Prediction of promiscuous epitopes in the e6 protein of three high risk human papilloma viruses: A computational approach

Asian Pacific Journal of Cancer Prevention

Volumn 14, Issue 7, 2013, Pages 4167-4175

  Nirmala, Subramanian ^a   Sudandiradoss, Chinnappan ^a  

^a VIT UNIVERSITY   (India)

Author keywords

Computational; E6 protein; Epitope; High risk HPVs; Peptide vaccine

Indexed keywords

DNA BINDING PROTEIN; E6 PROTEIN, HUMAN PAPILLOMAVIRUS TYPE 16; E6 PROTEIN, HUMAN PAPILLOMAVIRUS TYPE 18; EPITOPE; HLA ANTIGEN; ONCOPROTEIN; REPRESSOR PROTEIN;

AMINO ACID SEQUENCE; ARTICLE; BIOLOGY; FEMALE; HUMAN; IMMUNOLOGY; MOLECULAR GENETICS; PAPILLOMA VIRUS; SEQUENCE HOMOLOGY;

AMINO ACID SEQUENCE; COMPUTATIONAL BIOLOGY; DNA-BINDING PROTEINS; EPITOPES; FEMALE; HLA ANTIGENS; HUMANS; MOLECULAR SEQUENCE DATA; ONCOGENE PROTEINS, VIRAL; PAPILLOMAVIRIDAE; REPRESSOR PROTEINS; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 84885454653     PISSN: 15137368     EISSN: 2476762X     Source Type: Journal    
DOI: 10.7314/APJCP.2013.14.7.4167     Document Type: Article

References (73)

1. Ackerman AL, Cresswell P (2004). Cellular mechanisms governing cross-presentation of exogenous antigens. Nature Immunology, 5, 678-84.
2. Aidan M, Ulrich K, Charles, et al (2009). T-cell epitope prediction: rescaling can mask biological variation between MHC molecules. PLoS Comput Biol, 5, 1000327.
3. Agarwal SM, Raghav D, Singh H, et al (2011). CCDB: a curated database of genes involved in cervix cancer. Nucleic Acids Res, 39, 975-9.
4. Agnieszka K, Grabowska, Riemer AB (2012). The invisible enemy-how human papillomaviruses avoid recognition and clearance by the host immune system. Open Virol J, 6, 249-56.
5. Alessia M, Marco T, Nello C (2009). Support vector machines. wiley interdisciplinary reviews: computation stat. Computational Statistics, 1, 283-9.
6. Altschul S, Madden T, Schaffer A, et al (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucl Acids Res, 25, 3389-402.
7. Androphyl EJ, Hubbert NL, Schiller JT, et al (1987). Identification of the HPV-16 E6 protein from transformed mouse cells and human cervical carcinoma cell lines. EMBO J, 6, 989-92.
8. Bernard HU, Burk RD, Chen Z, et al (2010). Classification of Papillomaviruses (PVs) based on 189 PV types and proposal of taxonomic amendments. Virology, 401, 70-9.
9. Bian H, Olson JFR, Hammer J (2003). The use of bioinformatics for identifying class II-restricted T-cell epitopes. Methods, 29, 299-309.
10. Boccardo E, Lepique AP, Luisa L (2010). The role of inflammation in HPV carcinogenesis. Carcin, 31, 1905-12.
11. Brusic V, Bajic VB, Petrovsky N (2004). Computational methods for prediction of T-cell epitopes-a framework for modeling, testing, and applications. Method, 34, 436-43.
12. Chandra S, Singh TR (2012). Linear B cell epitope prediction for epitope vaccine design against meningococcal disease and their computational validations through physicochemical properties. Netw Model Anal Health Inform Bioinforma, 1, 153-9.
13. Cole ST, Danos O (1987). Nucleotide sequence and comparative analysis of the human papillomavirus type 18 genome. Phylogeny of papillomavirus and repeated structure of the E6 and E7 gene products. J Mol Bio, 193, 599-608.
14. De Groot A S (2004). Immunome derived vaccine. Expert Opin Biol Ther, 4, 767-72.
15. Delius H, Hofmann B (1994). Primer-directed sequencing of human papillomavirus types. Curr Top Microbial Immunol, 186, 13-31.
16. De Sanjose S, Quint WGV, Alemany L, et al (2010). Human papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study. Lancet Oncol, 11, 1048-56.
17. Dimitrov I, Garnev P, Flower DR (2010). EpiTop-a proteochemometric tool for MHC class II binding prediction. Bioinformatics, 26, 2066-8.
18. Doytchinova IA, Guan P, Flower DR (2006). EpiJen: a server for multistep T cell epitope prediction. BMC Bioinformatics, 7, 131.
19. Engelhard VH (1994). How cells process antigens. Sci Am, 271, 54-61.
20. Fakhry C, Gillison ML (2006). Clinical implications of human papillomavirus in head and neck cancers. J Clin Oncol, 24, 2606-11.
21. Flower DR, Phadwal K, Macdonald IK, et al (2010). T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges. Immunome Res, 6, 2-4.
22. Frazer IH (2004). Prevention of cervical cancer through papillomavirus vaccination. Nature Rev Immun, 4, 46-54.
23. Gallagher KME, Man S (2007). Identification of HLA-DR1-and HLA-DR15-restricted human papillomavirus type 16 (HPV16) and HPV18 E6 epitopes recognized by CD4+ T cells from healthy young women. J General Virology, 88, 1470-8.
24. Gnanamony M, Peedicayil A, Abraham P (2007). An overview of Human Papillomavirus and current vaccine strategies. Indian J Med Microbiol, 25, 10-17.
25. Govan VA (2008). A novel vaccine for cervical cancer: quadrivalent human papillomavirus (types 6, 11, 16 and 18) recombinant vaccine (Gardasil). Ther Clin Risk Manage, 4, 65-70.
26. Hakenberg J, Nussbaum A, Schild H, et al (2003). MAPPP-MHC-I antigenic peptide processing prediction. Appl Bioinformatics, 2, 155-8.
27. Hellberg S, Sjostrom M, Skagerberg B, et al (1987). Peptide quantitative structure-activity relationships, a multivariate approach. J Med Chem, 30, 1126-35.
28. Holzhutter HG, Frommel C, Kloetzel PM (1999). A theoretical approach towards the identification of cleavage-determining amino acid motifs of the 20 S proteasome. J Mol Bio, 286, 1251-65.
29. Iurescia S, Fioretti D, Fazio VM, et al (2012). Epitope-driven DNA vaccine design employing immunoinformatics against B-cell lymphoma: a biotech's challenge. Biotechnol Adv, 30, 372-83.
30. Jacob AG, Hansen NC, Vinther J, et al. (2003). A promoter within the E6 ORF of human papillomavirus type 16 contributes to the expression of the E7 oncoprotein from a monocistronic mRNA. J Gen Virol, 84, 3429-41.
31. Jones DT (1999). Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol, 292, 195-202.
32. Kavitha KV, Saritha R, Vinod Chandra SS (2013). Computational methods in linear b-cell epitope prediction. Int J Comput Appl, 63, 28-32.
33. Khan HA, Arif IA, Bahkali AH, et al (2008). Bayesian, maximum parsimony and UPGMA models for inferring the phylogenies of antelopes using mitochondrial markers. Evol Bioinform Online, 4, 263-70.
34. Koichiro T, Joel D, Masatoshi N, et al (2007). MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol, 24, 1596-9.
35. Larkin MA, Blackshields G, Brown NR et al (2007). Clustal w and clustal X version 2.0. Bioinformatics, 23, 2947-48.
36. Lapinsh M, Prusis P, Gutcaits A, et al (2001). Development of proteochemometrics: A novel technology of use for analysis of drug-receptor interactions. Biochim Biophys Acta, 1525, 180-90.
37. Lin SY, Cheng CW, Su ECY (2013). Prediction of B-cell epitopes using evolutionary information and propensity scales. BMC Bioinformatics, 14, 2-10.
38. Longworth MS, Laimins LA (2004). Pathogenesis of human papillomaviruses in differentiating epithelia. Microbiol Mol Biol R, 68, 362-72.
39. Lundegaard C, Lamberth K, Harndah M, et al (2008). NetMHC-3.0: Accurate web accessible predictions of human, mouse, and monkey MHC class i affinities for peptides of length 8-11. Nucleic Acids Res, 36, 509-12.
40. Ma B, Xu Y, Hung CF, et al (2010). HPV and Therapeutic Vaccines: Where are we in 2010? Curr Cancer Ther Rev, 6, 81-103.
41. Ma B, Roden R Wu TC (2010). Current status of HPV vaccines. J Formos Med Assoc, 109, 481-3.
42. Mark HE, Suzanne L, Lydia GC (2009). Genetic variants in TAP are associated with high-grade cervical neoplasia. Clin Cancer Res, 15, 1019-23.
43. Morrow MP, Yan J, Sardesai NY (2013). Human papillomavirus therapeutic vaccines: targeting viral antigens as immunotherapy for precancerous disease and cancer. Expert Rev Vaccines, 12, 271-83.
44. Munger K, Howley PM (2002). Human papillomavirus immortalization and transformation functions. Virus Res, 89, 213-28.
45. Nakagawa M, Kim KH, Moscicki AB (2004). Different methods of identifying new antigenic epitopes of human papillomavirus type 16 E6 and E7 Proteins. Clin Diagn Lab Immun, 11, 889-96.
46. Nakagawa M, Kim KH, Gillam TM, et al (2007). HLA class I binding promiscuity of the CD8 T-Cell epitopes of human papillomavirus type 16 E6 protein. J Virol, 81, 1412-23.
47. Nielsen M, Lundegaard C, Woming P, et al (2003). Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci, 12, 1007-17.
48. Nielsen M, Lundegaard C, Woming P, et al (2004). Improved prediction of MHC class I and II epitopes using a novel Gibbs sampling approach. Bioinformatics, 20, 1388-97.
49. Oyarzun P Ellis JJ, Boden M, et al (2013). PREDIVAC: CD4+ T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity. BMC Bioinformatics, 14, 52.
50. Patronov A, Doytchinova I (2013). T-cell epitope vaccine design by immunoinformatics. Open Biol, 3, 120139.
51. Peters B, Sidney J, Bourne P et al (2005). The design and implementation of the immune epitope database and analysis resource. Immunogenetics, 57, 326-36.
52. Pingping S, Wenhan C, Yanxin H, et al (2011). Epitope prediction based on random peptide library screening: benchmark dataset and prediction tools evaluation. Molecules, 16, 4971-94.
53. Rudolf MP, Man S, Melief CJM, et al (2001). Human T-Cell responses to HLA-A-restricted high binding affinity peptides of human papillomavirus type 18 proteins E6 and E7. Clin Cancer Res, 7, 788-95.
54. Saha S, Raghava GPS (2006). Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins, 65, 40-8.
55. Seedorf K, Krammer G, Durst M, et al (1985). Human papillomavirus type 16 DNA sequence. Virology, 145, 181-5.
56. Sette A, Sidney J, Oseroff C, et al (1993). HLA DR4w4-binding motifs illustrate the biochemical basis of degeneracy and specificity in peptide-DR interactions. J Immunol, 151, 3163-70.
57. Shehzadi A, Rehman SU, Idrees M, (2011). Promiscuous prediction and conservancy analysis of CTL binding epitopes of HCV 3a viral proteome from Punjab Pakistan: an In-silico approach. Virol J, 8, 55.
58. Smith KL, Tristram A, Gallagher KM, et al (2004). Epitope specificity and longevity of a vaccine-induced human T cell response against HPV18. Int Immunol, 17, 167-76.
59. Soliman PT, Slomovitz BM, Wolf JK (2004). Mechanisms of cervical cancer. Drug Discovery today: Disease mechanism, 1, 253-8.
60. Sirskyj D, Mitoma FD, Golshani A, et al (2011). Innovative bioinformatic approaches for developing peptide-based vaccines against hypervariable viruses. Immunol Cell Biol, 89, 81-9.
61. Sudandiradoss C, George Priya Doss C, Rajasekaran R, et al (2008). Analysis of binding residues between scorpion neurotoxins and D2 dopamine receptor: a computational docking study. Comput Biol Med, 38, 1056-67.
62. Stanley MA (2009). Immune responses to human papilloma viruses. Indian J Med Res, 130, 266-76.
63. The Universal protein resource (Uniprot) in 2010. Nucleic Acids Res, 38, 142-8.
64. Tomar N, De RK (2010). Immunoinformatics: an integrated scenario. Immunol, 131, 153-68.
65. Tong JC, Tan TW, Shoba R (2006). Methods and protocols for prediction of immunogenic epitopes. Briefings in Bioinformatics, 8, 96-108.
66. Tumban E, Peabody J, Peabody DS, et al (2011). A pan-HPV vaccine based on bacteriophage PP7 VLPs displaying broadly cross-neutralizing epitopes from the HPV minor capsid protein, L2. PLoS One, 6, 23310.
67. Waldmann TA (2003). Immune responses to human Papilloma viruses. Nat Med, 9, 269-77.
68. Walshe VA, Hattotuwagama CK, Doytchinova IA, et al (2009). Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw *0102: a bioinformatic approach to the prediction of new epitopes. PLoS One, 4, 8095.
69. Whelan S, Lio P, Goldman N (2001). Molecular phylogenetics: state-of-art methods for looking into the past. Trends Genet, 17, 262-72.
70. Wu CY, Monie A, Pang X, Hung CF, Wu TC (2010). Improving therapeutic HPV peptide-based vaccine potency by enhancing CD4+ T help and dendritic cell activation. J Biomed Sci, 17, 88-97.
71. Yao B, Zheng D, Liang S, et al (2013). Conformational B-Cell epitope prediction on antigen protein structures: a review of current algorithms and comparison with common binding site prediction methods. PLoS One, 8, 62249
72. Yasser ELM, Dobbs D, Honavar V (2008). Predicting linear B-cell epitopes using string kernels. J Mol Recognit, 21, 243-55
73. rd International conference on biomedical engineering and informatics. BMEI, 10, 5640578.