Exploratory algorithm to devise multi-epitope subunit vaccine by investigating Leishmania donovani membrane proteins

References

• Ahluwalia, P. K., Pandey, R. K., Sehajpal, P. K., & Prajapati, V. K. (2017). Perturbed microRNA expression by Mycobacterium tuberculosis promotes macrophage polarization leading to pro-survival foam cell. Frontiers in Immunology, 8, 107. doi: 10.3389/fimmu.2017.00107.
   PubMed Web of Science ®Google Scholar
• Alberts, B., Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2002). T cells and MHC proteins. New York: Garland Science.
   Google Scholar
• Ali, M., Pandey, R. K., Khatoon, N., Narula, A., Mishra, A., & Prajapati, V. K. (2017). Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection. Scientific Reports, 7(1), 9232. doi: 10.1038/s41598-017-09199-w
   PubMed Web of Science ®Google Scholar
• Alvar, J., Croft, S. L., Kaye, P., Khamesipour, A., Sundar, S., & Reed, S. G. (2013). Case study for a vaccine against leishmaniasis. Vaccine, 31, B244–B249.
   PubMed Web of Science ®Google Scholar
• Aslett, M., Aurrecoechea, C., Berriman, M., Brestelli, J., Brunk, B. P., Carrington, M., … Wang, H. (2010). TriTrypDB: A functional genomic resource for the Trypanosomatidae. Nucleic Acids Research, 38, D457–D462.
   PubMed Web of Science ®Google Scholar
• Bagos, P. G., Liakopoulos, T. D., Spyropoulos, I. C., & Hamodrakas, S. J. (2004). PRED-TMBB: A web server for predicting the topology of beta-barrel outer membrane proteins. Nucleic Acids Research, 32, W400–W404. doi: 10.1093/nar/gkh417
   PubMed Web of Science ®Google Scholar
• Birge, R. B., Boeltz, S., Kumar, S., Carlson, J., Wanderley, J., Calianese, D., … Herrmann, M. (2016). Phosphatidylserine is a global immunosuppressive signal in efferocytosis, infectious disease, and cancer. Cell Death & Differentiation, 23(6), 962.
   PubMed Web of Science ®Google Scholar
• Cheng, J., Randall, A. Z., Sweredoski, M. J., & Baldi, P. (2005). SCRATCH: A protein structure and structural feature prediction server. Nucleic Acids Research, 33, W72–W76.
   PubMed Web of Science ®Google Scholar
• Comber, J. D., & Philip, R. (2014). MHC class I antigen presentation and implications for developing a new generation of therapeutic vaccines. Therapeutic Advances in Vaccines, 2(3), 77–89.
   PubMedGoogle Scholar
• 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.
   PubMed Web of Science ®Google Scholar
• Dani, V. S., Ramakrishnan, C., & Varadarajan, R. (2003). MODIP revisited: Re-evaluation and refinement of an automated procedure for modeling of disulfide bonds in proteins. Protein Engineering, 16(3), 187–193.
   PubMedGoogle Scholar
• Darrieux, M., Goulart, C., Briles, D., & Leite, L. C. D. C. (2015). Current status and perspectives on protein-based pneumococcal vaccines. Critical Reviews in Microbiology, 41(2), 190–200.
   PubMed Web of Science ®Google Scholar
• DeLano, W. L. (2002). PyMOL (p. 700). San Carlos, CA: DeLano Scientific.
   Google Scholar
• Dhanda, S. K., Vir, P., & Raghava, G. P. S. (2013). Designing of interferon-gamma inducing MHC class-II binders. Biology Direct, 8(1), 30. doi: 10.1186/1745-6150-8-30
   PubMed Web of Science ®Google Scholar
• Dundas, J., Ouyang, Z., Tseng, J., Binkowski, A., Turpaz, Y., & Liang, J. (2006). CASTp: Computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Research, 34, W116–W118.
   PubMed Web of Science ®Google Scholar
• Emanuelsson, O., Nielsen, H., Brunak, S., & von Heijne, G. (2000). Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. Journal of Molecular Biology, 300(4), 1005–1016.
   PubMed Web of Science ®Google Scholar
• Finco, O., & Rappuoli, R. (2014). Designing vaccines for the twenty-first century society. Frontiers in Immunology, 5, 12.
   PubMed Web of Science ®Google Scholar
• 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.
   PubMed Web of Science ®Google Scholar
• Hailu, A., Dagne, D. A., & Boelaert, M. (2016). Leishmaniasis neglected tropical diseases-sub-Saharan Africa (pp. 87–112). New York: Springer.
   Google Scholar
• Hendrickx, S., Guerin, P. J., Caljon, G., Croft, S. L., & Maes, L. (2016). Evaluating drug resistance in visceral leishmaniasis: the challenges. Parasitology, 145(4), 453–463.
   PubMed Web of Science ®Google Scholar
• Hotez, P. J., Savioli, L., & Fenwick, A. (2012). Neglected tropical diseases of the Middle East and North Africa: Review of their prevalence, distribution, and opportunities for control. PLoS Neglected Tropical Diseases, 6(2), e1475.
   PubMed Web of Science ®Google Scholar
• 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), 8285.
   PubMed Web of Science ®Google Scholar
• Khushiramani, R., Girisha, S. K., Karunasagar, I., & Karunasagar, I. (2007). Cloning and expression of an outer membrane protein ompTS of Aeromonas hydrophila and study of immunogenicity in fish. Protein Expression and Purification, 51(2), 303–307.
   PubMed Web of Science ®Google Scholar
• Ko, J., Park, H., Heo, L., & Seok, C. (2012). GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Research, 40(W1), W294–W297.
   PubMed Web of Science ®Google Scholar
• Kumar, R., Singh, O. P., Gautam, S., Nylen, S., & Sundar, S. (2014). Enhanced expression of Toll‐like receptors 2 and 4, but not 9, in spleen tissue from patients with visceral leishmaniasis. Parasite Immunology, 36(12), 721–725.
   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(1), 424.
   PubMed Web of Science ®Google Scholar
• Lee, S. J., Shin, S. J., Lee, M. H., Lee, M.-G., Kang, T. H., Park, W. S., … Park, Y.-W. (2014). A potential protein adjuvant derived from Mycobacterium tuberculosis Rv0652 enhances dendritic cells-based tumor immunotherapy. PloS One, 9(8), e104351.
   PubMed Web of Science ®Google Scholar
• Lollini, P.-L., Cavallo, F., Nanni, P., & Forni, G. (2006). Vaccines for tumour prevention. Nature Reviews Cancer, 6(3), 204–216.
   PubMed Web of Science ®Google Scholar
• Lovell, S. C., Davis, I. W., Arendall, W. B., de Bakker, P. I. W., Word, J. M., Prisant, M. G., … Richardson, D. C. (2003). Structure validation by Calpha geometry: Phi, psi and Cbeta deviation. Proteins: Structure, Function, and Bioinformatics, 50(3), 437–450. doi: 10.1002/prot.10286
   PubMed Web of Science ®Google Scholar
• Mahmoodi, S., Nezafat, N., Barzegar, A., Negahdaripour, M., R. Nikanfar, A., Zarghami, N., & Ghasemi, Y. (2016). Harnessing bioinformatics for designing a novel multiepitope peptide vaccine against breast cancer. Current Pharmaceutical Biotechnology, 17(12), 1100–1114.
   PubMed Web of Science ®Google Scholar
• de la Maza, M. S. (2014). Leishmaniasis transmission biology: Role of Promastigote Secretory Gel as a transmission determinant (Doctoral dissertation). London School of Hygiene & Tropical Medicine.
   Google Scholar
• Maurya, R., Kumar, R., Prajapati, V. K., Manandhar, K. D., Sacks, D., Sundar, S., & Nylén, S. (2010). Brief definitive report: Human visceral leishmaniasis is not associated with expansion or accumulation of Foxp3+ CD4 cells in blood or spleen. Parasite Immunology, 32(7), 479–483.
   PubMed Web of Science ®Google Scholar
• Mirza, M., Usman, M., Biuk-Aghai, R. P., & Fong, S. (2016). A modular approach for implementation of honeypots in cyber security. International Journal of Applied Engineering Research, 11(8), 5446–5451.
   Google Scholar
• Narula, A., Pandey, R. K., Khatoon, N., Mishra, A., & Prajapati, V. K. (2018). Excavating chikungunya genome to design B and T cell multi-epitope subunit vaccine using comprehensive immunoinformatics approach to control chikungunya infection. Infection, Genetics and Evolution, 61, 4–15. doi: 10.1016/j.meegid.2018.03.007
   PubMed Web of Science ®Google Scholar
• Negahdaripour, M., Nezafat, N., Eslami, M., Ghoshoon, M. B., Shoolian, E., Najafipour, S., … Ghasemi, Y. (2018). Structural vaccinology considerations for in silico designing of a multi-epitope vaccine. Infection, Genetics and Evolution, 58, 96–109.
   PubMed Web of Science ®Google Scholar
• Nezafat, N., Ghasemi, Y., Javadi, G., Khoshnoud, M. J., & Omidinia, E. (2014). A novel multi-epitope peptide vaccine against cancer: An in silico approach. Journal of Theoretical Biology, 349, 121–134.
   PubMed Web of Science ®Google Scholar
• Nisha, C. M., Kumar, A., Nair, P., Gupta, N., Silakari, C., Tripathi, T., & Kumar, A. (2016). Molecular docking and in silico ADMET study reveals acylguanidine 7a as a potential inhibitor of β-secretase. Advances in Bioinformatics, 2016, 9258578.
   PubMedGoogle Scholar
• Pandey, R. K. (2016). Molecular modeling and virtual screening approach to discover potential antileishmanial inhibitors against ornithine decarboxylase. Combinatorial Chemistry & High Throughput Screening, 19(10), 813–823. doi: 10.2174/1386207319666160907100134
   PubMed Web of Science ®Google Scholar
• Pandey, R., Prajapati, V. K., & Sundar, S. (2016). MicroRNA mediated immune regulation of T helper cell differentiation and plasticity during visceral leishmaniasis infection: A computational approach. International Journal of Infectious Diseases, 45, 374–375.
   Web of Science ®Google Scholar
• Pandey, R. K., Bhatt, T. K., & Prajapati, V. K. (2018). Novel immunoinformatics approaches to design multi-epitope subunit vaccine for malaria by investigating anopheles salivary protein. Scientific Reports, 8(1), 1125. doi: 10.1038/s41598-018-19456-1
   PubMed Web of Science ®Google Scholar
• Pandey, R. K., Narula, A., Naskar, M., Srivastava, S., Verma, P., Malik, R., … Prajapati, V. K. (2016). Exploring dual inhibitory role of febrifugine analogues against Plasmodium utilizing structure-based virtual screening and molecular dynamic simulation. Journal of Biomolecular Structure Dynamics, 35(4), 1–804. doi: 10.1080/07391102.2016.1161560
   PubMed Web of Science ®Google Scholar
• Pandey, R. K., & Prajapati, V. K. (2018). Exploring sand fly salivary proteins to design multi-epitope subunit vaccine to fight against visceral leishmaniasis. Journal of Cell Ular Biochemistry. doi: 10.1002/jcb.26719
   Web of Science ®Google Scholar
• Pandey, R. K., Verma, P., Sharma, D., Bhatt, T. K., Sundar, S., & Prajapati, V. K. (2017). High-throughput virtual screening and quantum mechanics approach to develop imipramine analogues as leads against trypanothione reductase of leishmania. Biomedicine Pharmacotheraphy, 83, 141–152. doi: 10.1016/j.biopha.2016.06.010
   Web of Science ®Google Scholar
• Patronov, A., & Doytchinova, I. (2013). T-cell epitope vaccine design by immunoinformatics. Open Biology, 3(1), 120139.
   PubMed Web of Science ®Google Scholar
• Peng, J., & Xu, J. (2011). RaptorX: Exploiting structure information for protein alignment by statistical inference. Proteins: Structure, Function, and Bioinformatics, 79(S10), 161–171.
   PubMed Web of Science ®Google Scholar
• Prajapati, V. K., & Pandey, R. K. (2017). Recent advances in the chemotherapy of visceral leishmaniasis. In Drug design: Principles and applications (pp. 69–88). New York: Springer.
   Google Scholar
• 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.
   PubMed Web of Science ®Google Scholar
• Roche, P. A., & Furuta, K. (2015). The ins and outs of MHC class II-mediated antigen processing and presentation. Nature Reviews Immunology, 15(4), 203.
   PubMed Web of Science ®Google Scholar
• Roy, S., Basu, S., Datta, A. K., Bhattacharyya, D., Banerjee, R., & Dasgupta, D. (2014). Equilibrium unfolding of cyclophilin from Leishmania donovani: Characterization of intermediate states. International Journal of Biological Macromolecules, 69, 353–360.
   PubMed Web of Science ®Google Scholar
• Saha, S., & Raghava, G. (2006). AlgPred: Prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Research, 34, W202–W209.
   PubMed Web of Science ®Google Scholar
• Schnarwiler, F., Niemann, M., Doiron, N., Harsman, A., Kaser, S., Mani, J., … Schneider, A. (2014). Trypanosomal TAC40 constitutes a novel subclass of mitochondrial β-barrel proteins specialized in mitochondrial genome inheritance. Proceedings of the National Academy of Sciences, 111(21), 7624–7629.
   PubMed Web of Science ®Google Scholar
• 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–W367.
   PubMed Web of Science ®Google Scholar
• Shukla, R., Shukla, H., Sonkar, A., Pandey, T., & Tripathi, T. (2017). Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase. Journal of Biomolecular Structure and Dynamics, 36(8), 2045–2057.
   PubMed Web of Science ®Google Scholar
• Stanley, M., Pinto, L. A., & Trimble, C. (2012). Human papillomavirus vaccines–immune responses. Vaccine, 30, F83–F87.
   PubMed Web of Science ®Google 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. doi: 10.1371/journal.pcbi.1000048
   PubMed Web of Science ®Google Scholar
• Wimley, W. C. (2003). The versatile beta-barrel membrane protein. Current Opinion in Structural Biology, 13(4), 404–411.
   PubMed Web of Science ®Google Scholar