Generic placeholder image

Current Computer-Aided Drug Design

Author(s): Peyman Bemani and Mozafar Mohammadi*

DOI: 10.2174/1573409919666221205122633

DownloadDownload PDF Flyer Cite As
In silico Prediction and Evaluation of Human Parainfluenza Virus-3 CD4+ T Cell Epitopes

Page: [163 - 175] Pages: 13

  • * (Excluding Mailing and Handling)

Abstract

Background: Human parainfluenza viruses type 3 (HPIV-3) through bronchiolitis and pneumonia is a common cause of lower respiratory tract infections. It is the main cause of hospitalization of infants and young children and also one of the main causes of morbidity and mortality in immuno-compromised and transplant patients. Despite many efforts, there is currently no specific anti-HPIV-3 drug or approved vaccine to prevent and control the virus. Identification of HPIV-3 epitopes with the capability of binding to human leukocyte antigen (HLA) class II molecules can be helpful in designing new vaccine candidates against HPIV-3 infection, and also can be useful for the in vitro stimulation and proliferation of HPIV-3-specific T cells for transplant and immunocompromised patients.

Objective: To predict and comprehensively evaluate CD4+T cell epitope (HLA-II binders) from four main HPIV-3 antigens.

Methods: In the present work, we predicted and comprehensively evaluated CD4+T cell epitope (HLA-II binders) from four main HPIV-3 antigens, including fusion protein (F), hemagglutininneuraminidase (HN), nucleocapsid (N) and matrix (M) proteins using bio- and immunoinformatics software. The toxicity, allergenicity, Blast screening and population coverage of the predicted epitopes were evaluated. The binding ability of the final selected epitopes was evaluated via a docking study.

Results: After several filtering steps, including blast screening, toxicity and allergenicity assay, population coverage and docking study, 9 epitopes were selected as candidate epitopes. The selected epitopes showed high population coverage and docking studies revealed a significantly higher binding affinity for the final epitopes in comparison with the negative control peptides.

Conclusion: The final selected epitopes could be useful in designing vaccine candidates and for the treatment of immune-compromised individuals and patients with transplantation.

Graphical Abstract

[1]
Cusick, M.F.; Libbey, J.E.; Fujinami, R.S. Molecular mimicry as a mechanism of autoimmune disease. Clin. Rev. Allergy Immunol., 2012, 42(1), 102-111.
[http://dx.doi.org/10.1007/s12016-011-8294-7] [PMID: 22095454]
[2]
Schomacker, H.; Schaap-Nutt, A.; Collins, P.L.; Schmidt, A.C. Pathogenesis of acute respiratory illness caused by human parainfluenza viruses. Curr. Opin. Virol., 2012, 2(3), 294-299.
[http://dx.doi.org/10.1016/j.coviro.2012.02.001] [PMID: 22709516]
[3]
Moscona, A. Entry of parainfluenza virus into cells as a target for interrupting childhood respiratory disease. J. Clin. Invest., 2005, 115(7), 1688-1698.
[http://dx.doi.org/10.1172/JCI25669] [PMID: 16007245]
[4]
McLaughlin, L.P.; Lang, H.; Williams, E.; Wright, K.E.; Powell, A.; Cruz, C.R.; Colberg-Poley, A.M.; Barese, C.; Hanley, P.J.; Bollard, C.M.; Keller, M.D. Human parainfluenza virus-3 can be targeted by rapidly ex vivo expanded T lymphocytes. Cytotherapy, 2016, 18(12), 1515-1524.
[http://dx.doi.org/10.1016/j.jcyt.2016.08.010] [PMID: 27692559]
[5]
Aguayo-Hiraldo, P.I.; Arasaratnam, R.J.; Tzannou, I.; Kuvalekar, M.; Lulla, P.; Naik, S.; Martinez, C.A.; Piedra, P.A.; Vera, J.F.; Leen, A.M. Characterizing the cellular immune response to parainfluenza virus 3. J. Infect. Dis., 2017, 216(2), 153-161.
[http://dx.doi.org/10.1093/infdis/jix203] [PMID: 28472480]
[6]
Greiff, D.R.L.; Patterson-Robert, A.; Blyth, C.C.; Glass, K.; Moore, H.C. Epidemiology and seasonality of human parainfluenza serotypes 1‐3 in Australian children. Influenza Other Respir. Viruses, 2021, 15(5), 661-669.
[http://dx.doi.org/10.1111/irv.12838] [PMID: 33491337]
[7]
Olivares, F.; Salinas, M.; Soto, A.; Dabanch, J.; Fica, A. Severe acute disseminated encephalomyelitis associated with parainfluenza 3 infection: Case report. Rev. Chilena Infectol., 2015, 32(4), 476-481.
[http://dx.doi.org/10.4067/S0716-10182015000500019] [PMID: 26436798]
[8]
Arisoy, E.S.; Demmler, G.J.; Thakar, S.; Doerr, C. Meningitis due to parainfluenza virus type 3: report of two cases and review. Clin. Infect. Dis., 1993, 17(6), 995-997.
[http://dx.doi.org/10.1093/clinids/17.6.995] [PMID: 8110958]
[9]
Liu, W.K.; Chen, D.H.; Tan, W.P.; Qiu, S.Y.; Xu, D.; Zhang, L.; Gu, S.J.; Zhou, R.; Liu, Q. Paramyxoviruses respiratory syncytial virus, parainfluenza virus, and human metapneumovirus infection in pediatric hospitalized patients and climate correlation in a subtropical region of southern China: a 7-year survey. Eur. J. Clin. Microbiol. Infect. Dis., 2019, 38(12), 2355-2364.
[http://dx.doi.org/10.1007/s10096-019-03693-x] [PMID: 31489496]
[10]
Schmidt, A.C.; Schaap-Nutt, A.; Bartlett, E.J.; Schomacker, H.; Boonyaratanakornkit, J.; Karron, R.A.; Collins, P.L. Progress in the development of human parainfluenza virus vaccines. Expert Rev. Respir. Med., 2011, 5(4), 515-526.
[http://dx.doi.org/10.1586/ers.11.32] [PMID: 21859271]
[11]
Kobayashi, H.; Iwatsuki-Horimoto, K.; Kiso, M.; Uraki, R.; Ichiko, Y.; Takimoto, T.; Kawaoka, Y. A replication-incompetent influenza virus bearing the HN glycoprotein of human parainfluenza virus as a bivalent vaccine. Vaccine, 2013, 31(52), 6239-6246.
[http://dx.doi.org/10.1016/j.vaccine.2013.10.029] [PMID: 24144478]
[12]
Ogonek, J.; Kralj Juric, M.; Ghimire, S.; Varanasi, P.R.; Holler, E.; Greinix, H.; Weissinger, E. Immune Reconstitution after Allogeneic Hematopoietic Stem Cell Transplantation. Front. Immunol., 2016, 7, 507.
[http://dx.doi.org/10.3389/fimmu.2016.00507] [PMID: 27909435]
[13]
Vilchez, R.A.; McCurry, K.; Dauber, J.; Iacono, A.; Keenan, R.; Zeevi, A.; Griffith, B.; Kusne, S. The epidemiology of parainfluenza virus infection in lung transplant recipients. Clin. Infect. Dis., 2001, 33(12), 2004-2008.
[http://dx.doi.org/10.1086/324348] [PMID: 11702289]
[14]
DeFabritus, A.M.; Riggio, R.R.; David, D.S.; Senterfit, L.B.; Cheigh, J.S.; Stenzel, K.H. Parainfluenza type 3 in a transplant unit. JAMA, 1979, 241(4), 384-386.
[http://dx.doi.org/10.1001/jama.1979.03290300026021] [PMID: 214588]
[15]
Herzog, K.D.; Dunn, S.P.; Langham, M.R., Jr; Marmon, L.M. Association of parainfluenza virus type 3 infection with allograft rejection in a liver transplant recipient. Pediatr. Infect. Dis. J., 1989, 8(8), 534-536.
[http://dx.doi.org/10.1097/00006454-198908000-00014] [PMID: 2549495]
[16]
Huang, Y.; Niu, B.; Gao, Y.; Fu, L.; Li, W. CD-HIT Suite: a web server for clustering and comparing biological sequences. Bioinformatics, 2010, 26(5), 680-682.
[http://dx.doi.org/10.1093/bioinformatics/btq003] [PMID: 20053844]
[17]
Sievers, F.; Wilm, A.; Dineen, D.; Gibson, T.J.; Karplus, K.; Li, W.; Lopez, R.; McWilliam, H.; Remmert, M.; Söding, J.; Thompson, J.D.; Higgins, D.G. Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol., 2011, 7(1), 539.
[http://dx.doi.org/10.1038/msb.2011.75] [PMID: 21988835]
[18]
Garcia-Boronat, M.; Diez-Rivero, C.M.; Reinherz, E.L.; Reche, P.A. PVS: a web server for protein sequence variability analysis tuned to facilitate conserved epitope discovery. Nucleic Acids Res., 2008, 36(Web Server), W35-W41.
[http://dx.doi.org/10.1093/nar/gkn211] [PMID: 18442995]
[19]
Doytchinova, I.A.; Flower, D.R. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics, 2007, 8(1), 4.
[http://dx.doi.org/10.1186/1471-2105-8-4] [PMID: 17207271]
[20]
Magnan, C.N.; Zeller, M.; Kayala, M.A.; Vigil, A.; Randall, A.; Felgner, P.L.; Baldi, P. High-throughput prediction of protein antigenicity using protein microarray data. Bioinformatics, 2010, 26(23), 2936-2943.
[http://dx.doi.org/10.1093/bioinformatics/btq551] [PMID: 20934990]
[21]
Jensen, K.K.; Andreatta, M.; Marcatili, P.; Buus, S.; Greenbaum, J.A.; Yan, Z.; Sette, A.; Peters, B.; Nielsen, M. Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology, 2018, 154(3), 394-406.
[http://dx.doi.org/10.1111/imm.12889] [PMID: 29315598]
[22]
Singh, H.; Raghava, G.P.S. ProPred: prediction of HLA-DR binding sites. Bioinformatics, 2001, 17(12), 1236-1237.
[http://dx.doi.org/10.1093/bioinformatics/17.12.1236] [PMID: 11751237]
[23]
Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol., 1990, 215(3), 403-410.
[http://dx.doi.org/10.1016/S0022-2836(05)80360-2] [PMID: 2231712]
[24]
Dimitrov, I.; Naneva, L.; Doytchinova, I.; Bangov, I. AllergenFP: allergenicity prediction by descriptor fingerprints. Bioinformatics, 2014, 30(6), 846-851.
[http://dx.doi.org/10.1093/bioinformatics/btt619] [PMID: 24167156]
[25]
Gupta, S.; Kapoor, P.; Chaudhary, K.; Gautam, A.; Kumar, R.; Raghava, G.P.S. In silico approach for predicting toxicity of peptides and proteins. PLoS One, 2013, 8(9), e73957.
[http://dx.doi.org/10.1371/journal.pone.0073957] [PMID: 24058508]
[26]
Bui, H.H.; Sidney, J.; Dinh, K.; Southwood, S.; Newman, M.J.; Sette, A. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics, 2006, 7(1), 153.
[http://dx.doi.org/10.1186/1471-2105-7-153] [PMID: 16545123]
[27]
Lee, H.; Heo, L.; Lee, M.S.; Seok, C. GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization. Nucleic Acids Res., 2015, 43(W1), W431-W435.
[http://dx.doi.org/10.1093/nar/gkv495] [PMID: 25969449]
[28]
Weng, G.; Wang, E.; Wang, Z.; Liu, H.; Zhu, F.; Li, D.; Hou, T. HawkDock: a web server to predict and analyze the protein–protein com-plex based on computational docking and MM/GBSA. Nucleic Acids Res., 2019, 47(W1), W322-W330.
[http://dx.doi.org/10.1093/nar/gkz397] [PMID: 31106357]
[29]
Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera?A visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612.
[http://dx.doi.org/10.1002/jcc.20084] [PMID: 15264254]
[30]
Schlundt, A.; Günther, S.; Sticht, J.; Wieczorek, M.; Roske, Y.; Heinemann, U.; Freund, C. Peptide linkage to the α-subunit of MHCII creates a stably inverted antigen presentation complex. J. Mol. Biol., 2012, 423(3), 294-302.
[http://dx.doi.org/10.1016/j.jmb.2012.07.008] [PMID: 22820093]
[31]
Parry, C.S.; Gorski, J.; Stern, L.J. Crystallographic structure of the human leukocyte antigen DRA, DRB3*0101: models of a directional alloimmune response and autoimmunity. J. Mol. Biol., 2007, 371(2), 435-446.
[http://dx.doi.org/10.1016/j.jmb.2007.05.025] [PMID: 17583734]
[32]
Gerstner, C.; Dubnovitsky, A.; Sandin, C.; Kozhukh, G.; Uchtenhagen, H.; James, E.A.; Rönnelid, J.; Ytterberg, A.J.; Pieper, J.; Reed, E.; Tandre, K.; Rieck, M.; Zubarev, R.A.; Rönnblom, L.; Sandalova, T.; Buckner, J.H.; Achour, A.; Malmström, V. Functional and Structural Characterization of a Novel HLA-DRB1*04:01-Restricted α-Enolase T Cell Epitope in Rheumatoid Arthritis. Front. Immunol., 2016, 7, 494.
[http://dx.doi.org/10.3389/fimmu.2016.00494] [PMID: 27895642]
[33]
Ting, Y.T.; Petersen, J.; Ramarathinam, S.H.; Scally, S.W.; Loh, K.L.; Thomas, R.; Suri, A.; Baker, D.G.; Purcell, A.W.; Reid, H.H.; Rossjohn, J. The interplay between citrullination and HLA-DRB1 polymorphism in shaping peptide binding hierarchies in rheumatoid arthritis. J. Biol. Chem., 2018, 293(9), 3236-3251.
[http://dx.doi.org/10.1074/jbc.RA117.001013] [PMID: 29317506]
[34]
Galperin, M.; Farenc, C.; Mukhopadhyay, M.; Jayasinghe, D.; Decroos, A.; Benati, D.; Tan, L.L.; Ciacchi, L.; Reid, H.H.; Rossjohn, J.; Chakrabarti, L.A.; Gras, S. CD4+ T cell-mediated HLA class II cross-restriction in HIV controllers. Sci. Immunol., 2018, 3(24), eaat0687.
[http://dx.doi.org/10.1126/sciimmunol.aat0687] [PMID: 29884618]
[35]
Ooi, J.D.; Petersen, J.; Tan, Y.H.; Huynh, M.; Willett, Z.J.; Ramarathinam, S.H.; Eggenhuizen, P.J.; Loh, K.L.; Watson, K.A.; Gan, P.Y.; Alikhan, M.A.; Dudek, N.L.; Handel, A.; Hudson, B.G.; Fugger, L.; Power, D.A.; Holt, S.G.; Coates, P.T.; Gregersen, J.W.; Purcell, A.W.; Holdsworth, S.R.; La Gruta, N.L.; Reid, H.H.; Rossjohn, J.; Kitching, A.R. Dominant protection from HLA-linked autoimmunity by antigen-specific regulatory T cells. Nature, 2017, 545(7653), 243-247.
[http://dx.doi.org/10.1038/nature22329] [PMID: 28467828]
[36]
Lang, H.L.E.; Jacobsen, H.; Ikemizu, S.; Andersson, C.; Harlos, K.; Madsen, L.; Hjorth, P.; Sondergaard, L.; Svejgaard, A.; Wucherpfen-nig, K.; Stuart, D.I.; Bell, J.I.; Jones, E.Y.; Fugger, L. A functional and structural basis for TCR cross-reactivity in multiple sclerosis. Nat. Immunol., 2002, 3(10), 940-943.
[http://dx.doi.org/10.1038/ni835] [PMID: 12244309]
[37]
Hutspardol, S.; Essa, M.; Richardson, S.; Schechter, T.; Ali, M.; Krueger, J.; Fujii, H.; Egeler, R.M.; Gassas, A. Significant transplantation-related mortality from respiratory virus infections within the first one hundred days in children after hematopoietic stem cell transplantation. Biol. Blood Marrow Transplant., 2015, 21(10), 1802-1807.
[http://dx.doi.org/10.1016/j.bbmt.2015.06.015] [PMID: 26117558]
[38]
Chemaly, R.F.; Shah, D.P.; Boeckh, M.J. Management of respiratory viral infections in hematopoietic cell transplant recipients and patients with hematologic malignancies. Clin. Infect. Dis., 2014, 59(Suppl. 5), S344-S351.
[http://dx.doi.org/10.1093/cid/ciu623] [PMID: 25352629]
[39]
Henrickson, K.J. Parainfluenza Viruses. Clin. Microbiol. Rev., 2003, 16(2), 242-264.
[http://dx.doi.org/10.1128/CMR.16.2.242-264.2003] [PMID: 12692097]
[40]
Khan, M.K.; Zaman, S.; Chakraborty, S.; Chakravorty, R.; Alam, M.M.; Bhuiyan, T.R.; Rahman, M.J.; Fernández, C.; Qadri, F.; Seraj, Z.I. In silico predicted mycobacterial epitope elicits in vitro T-cell responses. Mol. Immunol., 2014, 61(1), 16-22.
[http://dx.doi.org/10.1016/j.molimm.2014.04.009] [PMID: 24853589]
[41]
Escalona, E.; Sáez, D.; Oñate, A. immunogenicity of a multi-epitope dna vaccine encoding epitopes from Cu-Zn superoxide dismutase and open reading Frames of Brucella abortus in mice. Front. Immunol., 2017, 8, 125.
[http://dx.doi.org/10.3389/fimmu.2017.00125] [PMID: 28232837]
[42]
Yang, Y.; Sun, W.; Guo, J.; Zhao, G.; Sun, S.; Yu, H.; Guo, Y.; Li, J.; Jin, X.; Du, L.; Jiang, S.; Kou, Z.; Zhou, Y. In silico design of a DNA-based HIV-1 multi-epitope vaccine for Chinese populations. Hum. Vaccin. Immunother., 2015, 11(3), 795-805.
[http://dx.doi.org/10.1080/21645515.2015.1012017] [PMID: 25839222]
[43]
Díaz, I.; Pujols, J.; Ganges, L.; Gimeno, M.; Darwich, L.; Domingo, M.; Mateu, E. In silico prediction and ex vivo evaluation of potential T-cell epitopes in glycoproteins 4 and 5 and nucleocapsid protein of genotype-I (European) of porcine reproductive and respiratory syndrome virus. Vaccine, 2009, 27(41), 5603-5611.
[http://dx.doi.org/10.1016/j.vaccine.2009.07.029] [PMID: 19646408]
[44]
Koutsoni, O.S.; Routsias, J.G.; Kyriazis, I.D.; Barhoumi, M.; Guizani, I.; Tsakris, A.; Dotsika, E. In silico analysis and in vitro evaluation of immunogenic and immunomodulatory properties of promiscuous peptides derived from Leishmania infantum eukaryotic initiation factor. Bioorg. Med. Chem., 2017, 25(21), 5904-5916.
[http://dx.doi.org/10.1016/j.bmc.2017.07.013] [PMID: 28974324]
[45]
Gutiérrez, A.H.; Loving, C.; Moise, L.; Terry, F.E.; Brockmeier, S.L.; Hughes, H.R.; Martin, W.D.; De Groot, A.S. In vivo validation of predicted and conserved T cell epitopes in a swine influenza model. PLoS One, 2016, 11(7), e0159237.
[http://dx.doi.org/10.1371/journal.pone.0159237] [PMID: 27411061]
[46]
Godkin, A.J.; Smith, K.J.; Willis, A.; Tejada-Simon, M.V.; Zhang, J.; Elliott, T.; Hill, A.V.S. Naturally processed HLA class II peptides reveal highly conserved immunogenic flanking region sequence preferences that reflect antigen processing rather than peptide-MHC interactions. J. Immunol., 2001, 166(11), 6720-6727.
[http://dx.doi.org/10.4049/jimmunol.166.11.6720] [PMID: 11359828]
[47]
Rammensee, H.G.; Friede, T.; Stevanović, S. MHC ligands and peptide motifs: first listing. Immunogenetics, 1995, 41(4), 178-228.
[http://dx.doi.org/10.1007/BF00172063] [PMID: 7890324]
[48]
Jiang, W.; Boder, E.T. High-throughput engineering and analysis of peptide binding to class II MHC. Proc. Natl. Acad. Sci. USA, 2010, 107(30), 13258-13263.
[http://dx.doi.org/10.1073/pnas.1006344107] [PMID: 20622157]
[49]
Racle, J.; Michaux, J.; Rockinger, G.A.; Arnaud, M.; Bobisse, S.; Chong, C.; Guillaume, P.; Coukos, G.; Harari, A.; Jandus, C.; Bassani-Sternberg, M.; Gfeller, D. Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes. Nat. Biotechnol., 2019, 37(11), 1283-1286.
[http://dx.doi.org/10.1038/s41587-019-0289-6] [PMID: 31611696]
[50]
Dhanda, S.K.; Karosiene, E.; Edwards, L.; Grifoni, A.; Paul, S.; Andreatta, M.; Weiskopf, D.; Sidney, J.; Nielsen, M.; Peters, B.; Sette, A. Predicting HLA CD4 immunogenicity in human populations. Front. Immunol., 2018, 9, 1369.
[http://dx.doi.org/10.3389/fimmu.2018.01369] [PMID: 29963059]