References
- Abbink, P., Stephenson, K. E., & Barouch, D. H. (2018). Zika virus vaccines. Nature Reviews Microbiology, 16(10), 594–600. https://doi.org/https://doi.org/10.1038/s41579-018-0039-7
- Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1-2, 19–25. https://doi.org/https://doi.org/10.1016/j.softx.2015.06.001
- Agumadu, V. C., & Ramphul, K. (2018). Zika virus: A review of literature. Cureus, 10(7), e3025. https://doi.org/https://doi.org/10.7759/cureus.3025
- Almofti, Y. A., Abd-Elrahman, K. A., Gassmallah, S. A., & Salih, M. A. (2018). Multi epitopes vaccine prediction against severe acute respiratory syndrome (SARS) coronavirus using immunoinformatics approaches. American Journal of Microbiological Research, 6(3), 94–114. https://doi.org/https://doi.org/10.12691/ajmr-6-3-5
- Angov, E. (2011). Codon usage: Nature’s roadmap to expression and folding of proteins. Biotechnology Journal, 6(6), 650–659. https://doi.org/https://doi.org/10.1002/biot.201000332
- Arai, R., Ueda, H., Kitayama, A., Kamiya, N., & Nagamune, T. (2001). Design of the linkers which effectively separate domains of a bifunctional fusion protein. Protein Engineering, 14(8), 529–532. https://doi.org/https://doi.org/10.1093/protein/14.8.52 https://doi.org/https://doi.org/10.1093/protein/14.8.529
- Arpin, C., Dechanet, J., Van Kooten, C., Merville, P., Grouard, G., Briere, F., Banchereau, J., & Liu, Y. J. (1995). Generation of memory B cells and plasma cells in vitro. Science, 268(5211), 720–722. https://doi.org/https://doi.org/10.1126/science.7537388
- Atapour, A., Mokarram, P., MostafaviPour, Z., Hosseini, S. Y., Ghasemi, Y., Mohammadi, S., & Nezafat, N. (2019). Designing a fusion protein vaccine against HCV: An in silico approach. International Journal of Peptide Research and Therapeutics, 25(3), 861–872. https://doi.org/https://doi.org/10.1007/s10989-018-9735-4
- Bacchetta, R., Gregori, S., & Roncarolo, M. G. (2005). CD4+ regulatory T cells: Mechanisms of induction and effector function. Autoimmunity Reviews, 4(8), 491–496. https://doi.org/10.1016/j.autrev.2005.04.005
- Bhatt, S., Gething, P. W., Brady, O. J., Messina, J. P., Farlow, A. W., Moyes, C. L., Drake, J. M., Brownstein, J. S., Hoen, A. G., Sankoh, O., Myers, M. F., George, D. B., Jaenisch, T., Wint, G. R. W., Simmons, C. P., Scott, T. W., Farrar, J. J., & Hay, S. I. (2013). The global distribution and burden of dengue. Nature, 496(7446), 504–507. https://doi.org/https://doi.org/10.1038/nature12060
- Biovia, D. S., Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., & Richmond, T. J. (2000). BIOVIA, discovery studio visualizer, v. 17.2, San Diego: Dassault systèmes, 2016. The Journal of Chemical Physics, 10, 0021–9991.
- Biswal, J. K., Bisht, P., Mohapatra, J. K., Ranjan, R., Sanyal, A., & Pattnaik, B. (2015). Application of a recombinant capsid polyprotein (P1) expressed in a prokaryotic system to detect antibodies against foot-and-mouth disease virus serotype O. Journal of Virological Methods, 215–216, 45–51. https://doi.org/https://doi.org/10.1016/j.jviromet.2015.02.008
- Brady, O. J., Gething, P. W., Bhatt, S., Messina, J. P., Brownstein, J. S., Hoen, A. G., Moyes, C. L., Farlow, A. W., Scott, T. W., & Hay, S. I. (2012). Refining the global spatial limits of dengue virus transmission by evidence-based consensus. PLoS Neglected Tropical Diseases, 6(8), e1760. https://doi.org/https://doi.org/10.1371/journal.pntd.0001760
- Buchan, D. W., & Jones, D. T. (2019). The PSIPRED protein analysis workbench: 20 years on. Nucleic Acids Research, 47(W1), W402–7. https://doi.org/https://doi.org/10.1093/nar/gkz297
- Bui, H. H., Sidney, J., Dinh, K., Southwood, S., Newman, M. J., & Sette, A. (2006). Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics, 7(1), 153. https://doi.org/https://doi.org/10.1186/1471-2105-7-153
- Cano, R. L., & Lopera, H. D. (2013). Introduction to T and B lymphocytes. Autoimmunity: from bench to bedside. El Rosario University Press.
- Carvalho, L. H., Sano, G. I., Hafalla, J. C., Morrot, A., De Lafaille, M. A., & Zavala, F. (2002). IL-4-secreting CD4+ T cells are crucial to the development of CD8+ T-cell responses against malaria liver stages. Nature Medicine, 8(2), 166–170. https://doi.org/https://doi.org/10.1038/nm0202-166
- Carrillo-Hernández, M. Y., Ruiz-Saenz, J., Villamizar, L. J., Gómez-Rangel, S. Y., & Martínez-Gutierrez, M. (2018). Co-circulation and simultaneous co-infection of dengue, chikungunya, and zika viruses in patients with febrile syndrome at the Colombian-Venezuelan border. BMC Infectious Diseases, 18(1), 61. https://doi.org/https://doi.org/10.1186/s12879-018-2976-1
- Castiglione, F., Mantile, F., De Berardinis, P., & Prisco, A. (2012). How the interval between prime and boost injection affects the immune response in a computational model of the immune system. Computational and Mathematical Methods in Medicine, 2012, 1–9. https://doi.org/https://doi.org/10.1155/2012/842329
- Chang, K. Y., & Yang, J. R. (2013). Analysis and prediction of highly effective antiviral peptides based on random forests. PLoS One, 8(8), e70166. https://doi.org/https://doi.org/10.1371/journal.pone.0070166
- Chaudhri, G., Quah, B. J., Wang, Y., Tan, A. H., Zhou, J., Karupiah, G., & Parish, C. R. (2009). T cell receptor sharing by cytotoxic T lymphocytes facilitates efficient virus control. Proceedings of the National Academy of Sciences of the United States of America, 106(35), 14984–14989. https://doi.org/https://doi.org/10.1073/pnas.090655410
- Chaves, B. A., Orfano, A. S., Nogueira, P. M., Rodrigues, N. B., Campolina, T. B., Nacif-Pimenta, R., Pires, A. C. A. M., Júnior, A. B. V., Paz, A. D. C., Vaz, E. B. D. C., Guerra, M. D. G. V. B., Silva, B. M., de Melo, F. F., Norris, D. E., de Lacerda, M. V. G., Pimenta, P. F. P., & Secundino, N. F. C. (2018). Coinfection with Zika virus (ZIKV) and dengue virus results in preferential ZIKV transmission by vector bite to vertebrate host. The Journal of Infectious Diseases, 218(4), 563–571. https://doi.org/https://doi.org/10.1093/infdis/jiy196
- Chong, L. C., & Khan, A. M. (2019). Vaccine target discovery. Encyclopedia of bioinformatics and computational biology (pp. 241). Elsevier.
- Cohen, J. (2019). Controversy over dengue vaccine risk. Science, 365(6457), 961-962. https://doi.org/https://doi.org/10.1126/science.365.6457.961
- Cooper, M. D. (2015). The early history of B cells. Nature Reviews Immunology, 15(3), 191–197. https://doi.org/https://doi.org/10.1038/nri3801
- Cooper, N. R., & Nemerow, G. R. (1984). The role of antibody and complement in the control of viral infections. Journal of Investigative Dermatology, 83(1), S121–S7. https://doi.org/https://doi.org/10.1038/jid.1984.33
- Craig, D. B., & Dombkowski, A. A. (2013). Disulfide by design 2.0: A web-based tool for disulfide engineering in proteins. BMC Bioinformatics, 14(1), 346. https://doi.org/https://doi.org/10.1186/1471-2105-14-346
- da Silveira, L. T., Tura, B., & Santos, M. (2019). Systematic review of dengue vaccine efficacy. BMC Infectious Diseases, 19(1), 750. https://doi.org/https://doi.org/10.1186/s12879-019-4369-5
- De Groot, A. S., Sbai, H., Aubin, C. S., McMurry, J., & Martin, W. (2002). Immuno-informatics: Mining genomes for vaccine components. Immunology and Cell Biology, 80(3), 255–269. https://doi.org/https://doi.org/10.1046/j.1440-1711.2002.01092.x
- Dhanda, S. K., Vir, P., & Raghava, G. P. (2013). Designing of interferon-gamma inducing MHC class-II binders. Biology Direct, 8(1), 30. https://doi.org/https://doi.org/10.1186/1745-6150-8-30
- Dimitrov, I., Bangov, I., Flower, D. R., & Doytchinova, I. (2014). AllerTOP v.2-a server for in silico prediction of allergens. Journal of Molecular Modeling, 20(6), 2278. https://doi.org/https://doi.org/10.1007/s00894-014-2278-5
- Dimitrov, I., Naneva, L., Doytchinova, I., & Bangov, I. (2014). AllergenFP: Allergenicity prediction by descriptor fingerprints. Bioinformatics, 30(6), 846–851. https://doi.org/https://doi.org/10.1093/bioinformatics/btt619
- Dowd, K. A., DeMaso, C. R., Pelc, R. S., Speer, S. D., Smith, A. R. Y., Goo, L., Platt, D. J., Mascola, J. R., Graham, B. S., Mulligan, M. J., Diamond, M. S., Ledgerwood, J. E., & Pierson, T. C. (2016). Broadly neutralizing activity of Zika virus-immune sera identifies a single viral serotype. Cell Reports, 16(6), 1485–1491. https://doi.org/https://doi.org/10.1016/j.celrep.2016.07.049
- Doytchinova, I. A., & Flower, D. R. (2008). Bioinformatic approach for identifying parasite and fungal candidate subunit vaccines. The Open Vaccine Journal, 1, 4. https://doi.org/https://doi.org/10.2174/1875035400801010022
- Doytchinova, I. A., & Flower, D. R. (2007a). VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics, 8(1), 4. https://doi.org/https://doi.org/10.1186/1471-2105-8-4
- Duhovny, D., Nussinov, R., & Wolfson, H. J. (2002). Efficient unbound docking of rigid molecules. InInternational workshop on algorithms in bioinformatics (pp. 185–200). Springer.
- Dupont-Rouzeyrol, M., O’Connor, O., Calvez, E., Daurès, M., John, M., Grangeon, J. P., & Gourinat, A. C. (2015). Co-infection with Zika and dengue viruses in 2 patients, New Caledonia, 2014. Emerging Infectious Diseases, 21(2), 381–382. https://doi.org/https://doi.org/10.3201/eid2102.141553
- Fatima, K., & Syed, N. I. (2018). Dengvaxia controversy: Impact on vaccine hesitancy. Journal of Global Health, 8(2), 020312. https://doi.org/https://doi.org/10.7189/jogh.08.020312
- Feng, T., Chen, F., Kang, Y., Sun, H., Liu, H., Li, D., Zhu, F., & Hou, T. (2017). HawkRank: A new scoring function for protein-protein docking based on weighted energy terms. Journal of Cheminformatics, 9(1), 66. https://doi.org/https://doi.org/10.1186/s13321-017-0254-7
- Fernandez, E., & Diamond, M. S. (2017). Vaccination strategies against Zika virus. Current Opinion in Virology, 23, 59–67. https://doi.org/https://doi.org/10.1016/j.coviro.2017.03.006
- Funderburg, N., Lederman, M. M., Feng, Z., Drage, M. G., Jadlowsky, J., Harding, C. V., Weinberg, A., & Sieg, S. F. (2007). Human -defensin-3 activates professional antigen-presenting cells via Toll-like receptors 1 and 2. Proceedings of the National Academy of Sciences of the United States of America, 104(47), 18631–18635. https://doi.org/https://doi.org/10.1073/pnas.0702130104
- Garcia, K. C., Teyton, L., & Wilson, I. A. (1999). Structural basis of T cell recognition. Annual Review of Immunology, 17(1), 369–397. https://doi.org/https://doi.org/10.1146/annurev.immunol.17.1.369
- Garnier, J., Gibrat, J. F., & Robson, B. (1996). [32] GOR method for predicting protein secondary structure from amino acid sequence. Methods in enzymology (Vol. 266, pp. 540–553). Academic Press.
- Gasteiger, E., Hoogland, C., Gattiker, A., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein identification and analysis tools on the ExPASy server. The proteomics protocols handbook (pp. 571–607). Humana press.
- Geourjon, C., & Deleage, G. (1995). SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Computer Applications in the Biosciences: Cabios, 11(6), 681–684. https://doi.org/https://doi.org/10.1093/bioinformatics/11.6.681
- Gill, S. C., & Von Hippel, P. H. (1989). Calculation of protein extinction coefficients from amino acid sequence data. Analytical Biochemistry, 182(2), 319–326. https://doi.org/https://doi.org/10.1016/0003-2697(89)90602-7
- Grote, A., Hiller, K., Scheer, M., Münch, R., Nörtemann, B., Hempel, D. C., & Jahn, D. (2005). JCat: A novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Research, 33, W526–W531. https://doi.org/https://doi.org/10.1093/nar/gki376
- Gruber, A. R., Lorenz, R., Bernhart, S. H., Neuböck, R., & Hofacker, I. L. (2008). The vienna RNA websuite. Nucleic Acids Research, 36, W70–W74. https://doi.org/https://doi.org/10.1093/nar/gkn188
- Gu, Y., Sun, X., Li, B., Huang, J., Zhan, B., & Zhu, X. (2017). Vaccination with a paramyosin-based multi-epitope vaccine elicits significant protective immunity against Trichinella spiralis infection in mice. Frontiers in Microbiology, 8, 1475. https://doi.org/https://doi.org/10.3389/fmicb.2017.01475
- Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., & Raghava, G. P, Open Source Drug Discovery Consortium (2013). In silico approach for predicting toxicity of peptides and proteins. PLoS One, 8(9), e73957. https://doi.org/https://doi.org/10.1371/journal.pone.0073957
- Guruprasad, K., Reddy, B. B., & Pandit, M. W. (1990). Correlation between stability of a protein and its dipeptide composition: A novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Engineering, 4(2), 155–161. https://doi.org/https://doi.org/10.1093/protein/4.2.155
- Guzman, M. G., Halstead, S. B., Artsob, H., Buchy, P., Farrar, J., Gubler, D. J., Hunsperger, E., Kroeger, A., Margolis, H. S., Martínez, E., Nathan, M. B., Pelegrino, J. L., Simmons, C., Yoksan, S., & Peeling, R. W. (2010). Dengue: A continuing global threat. Nature Reviews Microbiology, 8(12), S7–S16. https://doi.org/https://doi.org/10.1038/nrmicro2460
- Hamasaki‐Katagiri, N., Lin, B. C., Simon, J., Hunt, R. C., Schiller, T., Russek‐Cohen, E., Komar, A. A., Bar, H., & Kimchi‐Sarfaty, C. (2017). The importance of mRNA structure in determining the pathogenicity of synonymous and non-synonymous mutations in haemophilia. Haemophilia: The Official Journal of the World Federation of Hemophilia, 23(1), e8–e17. https://doi.org/https://doi.org/10.1111/hae.13107
- Hancock, R. E., Nijnik, A., & Philpott, D. J. (2012). Modulating immunity as a therapy for bacterial infections. Nature Reviews Microbiology, 10(4), 243–254. https://doi.org/https://doi.org/10.1038/nrmicro2745
- Hebditch, M., Carballo-Amador, M. A., Charonis, S., Curtis, R., & Warwicker, J. (2017). Protein-Sol: a web tool for predicting protein solubility from sequence. Bioinformatics, 33(19), 3098–3100. https://doi.org/https://doi.org/10.1093/bioinformatics/btx345
- Hoque, M. N., Istiaq, A., Clement, R. A., Sultana, M., Crandall, K. A., Siddiki, A. Z., & Hossain, M. A. (2019). Metagenomic deep sequencing reveals association of microbiome signature with functional biases in bovine mastitis. Scientific Reports, 9(1), 1–4. https://doi.org/https://doi.org/10.1038/s41598-019-49468-4
- Hou, T., Wang, J., Li, Y., & Wang, W. (2011). Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. Journal of Chemical Information and Modeling, 51(1), 69–82. https://doi.org/https://doi.org/10.1021/ci100275a
- Ikai, A. (1980). Thermostability and aliphatic index of globular proteins. The Journal of Biochemistry, 88(6), 1895–1898. https://doi.org/https://doi.org/10.1093/oxfordjournals.jbchem.a133168
- Jones, D. T. (1999). Protein secondary structure prediction based on position-specific scoring matrices. Journal of Molecular Biology, 292(2), 195–202. https://doi.org/https://doi.org/10.1006/jmbi.1999.3091
- Källberg, M., Wang, H., Wang, S., Peng, J., Wang, Z., Lu, H., & Xu, J. (2012). Template-based protein structure modeling using the RaptorX web server. Nature Protocols, 7(8), 1511–1522. https://doi.org/https://doi.org/10.1038/nprot.2012.085
- Kambayashi, T., & Laufer, T. M. (2014). Atypical MHC class II-expressing antigen-presenting cells: Can anything replace a dendritic cell? Nature Reviews. Immunology, 14(11), 719–730. https://doi.org/https://doi.org/10.1038/nri3754
- Kaminski, G. A., Friesner, R. A., Tirado-Rives, J., & Jorgensen, W. L. (2001). Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. The Journal of Physical Chemistry B, 105(28), 6474–6487. https://doi.org/https://doi.org/10.1021/jp003919d
- Khatoon, N., Pandey, R. K., & Prajapati, V. K. (2017). Exploring Leishmania secretory proteins to design B and T cell multi-epitope subunit vaccine using immunoinformatics approach. Scientific Reports, 7(1), 1–2. https://doi.org/https://doi.org/10.1038/s41598-017-08842-w
- Kindhauser, M. K., Allen, T., Frank, V., Santhana, R. S., & Dye, C. (2016). Zika: The origin and spread of a mosquito-borne virus. Bulletin of the World Health Organization, 94(9), 675–686C. https://doi.org/https://doi.org/10.2471/BLT.16.171082
- Klein, D. E., Choi, J. L., & Harrison, S. C. (2013). Structure of a dengue virus envelope protein late-stage fusion intermediate. Journal of Virology, 87(4), 2287–2293. https://doi.org/https://doi.org/10.1128/JVI.02957-12
- Ko, J., Park, H., Heo, L., & Seok, C. (2012). GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Research, 40, W294–W297. https://doi.org/https://doi.org/10.1093/nar/gks493
- Kozakov, D., Hall, D. R., Xia, B., Porter, K. A., Padhorny, D., Yueh, C., Beglov, D., & Vajda, S. (2017). The ClusPro web server for protein–protein docking. Nature Protocols, 12(2), 255–278. https://doi.org/https://doi.org/10.1038/nprot.2016.169
- Kyte, J., & Doolittle, R. F. (1982). A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology, 157(1), 105–132. https://doi.org/https://doi.org/10.1016/0022-2836(82)90515-0
- Larsen, J. E., Lund, O., & Nielsen, M. (2006). Improved method for predicting linear B-cell epitopes. Immunome Research, 2(1), 2. https://doi.org/https://doi.org/10.1186/1745-7580-2-2
- Laskowski, R. A., MacArthur, M. W., & Thornton, J. M. (2006). PROCHECK: Validation of protein-structure coordinates. International tables for crystallography (pp. 722–725). Wiley.
- Lee, S. J., Shin, S. J., Lee, M. H., Lee, M.-G., Kang, T. H., Park, W. S., Soh, B. Y., Park, J. H., Shin, Y. K., Kim, H. W., Yun, C. H., Jung, I. D., & Park, Y. M. (2014). A potential protein adjuvant derived from Mycobacterium tuberculosis Rv0652 enhances dendritic cells-based tumor immunotherapy. PLoS One, 9(8), e104351. https://doi.org/https://doi.org/10.1371/journal.pone.0104351
- Levin, J. M., Robson, B., & Garnier, J. (1986). An algorithm for secondary structure determination in proteins based on sequence similarity. FEBS Letters, 205(2), 303–308. https://doi.org/https://doi.org/10.1016/0014-5793(86)80917-6
- Luckheeram, R. V., Zhou, R., Verma, A. D., & Xia, B. (2012). CD4+ T cells: Differentiation and functions. Clinical and Developmental Immunology, 2012, 1–12. https://doi.org/https://doi.org/10.1155/2012/925135
- Ma, J., Wang, S., Zhao, F., & Xu, J. (2013). Protein threading using context-specific alignment potential. Bioinformatics, 29(13), i257–65. https://doi.org/https://doi.org/10.1093/bioinformatics/btt210
- Magnan, C. N., Zeller, M., Kayala, M. A., Vigil, A., Randall, A., Felgner, P. L., & Baldi, P. (2010). High-throughput prediction of protein antigenicity using protein microarray data. Bioinformatics, 26(23), 2936–2943. https://doi.org/https://doi.org/10.1093/bioinformatics/btq551
- María, R. A., Arturo, C. V., Alicia, J. A., Paulina, M. L., & Gerardo, A. O. (2017). The impact of bioinformatics on vaccine design and development. InTech.
- Mathews, D. H., Sabina, J., Zuker, M., & Turner, D. H. (1999). Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. Journal of Molecular Biology, 288(5), 911–940. https://doi.org/https://doi.org/10.1006/jmbi.1999.2700
- Mathews, D. H., Turner, D. H., & Zuker, M. (2007). RNA secondary structure prediction. Current Protocols in Nucleic Acid Chemistry, 28(1), 11–12. https://doi.org/https://doi.org/10.1002/0471142700.nc1102s28
- Merten, O. W. (2002). Virus contaminations of cell cultures - A biotechnological view. Cytotechnology, 39(2), 91–116. https://doi.org/10.1023/A:1022969101804
- Möller, S., Croning, M. D., & Apweiler, R. (2001). Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics, 17(7), 646–653. https://doi.org/https://doi.org/10.1093/bioinformatics/17.7.646
- Morla, S., Makhija, A., & Kumar, S. (2016). Synonymous codon usage pattern in glycoprotein gene of rabies virus. Gene, 584(1), 1–6. https://doi.org/https://doi.org/10.1016/j.gene.2016.02.047
- Morris, A. L., MacArthur, M. W., Hutchinson, E. G., & Thornton, J. M. (1992). Stereochemical quality of protein structure coordinates. Proteins, 12(4), 345–364. https://doi.org/https://doi.org/10.1002/prot.340120407
- Mustafa, M. S., Rasotgi, V., Jain, S., & Gupta, V. (2015). Discovery of fifth serotype of dengue virus (DENV-5): A new public health dilemma in dengue control. Medical Journal, Armed Forces India, 71(1), 67–70. https://doi.org/https://doi.org/10.1016/j.mjafi.2014.09.011
- Nagpal, G., Usmani, S. S., Dhanda, S. K., Kaur, H., Singh, S., Sharma, M., & Raghava, G. P. (2017). Computer-aided designing of immunosuppressive peptides based on IL-10 inducing potential. Scientific Reports, 7, 42851. https://doi.org/https://doi.org/10.1038/srep42851
- Oyarzún, P., & Kobe, B. (2016). Recombinant and epitope-based vaccines on the road to the market and implications for vaccine design and production. Human Vaccines & Immunotherapeutics, 12(3), 763–767. https://doi.org/https://doi.org/10.1080/21645515.2015.1094595
- Pace, C. N., Vajdos, F., Fee, L., Grimsley, G., & Gray, T. (1995). How to measure and predict the molar absorption coefficient of a protein. Protein Science: A Publication of the Protein Society, 4(11), 2411–2423. https://doi.org/https://doi.org/10.1002/pro.5560041120
- Panda, S., & Chandra, G. (2012). Physicochemical characterization and functional analysis of some snake venom toxin proteins and related non-toxin proteins of other chordates. Bioinformation, 8(18), 891–896. https://doi.org/https://doi.org/10.6026/97320630008891
- Pandey, R. K., Sundar, S., & Prajapati, V. K. (2016). Differential expression of miRNA regulates T cell differentiation and plasticity during visceral leishmaniasis infection. Frontiers in Microbiology, 7, 206. https://doi.org/https://doi.org/10.3389/fmicb.2016.00206
- Pei, H., Liu, J., Cheng, Y., Sun, C., Wang, C., Lu, Y., Ding, J., Zhou, J., & Xiang, H. (2005). Expression of SARS-coronavirus nucleocapsid protein in Escherichia coli and Lactococcus lactis for serodiagnosis and mucosal vaccination. Applied Microbiology and Biotechnology, 68(2), 220–227. https://doi.org/https://doi.org/10.1007/s00253-004-1869-y
- Peng, J., & Xu, J. (2011). RaptorX: Exploiting structure information for protein alignment by statistical inference. Proteins: Structure, Function, and Bioinformatics, 79(S10), 161–171. https://doi.org/https://doi.org/10.1002/prot.23175
- Peters, B., & Sette, A. (2005). Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics, 6(1), 132. https://doi.org/https://doi.org/10.1186/1471-2105-6-132
- Petersen, M. T., Jonson, P. H., & Petersen, S. B. (1999). Amino acid neighbours and detailed conformational analysis of cysteines in proteins. Protein Engineering, 12(7), 535–548. https://doi.org/https://doi.org/10.1093/protein/12.7.535
- Poland, G. A., Ovsyannikova, I. G., & Jacobson, R. M. (2009). Application of pharmacogenomics to vaccines. Pharmacogenomics, 10(5). https://doi.org/https://doi.org/10.2217/pgs.09.25
- Ponomarenko, J., Bui, H. H., Li, W., Fusseder, N., Bourne, P. E., Sette, A., & Peters, B. (2008). ElliPro: A new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 9(1), 514. https://doi.org/https://doi.org/10.1186/1471-2105-9-514
- Purcell, A. W., McCluskey, J., & Rossjohn, J. (2007). More than one reason to rethink the use of peptides in vaccine design. Nature Reviews Drug Discovery, 6(5), 404–414. https://doi.org/10.1038/nrd2224 PMC]]
- Rana, A., & Akhter, Y. (2016). A multi-subunit based, thermodynamically stable model vaccine using combined immunoinformatics and protein structure based approach. Immunobiology, 221(4), 544–557. https://doi.org/https://doi.org/10.1016/j.imbio.2015.12.004
- Rapin, N., Lund, O., Bernaschi, M., & Castiglione, F. (2010). Computational immunology meets bioinformatics: The use of prediction tools for molecular binding in the simulation of the immune system. PLoS One, 5(4), e9862. https://doi.org/https://doi.org/10.1371/journal.pone.0009862
- Rappuoli, R. (2000). Reverse vaccinology. Current Opinion in Microbiology, 3(5), 445–450. https://doi.org/https://doi.org/10.1016/S1369-5274(00)00119-3
- Romagnani, S. (1997). The th1/th2 paradigm. Immunology Today, 18(6), 263–266. https://doi.org/https://doi.org/10.1016/S0167-5699(97)80019-9
- Saadi, M., Karkhah, A., & Nouri, H. R. (2017). Development of a multi-epitope peptide vaccine inducing robust T cell responses against brucellosis using immunoinformatics based approaches. Infection, Genetics and Evolution: Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases, 51, 227–234. https://doi.org/https://doi.org/10.1016/j.meegid.2017.04.009
- Sarkar, B., Ullah, M. A., Johora, F. T., Taniya, M. A., & Araf, Y. (2020). Immunoinformatics-guided designing of epitope-based subunit vaccine against the SARS Coronavirus-2 (SARS-CoV-2). Immunobiology, 225(3), 151955. https://doi.org/https://doi.org/10.1016/j.imbio.2020.151955
- Saha, S., & Raghava, G. P. (2006). AlgPred: Prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Research, 34, W202– W20 9. https://doi.org/https://doi.org/10.1093/nar/gkl343
- Schneidman-Duhovny, D., Inbar, Y., Nussinov, R., & Wolfson, H. J. (2005). PatchDock and SymmDock: Servers for rigid and symmetric docking. Nucleic Acids Research, 33, W363–7. https://doi.org/https://doi.org/10.1093/nar/gki481
- Shey, R. A., Ghogomu, S. M., Esoh, K. K., Nebangwa, N. D., Shintouo, C. M., Nongley, N. F., Asa, B. F., Ngale, F. N., Vanhamme, L., & Souopgui, J. (2019). In-silico design of a multi-epitope vaccine candidate against onchocerciasis and related filarial diseases. Scientific Reports, 9(1), 1–8. https://doi.org/https://doi.org/10.1038/s41598-019-40833-x
- Simmons, C. P., Farrar, J. J., van Vinh Chau, N., & Wills, B. (2012). Dengue. The New England Journal of Medicine, 366(15), 1423–1432. https://doi.org/https://doi.org/10.1056/NEJMra1110265
- Solanki, V., & Tiwari, V. (2018). Subtractive proteomics to identify novel drug targets and reverse vaccinology for the development of chimeric vaccine against Acinetobacter baumannii. Scientific Reports, 8(1), 1–9. https://doi.org/https://doi.org/10.1038/s41598-018-26689-7
- Spreiter, Q., & Walter, M. (1999). Classical molecular dynamics simulation with the Velocity Verlet algorithm at strong external magnetic fields. Journal of Computational Physics, 152(1), 102–119. https://doi.org/https://doi.org/10.1006/jcph.1999.6237
- Sturniolo, T., Bono, E., Ding, J., Raddrizzani, L., Tuereci, O., Sahin, U., Braxenthaler, M., Gallazzi, F., Protti, M. P., Sinigaglia, F., & Hammer, J. (1999). Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nature Biotechnology, 17(6), 555–561. https://doi.org/https://doi.org/10.1038/9858
- Sun, H., Li, Y., Tian, S., Xu, L., & Hou, T. (2014). Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set. Physical Chemistry Chemical Physics, 16(31), 16719–16729. https://doi.org/https://doi.org/10.1039/c4cp01388c
- Tameris, M. D., Hatherill, M., Landry, B. S., Scriba, T. J., Snowden, M. A., Lockhart, S., Shea, J. E., McClain, J. B., Hussey, G. D., Hanekom, W. A., Mahomed, H., & McShane, H. (2013). MVA85A 020 trial study team: Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: A randomised, placebo-controlled phase 2b trial. The Lancet, 381(9871), 1021–1028. https://doi.org/https://doi.org/10.1016/S0140-6736(13)60177-4
- Tang, B., Huo, X., Xiao, Y., Ruan, S., & Wu, J. (2018). A conceptual model for optimizing vaccine coverage to reduce vector-borne infections in the presence of antibody-dependent enhancement. Theoretical Biology & Medical Modelling, 15(1), 13. https://doi.org/https://doi.org/10.1186/s12976-018-0085-x
- Thomsen, M., Lundegaard, C., Buus, S., Lund, O., & Nielsen, M. (2013). MHCcluster, a method for functional clustering of MHC molecules. Immunogenetics, 65(9), 655–665. https://doi.org/https://doi.org/10.1007/s00251-013-0714-9
- Toussi, D. N., & Massari, P. (2014). Immune adjuvant effect of molecularly-defined toll-like receptor ligands. Vaccines, 2(2), 323–353. https://doi.org/https://doi.org/10.3390/vaccines2020323
- Turner, P. J., & Xmgrace, V. (2005). Center for coastal and land-margin research. Oregon Graduate Institute of Science and Technology.
- Ullah, M. A., Sarkar, B., & Islam, S. S. (2020). Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus. Immunobiology, 225(3), 1:151949. https://doi.org/https://doi.org/10.1016/j.imbio.2020.151949
- Vajda, S., Yueh, C., Beglov, D., Bohnuud, T., Mottarella, S. E., Xia, B., Hall, D. R., & Kozakov, D. (2017). New additions to the ClusPro server motivated by CAPRI. Proteins, 85(3), 435–444. https://doi.org/https://doi.org/10.1002/prot.25219
- Vita, R., Mahajan, S., Overton, J. A., Dhanda, S. K., Martini, S., Cantrell, J. R., Wheeler, D. K., Sette, A., & Peters, B. (2019). The immune epitope database (IEDB): 2018 update. Nucleic Acids Research, 47(D1), D339–D3 43. https://doi.org/https://doi.org/10.1093/nar/gky1006
- Wen, D., Foley, S. F., Hronowski, X. L., Gu, S., & Meier, W. (2013). Discovery and investigation of O-xylosylation in engineered proteins containing a (GGGGS) n linker. Analytical Chemistry, 85(9), 4805–4812. https://doi.org/https://doi.org/10.1021/ac400596g
- Weng, G., Wang, E., Wang, Z., Liu, H., Zhu, F., Li, D., & Hou, T. (2019). HawkDock: A web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA. Nucleic Acids Research, 47(W1), W322– W3 30. https://doi.org/https://doi.org/10.1093/nar/gkz397
- World Health Organization. (2019). Zika epidemiology update, July. https://www.who.int/emergencies/diseases/zika/epidemiology-update/en/
- Wiederstein, M., & Sippl, M. J. (2007). ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research, 35, W407–W4010. https://doi.org/https://doi.org/10.1093/nar/gkm290
- Wu, C. Y., Monie, A., Pang, X., Hung, C. F., & Wu, T. C. (2010). Improving therapeutic HPV peptide-based vaccine potency by enhancing CD4+ T help and dendritic cell activation. Journal of Biomedical Science, 17(1), 88. https://doi.org/https://doi.org/10.1186/1423-0127-17-88
- Yuriev, E., & Ramsland, P. A. (2013). Latest developments in molecular docking: 2010-2011 in review. Journal of Molecular Recognition, 26(5), 215–239. https://doi.org/https://doi.org/10.1002/jmr.2266
- Zhang, L. (2018). Multi-epitope vaccines: A promising strategy against tumors and viral infections. Cellular & Molecular Immunology, 15(2), 182–184. https://doi.org/https://doi.org/10.1038/cmi.2017.92
- Zhu, J., & Paul, W. E. (2008). CD4 T cells: Fates, functions, and faults. Blood, 112(5), 1557–1569. https://doi.org/https://doi.org/10.1182/blood-2008-05-078154
- Zuker, M. (2003). Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Research, 31(13), 3406–3415. https://doi.org/https://doi.org/10.1093/nar/gkg595