A (2013) Middle East respiratory syndrome coronavirus infections in health care workers. N Engl J Med 369:884–886
5. Zaki AM, Van Boheemen S, Bestebroer TM, Osterhaus AD, Fouchier RA (2012) Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. N Engl J Med 367:1814–1820
6. Hui DS, Alimuddin Z (2014) Advancing priority research on the Middle East respiratory syndrome coronavirus. J Infect Dis 209:173–176
7. Guery B, Poissy J, Mansouf L, Sejourne C, Ettahar N, Lemaire X (2013) Clinical features and viral diagnosis of two cases of infection with Middle East respiratory syndrome coronavirus: a report of nosocomial transmission. Lancet 38:2265–2272
8. Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D. (2013) Hospital outbreak of Middle East respiratory syndrome coronavirus. N Engl J Med 369:407–416
9. Annan A, Baldwin HJ, Corman VM, Klose SM, Owusu M, Nkrumah EE (2013) Human betacoronavirus 2c EMC/2012-related viruses in bats, Ghana and Europe. Emerg Infect Dis 19:456–459
10. Eckerle I, Corman VM, Müller MA, Lenk M, Ulrich RG, Drosten C (2014) Replicative capacity of MERS coronavirus in livestock cell lines. Emerg Infect Dis 20:276–279
11. Müller MA, Raj VS, Muth D, Meyer B, Kallies S, Smits SL (2012) Human coronavirus EMC does not require the SARS-coronavirus receptor and maintains broad replicative capability in mammalian cell lines. MBio 3:515-12
12. Eric JZ, Alexander ES, Gorbalenya E (2000) Virus-encoded proteinases and proteolytic processing in the Nidovirales. J Gen Virol 81:853–879
13. Van Bohemeen S, De Graaf M, Lauber C, Bestebroer TM, Raj VS, Zaki AM (2012) Genomic characterization of a newly discovered coronavirus associated with acute respiratory distress syndrome in humans. MBio 3:e00473-12
14. Pasternak AO, Spaan WJ, Snijder EJ (2006) Nidovirus transcription: how to make sense…? J Gen Virol 87:1403–1421
15. Sawicki SG, Sawicki DL, Siddell SG (2007) A contemporary view of coronavirus transcription. J Virol 81:20–29
16. Sola I, Mateos-Gomez PA, Almazan F, Zu niga S, Enjuanes L (2011) RNA–RNA and RNA–protein interactions in coronavirus replication and transcription. RNA Biol 8:237–248
17. Taxman DJ, Livingstone LR, Zhang J, Conti BJ, Iocca HA, Williams KL, Lich JD, Ting JP, Reed W (2006) Criteria for effective design, construction, and gene knockdown by shRNA vectors. BMC Biotechnol 24:6–7
18. Ui-Tei K, Naito Y, Nishi K, Juni A, Saigo K (2008) Thermodynamic stability and Watson–Crick base pairing in the seed duplex are major determinants of the efficiency of the siRNA-based off-target effect. Nucleic Acids Res 36:7100–7109
19. Jackson AL, Linsley PS (2010) Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application. Nat Rev Drug Discov 9:57–67
20. Chan CY, Carmack CS, Long DD, Maliyekkel A, Shao Y, Roninson IB, Ding Y (2009) A structural interpretation of the effect of GC-content on efficiency of RNA interference. BMC Bioinform 10(Suppl):1–S33
21. Filipowicz W, Bhattacharyya SN, Sonenberg N (2008) Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet 9:102–114
22. Naito Y, Yoshimura J, Morishita S, Ui-Tei K (2009) siDirect 2.0: updated software for designing functional siRNA with reduced seed-dependent off-target effect. BMC Bioinform 10:392
23. Ahmed F, Ansari HR, Raghava GPS (2009) Prediction of guide strand of microRNAs from its sequence and secondary structure. BMC Bioinform 10:105
24. Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31:3406–3415
25. Bernhart SH, Tafer H, Mückstein U, Flamm C, Stadler PF, Hofacker IL (2006) Partition function and base pairing probabilities of RNA heterodimers. Algorithms Mol Biol 16:1–3
26. Rehmsmeier M, Steffen P, Höchsmann M, Giegerich R (2006) Fast and effective prediction of microRNA/target duplexes. RNA 10:1507–1517
27. Markham NR, Zuker M (2005) DINAMelt web server for nucleic acid melting prediction. Nucleic Acids Res 33:577–581
28. Bret SE, Harris HS, Bowers SC, Rossi JJ (2005) siRNA target site secondary structure predictions using local stable substructures. Nucleic Acid Res 33:e30
29. Liu Y, Chang Y, Zhang C, Wei Q, Chen J, Chen H, Xu D (2013) Influence of mRNA features on siRNA interference efficacy. J Bioinform Comput Biol 11:1341004
30. Hajiaghayi M, Condon A, Hoos HH (2012) Analysis of energy-based algorithms for RNA secondary structure prediction. BMC Bioinform 13:22
31. Ding Y, han CY, Lawrence CE (2005) RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble. RNA 11:1157–1166
32. Mathews DH (2005) Predicting a set of minimal free energy RNA secondary structures common to two sequences. Bioinformatics 21:2246–2253
33. Muckstein U, Tafer H, Hackermuller J, Bernhart SB, Stadler F, Hofacker IL (2006) Thermodynamics of RNA–RNA binding. Bioinformatics 22:1177–1182
34. Bohula EA, Salisbury AJ, Sohail M, Playford MP, Riedemann J, Southern EM, Macaulay VM (2003) The efficacy of small interfering RNAs targeted to the type 1 insulin-like growth factor receptor (IGF1R) is influenced by secondary structure in the IGF1R transcript. J Biol Chem 278:15991–15997
35. Nur SM, Amin MA, Alam R, Hasan MA, Hossain MA, Mannan A (2013) An In silico approach to design potential siRNA molecules for ICP22 (US1) gene silencing of different strains of human herpes simplex 1. J Young Pharm 5:46–49
36. Vickers TA, Wyatt JR, Freier SM (2000) Effects of RNA secondary structure on cellular antisense activity. Nucleic Acids Res 28:1340–1347
37. Bryan K, Terrile M, Bray IM, Domingo-Fernandéz R, Watters KM, Koster J, Versteeg R, Stallings RL (2014) Discovery and visualization of miRNA–mRNA functional modules within integrated data using bicluster analysis. Nucleic Acids Res 42:e17
38. Stahlhut C, Slack FJ (2013) MicroRNAs and the cancer phenotype: profiling, signatures and clinical implications. Genome Med 5:111
39. Harada M, Luo X, Murohara T, Yang B, Dobrev D, Nattel S (2014) MicroRNA regulation and cardiac calcium signaling: role in cardiac disease and therapeutic potential. Circ Res 114:689–705