In silico based multi-epitope vaccine design against norovirus

References

• Abraham Peele, K., Srihansa, T., Krupanidhi, S., Ayyagari, V. S., & Venkateswarulu, T. C. (2021). Design of multi-epitope vaccine candidate against SARS-CoV-2: a study. Journal of Biomolecular Structure & Dynamics, 39(10), 3793–3801. https://doi.org/10.1080/07391102.2020.1770127
   PubMed Web of Science ®Google Scholar
• Alberts, B. (2017). Molecular biology of the cell. Garland Science.
   Google Scholar
• Bartsch, S. M., Lopman, B. A., Ozawa, S., Hall, A. J., & Lee, B. Y. (2016). Global economic burden of norovirus gastroenteritis. PLoS One, 11(4), e0151219. https://doi.org/10.1371/journal.pone.0151219
   PubMed Web of Science ®Google Scholar
• Bui, H.-H., Sidney, J., Li, W., Fusseder, N., & Sette, A. (2007). Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines. BMC Bioinformatics, 8, 361. https://doi.org/10.1186/1471-2105-8-361
   PubMed Web of Science ®Google Scholar
• Calis, J. J. A., Maybeno, M., Greenbaum, J. A., Weiskopf, D., De Silva, A. D., Sette, A., Keşmir, C., & Peters, B. (2013). Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Computational Biology, 9(10), e1003266. https://doi.org/10.1371/journal.pcbi.1003266
   PubMed Web of Science ®Google Scholar
• Chen, X., Zaro, J. L., & Shen, W. C. (2013). Fusion protein linkers: Property, design and functionality. Advanced Drug Delivery Reviews, 65(10), 1357–1369.
   PubMed Web of Science ®Google Scholar
• Chisholm, H. (2018). The Encyclopaedia Britannica: A dictionary of arts, sciences, literature and general information (Vol. 10). Palala Press.
   Google Scholar
• Choe, J., Kelker, M. S., & Wilson, I. A. (2005). Crystal structure of human toll-like receptor 3 (TLR3) ectodomain. Science (New York, NY), 309(5734), 581–585. https://doi.org/10.1126/science.1115253
   Google Scholar
• Colovos, C., & Yeates, T. O. (1993). Verification of protein structures: patterns of nonbonded atomic interactions. Protein Science, 2(9), 1511–1519. https://doi.org/10.1002/pro.5560020916
   PubMed Web of Science ®Google Scholar
• DeLano, W. L. (2002). Pymol: An open-source molecular graphics tool. CCP4 Newsletter on Protein Crystallography, 40, 82–92.
   Google Scholar
• Dhanda, S. K., Vir, P., & Raghava, G. P. S. (2013). Designing of interferon-gamma inducing MHC class-II binders. Biology Direct, 8, 30. https://doi.org/10.1186/1745-6150-8-30
   PubMed Web of Science ®Google Scholar
• 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/10.1007/s00894-014-2278-5
   PubMed Web of Science ®Google Scholar
• Doytchinova, I. A., & Flower, D. R. (2007a). Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties. Vaccine, 25(5), 856–866. https://doi.org/10.1016/j.vaccine.2006.09.032
   PubMed Web of Science ®Google Scholar
• Doytchinova, I. A., & Flower, D. R. (2007b). VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics, 8(1), 4. https://doi.org/10.1186/1471-2105-8-4
   PubMed Web of Science ®Google Scholar
• Doytchinova, I. A., & Flower, D. R. (2008). Bioinformatic approach for identifying parasite and fungal candidate subunit vaccines. Open Vaccine Journal, 1(1), 4.
   Google Scholar
• Eden, J.-S., Lim, K. L., & White, P. A. (2012). Complete genome of the human norovirus GIV.1 strain Lake Macquarie virus. Journal of Virology, 86(18), 10251–10252. https://doi.org/10.1128/JVI.01604-12
   PubMed Web of Science ®Google Scholar
• Eisenberg, D., Lüthy, R., & Bowie, J. U. (1997). VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods in Enzymology, 277, 396–404. https://doi.org/10.1016/s0076-6879(97)77022-8
   PubMed Web of Science ®Google Scholar
• Ertl, H. C., Dietzschold, B., & Otvos, L. (1991). T helper cell epitope of rabies virus nucleoprotein defined by tri‐and tetrapeptides. European Journal of Immunology, 21(1), 1–10.
   PubMed Web of Science ®Google Scholar
• Esposito, S., & Principi, N. (2020). Norovirus vaccine: Priorities for future research and development. Frontiers in Immunology, 11(1383), 1383.
   PubMedGoogle Scholar
• Fleri, W., Paul, S., Dhanda, S. K., Mahajan, S., Xu, X., Peters, B., & Sette, A. (2017). The immune epitope database and analysis resource in epitope discovery and synthetic vaccine design. Frontiers in Immunology, 8, 278.
   PubMed Web of Science ®Google Scholar
• Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., & Appel, R. D. (2005). Protein identification and analysis tools on the ExPASy server. The Proteomics Protocols Handbook, 571–607. https://doi.org/10.1385/1-59259-890-0:571.
   Google Scholar
• Guo, Y., Yu, L., Wen, Z., & Li, M. (2008). Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences. Nucleic Acids Research, 36(9), 3025–3030. https://doi.org/10.1093/nar/gkn159
   PubMed Web of Science ®Google Scholar
• Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., & Raghava, G. P. S., Open Source Drug Discovery Consortium. (2013). In silico approach for predicting toxicity of peptides and proteins. PLoS One, 8(9), e73957. https://doi.org/10.1371/journal.pone.0073957
   PubMed Web of Science ®Google Scholar
• Hall, A. J., Lopman, B. A., Payne, D. C., Patel, M. M., Gastañaduy, P. A., Vinjé, J., & Parashar, U. D. (2013). Norovirus disease in the United States. Emerging Infectious Diseases, 19(8), 1198–1205. https://doi.org/10.3201/eid1908.130465
   PubMed Web of Science ®Google Scholar
• Hallowell, B. D., Parashar, U. D., & Hall, A. J. (2019). Epidemiologic challenges in norovirus vaccine development. Human Vaccines & Immunotherapeutics, 15(6), 1279–1283. https://doi.org/10.1080/21645515.2018.1553594
   PubMed Web of Science ®Google Scholar
• Hebditch, M., Alejandro Carballo-Amador, M., Charonis, S., Curtis, R., & Warwicker, J. (2017). Protein–Sol: A web tool for predicting protein solubility from sequence. Bioinformatics (Oxford, England), 33(19), 3098–3100. https://doi.org/10.1093/bioinformatics/btx345
   PubMed Web of Science ®Google Scholar
• Johnson, M., Zaretskaya, I., Raytselis, Y., Merezhuk, Y., McGinnis, S., & Madden, T. L. (2008). NCBI BLAST: a better web interface. Nucleic Acids Research, 36(Web Server issue), W5–W9. https://doi.org/10.1093/nar/gkn201
   PubMed Web of Science ®Google Scholar
• Jones, D. T. (1999). Protein secondary structure prediction based on position-specific scoring matrices 1. Journal of Molecular Biology, 292(2), 195–202. https://doi.org/10.1006/jmbi.1999.3091
   PubMed Web of Science ®Google Scholar
• Khairkhah, N., Aghasadeghi, M. R., Namvar, A., & Bolhassani, A. (2020). Design of novel multiepitope constructs-based peptide vaccine against the structural S, N and M proteins of human COVID-19 using immunoinformatics analysis. PLoS One, 15(10), e0240577. https://doi.org/10.1371/journal.pone.0240577
   PubMed Web of Science ®Google Scholar
• Khan, M. T., Islam, R., Jerin, T. J., Mahmud, A., Khatun, S., Kobir, A., Islam, M. N., Akter, A., & Mondal, S. I. (2021). Immunoinformatics and molecular dynamics approaches: Next generation vaccine design against West Nile virus. PLoS One, 16(6), e0253393. https://doi.org/10.1371/journal.pone.0253393
   PubMed Web of Science ®Google Scholar
• Kirkland, T. N., Finley, F., Orsborn, K. I., & Galgiani, J. N. (1998). Evaluation of the proline-rich antigen of Coccidioides immitis as a vaccine candidate in mice. Infection and Immunity, 66(8), 3519–3522.
   PubMed Web of Science ®Google Scholar
• Kolla, H. B., Tirumalasetty, C., Sreerama, K., & Ayyagari, V. S. (2021). An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus. Journal of Genetic Engineering and Biotechnology, 19(1), 1–14. https://doi.org/10.1186/s43141-021-00160-z
   PubMed Web of Science ®Google Scholar
• Larsen, M. V., Lundegaard, C., Lamberth, K., Buus, S., Brunak, S., Lund, O., & Nielsen, M. (2005). An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions. European Journal of Immunology, 35(8), 2295–2303. https://doi.org/10.1002/eji.200425811
   PubMed Web of Science ®Google Scholar
• Larsen, M. V., Lundegaard, C., Lamberth, K., Buus, S., Lund, O., & Nielsen, M. (2007). Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinformatics, 8, 424. https://doi.org/10.1186/1471-2105-8-424
   PubMed Web of Science ®Google Scholar
• Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., & Shaw, D. E. (2010). Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins, 78(8), 1950–1958. https://doi.org/10.1002/prot.22711
   PubMed Web of Science ®Google Scholar
• Lucero, Y., Vidal, R., & Miguel, O. G. (2018). Norovirus vaccines under development. Vaccine, 36(36), 5435–5441. https://doi.org/10.1016/j.vaccine.2017.06.043
   PubMed Web of Science ®Google Scholar
• Mark, P., & Nilsson, L. (2001). Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K. The Journal of Physical Chemistry A, 105(43), 9954–9960. https://doi.org/10.1021/jp003020w
   Web of Science ®Google Scholar
• Mattison, C. P., Cardemil, C. V., & Hall, A. J. (2018). Progress on norovirus vaccine research: public health considerations and future directions. Expert Review of Vaccines, 17(9), 773–784. https://doi.org/10.1080/14760584.2018.1510327
   PubMed Web of Science ®Google Scholar
• Parra, G. I. (2019). Emergence of norovirus strains: A tale of two genes. Virus Evolution, 5(2), vez048. https://doi.org/10.1093/ve/vez048
   PubMed Web of Science ®Google Scholar
• Parvizpour, S., Pourseif, M. M., Razmara, J., Rafi, M. A., & Omidi, Y. (2020). Epitope-based vaccine design: a comprehensive overview of bioinformatics approaches. Drug Discovery Today, 25(6), 1034–1042. https://doi.org/10.1016/j.drudis.2020.03.006
   PubMed Web of Science ®Google Scholar
• Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
   PubMed Web of Science ®Google Scholar
• Pickett, B. E., Sadat, E. L., Zhang, Y., Noronha, J. M., Squires, R. B., Hunt, V., Liu, M., Kumar, S., Zaremba, S., Gu, Z., Zhou, L., Larson, C. N., Dietrich, J., Klem, E. B., & Scheuermann, R. H. (2012). ViPR: An open bioinformatics database and analysis resource for virology research. Nucleic Acids Research, 40(Database issue), D593–D598. https://doi.org/10.1093/nar/gkr859
   PubMed Web of Science ®Google Scholar
• 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/10.1371/journal.pone.0009862
   PubMed Web of Science ®Google Scholar
• Rawal, K., Sinha, R., Abbasi, B. A., Chaudhary, A., Nath, S. K., Kumari, P., Preeti, P., Saraf, D., Singh, S., Mishra, K., Gupta, P., Mishra, A., Sharma, T., Gupta, S., Singh, P., Sood, S., Subramani, P., Dubey, A. K., Strych, U., Hotez, P. J., & Bottazzi, M. E. (2021). Identification of vaccine targets in pathogens and design of a vaccine using computational approaches. Scientific Reports, 11(1), 17626. https://doi.org/10.1038/s41598-021-96863-x
   PubMed Web of Science ®Google Scholar
• Roy, A., Kucukural, A., & Zhang, Y. (2010). I-TASSER: A unified platform for automated protein structure and function prediction. Nature Protocols, 5(4), 725–738. https://doi.org/10.1038/nprot.2010.5
   PubMed Web of Science ®Google Scholar
• Saha, S., & Raghava, G. P. S. (2004). BcePred: Prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties. Lecture Notes in Computer Science, 3239, 197–204. https://doi.org/10.1007/978-3-540-30220-9_16.
   Google Scholar
• Sanchez-Trincado, J. L., Gomez-Perosanz, M., & Reche, P. A. (2017). Fundamentals and methods for T- and B-cell epitope prediction. Journal of Immunology Research, 2017, 2680160. https://doi.org/10.1155/2017/2680160
   PubMed Web of Science ®Google Scholar
• Sanders, R. W., & Moore, J. P. (2021). Virus vaccines: proteins prefer prolines. Cell Host & Microbe, 29(3), 327–333.
   PubMed Web of Science ®Google Scholar
• Singh, H., Ansari, H. R., & Raghava, G. P. (2013). Improved method for linear B-cell epitope prediction using antigen’s primary sequence. PLoS One, 8(5), e62216.
   PubMed Web of Science ®Google Scholar
• Sun, J., Duffy, K. E., Ranjith-Kumar, C. T., Xiong, J., Lamb, R. J., Santos, J., Masarapu, H., Cunningham, M., Holzenburg, A., Sarisky, R. T., Mbow, M. L., & Kao, C. (2006). Structural and functional analyses of the human Toll-like receptor 3. Role of glycosylation. The Journal of Biological Chemistry, 281(16), 11144–11151. https://doi.org/10.1074/jbc.M510442200. PMID: 16533755.
   PubMed Web of Science ®Google Scholar
• The Proteomics Protocols Handbook. (2005). https://doi.org/10.1385/1592598900.
   Google Scholar
• Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005). GROMACS: fast, flexible, and free. Journal of Computational Chemistry, 26(16), 1701–1718. https://doi.org/10.1002/jcc.20291
   PubMed Web of Science ®Google Scholar
• van Zundert, G. C. P., Rodrigues, J. P. G. L. M., Trellet, M., Schmitz, C., Kastritis, P. L., Karaca, E., Melquiond, A. S. J., van Dijk, M., de Vries, S. J., & Bonvin, A. M. J. J. (2016). The HADDOCK2.2 web server: User-friendly integrative modeling of biomolecular complexes. Journal of Molecular Biology, 428(4), 720–725. https://doi.org/10.1016/j.jmb.2015.09.014
   PubMed Web of Science ®Google Scholar
• Vega, E., Barclay, L., Gregoricus, N., Shirley, S. H., Lee, D., & Vinje, J. (2014). Genotypic and epidemiologic trends of norovirus outbreaks in the United States, 2009 to 2013. Journal of Clinical Microbiology, 52(1), 147–155. https://doi.org/10.1128/JCM.02680-13
   PubMed Web of Science ®Google Scholar
• 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–D343. https://doi.org/10.1093/nar/gky1006
   PubMed Web of Science ®Google Scholar
• Wallace, A. C., Laskowski, R. A., & Thornton, J. M. (1995). LIGPLOT: A program to generate schematic diagrams of protein-ligand interactions. Protein Engineering, 8(2), 127–134. https://doi.org/10.1093/protein/8.2.127
   PubMedGoogle Scholar
• Wang, P., Sidney, J., Dow, C., Mothé, B., Sette, A., & Peters, B. (2008). A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Computational Biology, 4(4), e1000048. https://doi.org/10.1371/journal.pcbi.1000048
   PubMed Web of Science ®Google Scholar
• Wang, P., Sidney, J., Kim, Y., Sette, A., Lund, O., Nielsen, M., & Peters, B. (2010). Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinformatics, 11, 568. https://doi.org/10.1186/1471-2105-11-568
   PubMed Web of Science ®Google Scholar
• 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(Web Server issue), W407–W410. https://doi.org/10.1093/nar/gkm290
   PubMed Web of Science ®Google Scholar
• Yang, J., & Zhang, Y. (2015). I-TASSER server: new development for protein structure and function predictions. Nucleic Acids Research, 43(W1), W174–W181. https://doi.org/10.1093/nar/gkv342
   PubMed Web of Science ®Google Scholar
• Yang, J., Yan, R., Roy, A., Xu, D., Poisson, J., & Zhang, Y. (2015). The I-TASSER Suite: protein structure and function prediction. Nature Methods, 12(1), 7–8. https://doi.org/10.1038/nmeth.3213
   PubMed Web of Science ®Google Scholar
• Ząbczyńska, M., & Pocheć, E. (2015). The role of protein glycosylation in immune system. Postepy Biochemii, 61(2), 129–137.
   PubMedGoogle Scholar