A NOVEL TETRAVALENT RECOMBINANT ENVELOPE DOMAIN III VACCINE AGAINST DENGUE: AN IN SILICO APPROACH
HTML Full TextA NOVEL TETRAVALENT RECOMBINANT ENVELOPE DOMAIN III VACCINE AGAINST DENGUE: AN IN SILICO APPROACH
Ajit Kulkarni1*, Pramod Shinde 2, Sweta Kothari1, Rajas Warke1, Abhay Chowdhary1 and Ranjana A. Deshmukh1
Department of Virology 1, Haffkine Institute for Training, Research and Testing, Acharya Donde Marg, Parel, Mumbai-400012 India
Department of Bioinformatics 2, Guru Nanak Institute of Research and Development, Guru Nanak Khalsa College, Matunga, Mumbai-400019, India
ABSTRACT: The global rise in dengue cases is a major public health concern in terms of morbidity and mortality. The recent study reports 390 million dengue infections annually of which 96 million infections becomes clinically or subclinically severe. Therefore, development of an effective tetravalent vaccine against dengue is a top priority. Dengue envelope domain III is a surface exposed protein; involved in host cell binding and containing multiple, serotype-specific and subcomplex-specific neutralizing epitopes, thus becomes an ideal target for vaccine development. The rapid growth in bioinformatics or immunoinformatics area in terms of development of sophisticated tools assists researchers to predict immunodominant epitopes and study various characteristics of the predicted vaccine model. The combination of computer-aided or in silico methods and experimental methods are useful tools to address complex problems such as deciphering immune responses and vaccine design. In the present study we aim to develop a recombinant tetravalent vaccine model using bioinformatics tools of our vaccine candidate containing envelope domain III of all four dengue serotypes (GenBank ID: KF 855114) and study its role and characteristics with its sequence and structure based features. In silico approach showed that our vaccine is stable, properly folded, antigenic and having multiple predicted B and T cell epitopes that are known to be immunogenic. Also the docking studies using a mouse monoclonal antibody (4E11), which neutralizes all four DENV serotypes, predicted a favourable and stable protein-protein interaction model. Further studies are underway to test its immunogenicity and efficacy in mice.
Keywords: |
Dengue, Envelop Domain III, Vaccine, Immuno-Informatics
INTRODUCTION: Dengue virus (DENV) is a flavivirus causing major threat to health in tropical countries around the world. DENV is endemic in more than 125 countries 1. Annually 390 million people get infected by dengue of which 96 million cases have clinical or subclinical severity 2. DENV are maintained in nature in two cycles namely a sylvatic cycle and an urban cycle.
A sylvatic cycle is exist between non-human primates and arboreal Aedes mosquitoes, while an urban cycle is maintained between humans and domestic, peridomestic Aedes aegypti and Aedes albopictus mosquito vectors 3.
Four DENV serotypes (DENV-1 to 4) are capable of causing self-limited dengue fever (DF) or even life-threatening dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). The host immune system plays a significant role in dengue infection as well as in protection. The primary dengue infection provides lifelong protection to the homologous serotype, while secondary dengue infection with heterologous serotype causes severe complications like DHF/ DSS 4. Controlling severe life-threatening DENV infections (DHF/ DSS) are presently depends on modern supportive intensive care as there is no specific treatment (antivirals) or licensed vaccine present in the market to date 5.
Immunity to DENV infection is primarily mediated by neutralizing antibodies 6, 7. The role of T cells in protection as well as in pathogenesis of dengue has also been documented 8, 9. Envelope protein is the major protective antigen in DENV infection as it is exposed to the immune system and most of the neutralizing antibodies are directed against it 6. Most of the vaccine strategies focus on inducing neutralizing antibodies against this antigen10-13.
It has been well documented that most of the epitopes that are multiple, serotype-specific and subcomplex-specific elicit only virus-neutralizing monoclonal antibodies, having low potential for inducing cross-reactive antibodies to heterologous dengue serotypes located in domain III of envelope protein (EDIII) 10; also it is exposed to the surface and thus becomes the primary target for antibody-mediated neutralization. It is also involved in host cell binding 14. So neutralizing antibodies produced against EDIII may block the entry of the virus into the cell, thus become the ideal target for vaccine development 15.
Development of safe and effective dengue vaccine is a challenging task and has been hampered mainly because of the concern that cross reactive immunological memory elicited by a vaccine candidate could increase the risk of DHF and DSS as secondary heterologous DENV infection could lead to antibody dependant enhancement (ADE) and cytokine storm/ Tsunami that is known to accelerate DENV pathogenesis 8-9. Therefore, a safe and effective DENV vaccine must be tetravalent and induce balanced protective immune response against all four serotypes.
Bioinformatics or immunoinformatics is an interdisciplinary area involving chemical, biological and computational sciences. The bioinformatics and immunoinformatics fields are emerging rapidly in terms of development of various sophisticated bioinformatics tools that facilitate the process of designing vaccine candidate by assisting researchers in identifying the immunodominant T-cell and B-cell epitopes or immunological ‘hot-spots’, the most crucial step in vaccine design. In silico methods uses variety of statistical and machine learning approaches to study the various characteristics of predicted vaccine model. Experimental methods in combination with in silico methods are useful tools to address complex problems such as deciphering immune responses and vaccine design16, 17.
In the present study we aim to develop a recombinant tetravalent vaccine model using bioinformatics tools of our vaccine candidate containing EDIII of all four dengue serotypes (GenBank ID: KF 855114)18 and study its role and characteristics with its sequence and structure based features.
MATERIALS AND METHODS:
Recombinant tetravalent protein sequence:
We used the protein sequence of our recombinant tetravalent EDIII based dengue vaccine construct (GenBank ID: KF 855114)18 to predict the structure, and study various characteristics using bioinformatics tools see Fig. 1.
Immuno-informatics analysis with B and T cell epitope prediction:
We used IEDB sources to screen known epitopes against the tetravalent sequence to get maximum number of antigenic epitopes that are able to induce both the B-cell and T-cell response. B cell and T cell prediction tools from IEDB (www.iedb.org)19 were used to screen all reported epitopes in literature and further all the epitopes were manually inspected with respect to its presence in desire region, then aligned and confirmed using local Perl scripts and Emboss utilities see Table 1 and 2.
Primary sequence analysis and Biological activity prediction:
Various physico-chemical parameters like amino acid composition, theoretical pI, instability index, in vitro half-life, aliphatic index, grand average of hydropathicity (GRAVY) and molecular weight were evaluated using BioPerl scripts see Table 3 and Fig.2. Sequence directed biological activity and molecular function ontology predicted with Predict Protein (https://www.predictprotein.org/) 20 see Fig.3.
Antigenicity and allergenicity evaluation:
ANTIGENpro (http://scratch. proteomics.ics.uci. edu/), and VaxiJen v2.0 server were used to predict protein antigenicity. These are alignment independent approaches based on statistical approaches between principal amino acid properties. We used AlgPred web server (http://www.imtech.res.in/raghava/algpred/) in order to predict protein allergenicity 21 see Table 3.
Vaccine features:
Secondary structure prediction:
Secondary structure of recombinant tetravalent EDIII protein was predicted using secondary structure prediction utility at I-TASSER (zhanglab.ccmb.med.umich.edu/I-TASSER)22 and ProCheck (www.ebi.ac.uk/thornton-srv/ software/ PROCHECK) see Fig. 4.
Protein structure modeling:
Recombinant tetravalent sequence was submitted to I-TASSER. It generates full length model of proteins by excising continuous fragments from threading alignments and then reassembling them using replica-exchanged Monte Carlo simulations23 see Fig.5A.
Tertiary structure refinement:
As the sequence of tetravalent vaccine is the product of EDIII from different DENV serotypes, we selected homology and threading approach for protein tertiary structure modeling. The critical steps of structure refinement was specified and modeled by GalaxyLoop (http://galaxy.seoklab. org/) 22. The structure optimization of the model was performed using stepwise and direct energy minimization of knowledge based potential of mean force and stereochemistry correction see Fig. 5B.
Tertiary structure validation:
In order to find the potential errors in initial 3D models, ProSA-web at (https://prosa.services.came. sbg.ac.at/prosa.php) was used 24. The residue-by-residue stereochemical qualities of models were validated by Ramachandran plot obtained from RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php) see Fig. 5C and D and Table 4.
Ligand binding site prediction and protein- protein interaction study:
Protein-protein interaction was studied using Zdock server (http: //zdock. umassmed.edu/) 25. Interpolated partial charge surfaces and hydrophobic patches of vaccine were assessed by stand alone softwares viz. Accelerys Discovery Studio 4.5 (Accelrys Inc) see Fig. 6.
Data validation:
To predict potential B-cell and T-cell epitopes several servers were used. IEDB sources are using data from more than 15 locations and given more than 1000 epitope sequences as hits from all DENV serotypes. All the hits were then manually inspected with local Perl scripts and using Emboss services with different thresholds and scores. The shortlisted data is provided in Table 1 and 2.
RESULTS AND DISCUSSION:
Vaccination is an important global strategy for controlling the number of clinically significant DENV infections. A recombinant DNA vaccine against flaviviruses becomes an attractive and promising approach in order to understand the important immunodominant epitopes involved in protection. Furthermore, several advantages like simplicity of production, safety, target specificity, induction of both humoral and cellular immune responses and success in preclinical models has attracted global attention26-29.
Recombinant tetravalent protein sequence:
In the present study we analyzed various parameters of our dengue vaccine construct using bioinformatics tools. The protein sequence of our ED III based recombinant tetravalent dengue vaccine construct (GenBank Accession Number: KF855114)18 has been shown in Fig. 1.
The predicted sequence shows an extracellular involvement. This feature has importance in terms of exposure of epitopes to immune system to induce an immune response as EDIII contains multiple, serotype-specific and subcomplex-specific epitopes that are dominant neutralizine determinants having low potential for inducing cross-reactive antibodies to heterologous dengue serotypes. Also it is exposed and accessible on virion surface, and involved in host cell receptor binding.10, 14, 15
FIGURE 1: (A) SEQUENCE OF RECOMBINANT TETRAVALENT EDIII PROTEIN- CONSTRUCTED USING CLONING OF EDIII FROM DENV-1 TO 4 INTO A PVAC1-MCS MAMMALIAN EXPRESSION VECTOR (RESIDUES SHOWN YELLOW ARE FROM DENV-1, GREEN FROM DENV-2, BLUE FROM DENV-3, PINK FROM DENV-4, AND NON HIGHLIGHTED SEQUENCES ARE VECTOR SEQUENCES) (B) RECOMBINANT TETRAVALENT EDIII PREDICTED TO BE HAVING EXTRACELLULAR INVOLVEMENT AND HAVING SIGNAL PEPTIDE FROM 1 TO 25 AMINO ACIDS
B and T cell epitopes prediction:
B and T cell epitopes were predicted using bioinformatics tools in our novel recombinant tetravalent EDIII based dengue vaccine with known published B cell (neutralizing) and T cell (CD4+, CD8+ CTL) epitope data. The predicted epitopes were restricted to EDIII as our vaccine construct is based on EDIII of DENV-1 to 4 serotypes. Also the prediction is based on the known available data which is mostly focused on DENV-2, and the information regarding B cell (neutralizing) and T cell (CD4+, CD8+ CTL) epitopes present in EDIII of other DENV serotypes is limited. Table 1 and 2 summarizes the predicted B and T cell epitopes that are known to be neutralizing and CD4+ or CD8+ CTL epitopes respectively.
TABLE 1: B-CELL EPITOPES PREDICTED USING IEDB RESOURCES CONSIDERING B CELL RESPONSE ASSAYS
Sr. No. | Start-end position | Epitope sequence | Sr. No. | Start-end position | Epitope sequence |
1 | 124-135 | SYSMCTGKFKVV | 20 | 176-181 | RLITVN |
2 | 128- 159 | CTGKFKIVKEIAETQHGTIVIRVQYEGDGSPC | 21 | 177-182 | LITVNP |
3 | 135-144 | VKEIAETQHG | 22 | 177-185 | LITVNPIVT |
4 | 138-146 | IAETQHGTI | 23 | 178-194 | ITVNPIVTEKDSPVNIE |
5 | 143-148 | HGTIVI | 24 | 187-214 | KDSPVNIEAEPPFGDSYIIIGVEPGQLK |
6 | 144-149 | GTIVIR | 25 | 198-203 | PFGDSY |
7 | 144-154 | GTIVIRVQYEG | 26 | 198-209 | PFGDSYIIIGVE |
8 | 145-150 | TIVIRV | 27 | 199-204 | FGDSYI |
9 | 149-154 | RVQYEG | 28 | 200-205 | GDSYII |
10 | 150-161 | VQYEGDGSPCKI | 29 | 201-206 | DSYIII |
11 | 159-177 | CKIPFEIMDLEKRHVLGRL | 30 | 202-207 | SYIIIG |
12 | 170-175 | KRHVLG | 31 | 204-209 | IIIGVE |
13 | 171-176 | RHVLGR | 32 | 212-217 | QLKLNW |
14 | 171-182 | RHVLGRLITVNP | 33 | 212-218 | QLKLNWF |
15 | 171-185 | RHVLGRLITVNPIVT | 34 | 212-223 | QLKLNWFKKGSS |
16 | 172-177 | HVLGRL | 35 | 213-218 | LKLNWF |
17 | 174-179 | LGRLIT | 36 | 214-225 | KLNWFKKGSSIGQ |
18 | 175-182 | GRLITVNP | 37 | 219-226 | KKGSSIGM |
19 | 175-185 | GRLITVNPIVT |
TABLE 2: T-CELL EPITOPES PREDICTED USING IEDB RESOURCES CONSIDERING T CELL RESPONSE ASSAYS
Sr. No. | Start-end position | Epitope sequence |
1. | 108-120 | SSIGKMFEATARG |
2. | 157-172 | SPCKIPFEIMDLEKRH |
3. | 159-177 | CKIPFEIMDLEKRHVLGRL |
4. | 163-185 | FEIMDLEKRHVLGRLITVNPIVT |
5. | 178-194 | ITVNPIVTEKDSPVNIE |
6. | 188-194 | ITVNPIVTEKDSPVNIE |
7. | 234-248 | SYAMCTNTFVLKKEV |
8. | 239-253 | TNTFVLKKEVSETQH |
9. | 244-258 | LKKEVSETQHGTILV |
10. | 254-268 | GTILVKVEYKGEDAP |
11. | 304-318 | EAEPPFGESNIVIGI |
Thus our predicted vaccine model shall induce both B cell and T cell immune responses, which further need to be evaluated for immunogenicity and efficacy studies in laboratory animals.
Analysis of various physico-chemical parameters of recombinant tetravalent dengue vaccine:
Various physico-chemical parameters of recombinant tetravalent dengue vaccine are given in Table 3.
TABLE 3: PHYSICO-CHEMICAL PARAMETERS OF RECOMBINANT TETRAVALENT DENGUE VACCINE
Results: Property | Value | |
No. of amino acids | 466 | |
Molecular weight (Da) | 5 1 0 4 5. 1 | |
Theoretical pI | 7.95 | |
Negatively charged residuse (Asp+Glu) | 52 | |
Positively residue (Arg+lys) | 54 | |
Instability index | 35.98 | |
Extinction coefficient (M-1cm-1) at 280nm | 0.947 | |
Grand Average of hydropathicity (GRAVY) | - 0.114 | |
Half Life in mammalian reticulocytes (in vitro) | 30 hours | |
Vaccine antigenicity | ANTIGENpro | 0.73 |
VaxiJen | 0.64 |
Negatively charged residue (Asp+Glu) and positively charged residue (Arg+lys) charged were equally distributed in the recombinant vaccine suggesting its stability with respect to its electrical charge distribution. The instability index is used to determine the stability of protein and it was found to be 35.98 describing its probable stability. Extinction coefficient found to be 0.947 which is closer to 1 showing the greatest extent of purity which is a very important aspect in commercial vaccine production.
The Window position values shown on the x-axis of the graph reflect the average hydropathy of the entire window, with the corresponding amino acid as the middle element of that window peaks with scores greater than 1.8 (red line ) indicated possible transmembrane and surface protein regions. The transmembrane regions were found be at 10-18, 223-240, and 438-458 amino acid positions (see Fig.2. Also, GRAVY value found to be -0.114 indicating the hydrophilicity of the vaccine for its suitability intended for vaccine route selection where hydrophilicity is preferred. Half-life was estimated to be 30 h in mammalian reticulocytes showing its increasing bioavailability and slow enzymatic degradation during systemic circulation.
The antigenicity of vaccine found to be 0.73 and 0.64 with ANTIGENpro and VaxiJen to servers suggesting the binding specificity with a group of certain products that have adaptive immunity (T and B cell receptors). The peptide composition was also predicted to be non-allergen using Hybrid Approach (SVMc+IgE epitope+ARPs BLAST+MAST) of Alg Pred. The biological role of recombinant was predicted to be in viral life cycle, viral genome replication and RNA- dependant transcription. Also, molecular function ontology predicted its activities in protein binding and other activities see Fig. 3. These activities are very essential in predicting the activities of recombinant construct as a vaccine.
FIG. 2: KYTE DOOLITTLE HYDROPATHY PLOT SHOWING PEAKS WITH SCORES NEARER AND GREATER THAN 1.8 (RED LINE) INDICATE POSSIBLE TRANSMEMBRANE REGIONS FOUND TO BE AT 10-18, 223-240, 438-458. (THE WINDOW POSITION VALUES SHOWN ON THE X-AXIS OF THE GRAPH REFLECT THE AVERAGE HYDROPATHY OF THE ENTIRE WINDOW, WITH THE CORRESPONDING AMINO ACID AS THE MIDDLE ELEMENT OF THAT WINDOW)
FIG.3: CONNECTOGRAM OF CONSERVED ACTIVITIES FOR TETRAVALENT DENGUE VACCINE SHOWING (A) BIOLOGICAL ACTIVITY (B) MOLECULAR FUNCTION ONTOLOGY PREDICTED WITH PREDICTPROTEIN |
Secondary structure of recombinant tetravalent vaccine was predicted using PSIPRED. It showed around 43% of amino acids involved in formation of beta sheets, 48% of amino acids involved in coil formation and remaining amino acids involved in formation of alpha helix, confirming the ability of recombinant tetravalent vaccine in its structure formation see Fig. 4.
FIG. 4: GRAPHICAL VIEW FOR SECONDARY STRUCTURE OF RECOMBINANT TETRAVALENT EDIII DENGUE VACCINE SHOWING RESIDUES PREDICTED TO BE INVOLVED IN C: COILS, E: SHEET, H: HELIX REGIONS PREDICTED USING PSIPRED
Tertiary structure of protein for recombinant tetravalent vaccine was modeled using knowledge based threading approach where whole stretch of sequence was taken into consideration with secondary and tertiary structure based similarity approaches. The initial model structure was refined with utilities of energy minimizations. Structure had been resolved where all hydrogen atoms have been projected from the backbone and optimized in terms of packing. It was also confirmed that all the amino acid residues were taking part in the structure formation and proper folding patterns were observed where maximum residues were in allowed region of Ramchandran plot see Fig. 5 and Table 4.
FIG.5: TERTIARY STRUCTURE PREDICTION AND REFINEMENT OF RECOMBINANT TETRAVALENT EDIII (A) INITIAL AND (B) REFINED TERTIARY STRUCTURE ; RAMACHANDRAN PLOT FOR (C) INITIAL (D) REFINED TERTIARY STRUCTURE SHOWING MORE NUMBER OF AMINO ACIDS IN FAVORED REGIONS |
TABLE 4: COMPARISON OF RAMACHANDRAN PLOTS STATISTICS FOR INITIAL AND REFINED MODELS
Properties | Initial model | Refined model | ||
Residues in most favored regions [A, B, L] | 303 | 76.1% | 368 | 92.46% |
Residues in additional allowed regions [a, b, l, p] | 66 | 16.6% | 15 | 3.76% |
Residues in generously allowed regions [~a,~b,~ l , ~p] | 19 | 4.8% | 8 | 2.01% |
Residues in disallowed regions | 10 | 2.5% | 7 | 1.75% |
Number of non-glycine and non-proline residues | 398 | 100% | 398 | 100% |
Number of end-residues (excl. Gly and Pro) | 1 | 1 | ||
Number of glycine residues | 40 | 40 | ||
Number of proline residues | 28 | 28 | ||
Total number of residues | 467 | 467 |
We selected the murine monoclonal antibody 4E11, which neutralizes all four DENV serotypes 30, to check its activity with recombinant tetravalent vaccine. The structure of monoclonal antibody 4E11 was extracted from PDB database with 3UZV identifier. It showed favourable protein-protein interaction with most stable and lowest binding energy amongst see Fig. 6.A. The 2D interaction found to be between LYS (55) and VAL (57) amino acid residues of 4E11 and ILE (194) amino acid residues of recombinant vaccine see Fig.6.B.
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FIG. 6: PROTEIN-PROTEIN INTERACTION BETWEEN MICE MONOCLONAL ANTIBODY 4E11 AND RECOMBINANT VACCINE (A) COMPLETE VIEW WHERE RED BALL SHOWING THE REGION OF INTERACTION (B) 2D INTERACTION DIAGRAM SHOWING ACTUAL AMINO ACID INTERACTION |
This finding has been interesting as the ILE (194) amino acid residue of recombinant vaccine has potential to interact with mice monoclonal antibody (4E11) which is known to neutralize all four DENV serotypes. Thus ILE (194) amino acid residue has been predicted to be the critical residue for DENV complex-specific MAb 4E11.
CONCLUSION: In silico approach to study various parameters of our dengue vaccine candidate indicates that the vaccine is stable, antigenic, properly folded, with proper binding to a broad cross-neutralizing murine monoclonal antibody against all DENV serotypes. Also multiple B-cell and T-cell epitopes predicted in the vaccine model are known immunogenic epitopes. Thus our predicted vaccine model shall induce both B-cell and T-cell immune response, which further need to be evaluated for immunogenicity and efficacy studies in laboratory animals.
ACKNOWLEDGMENTS: Authors would like to thank Dr. Kiran Mahale, Post Doctoral Fellow at National Centre for Cell Sciences, Pune for helping with vaccine sequence data submission to GenBank.
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How to cite this article:
Kulkarni A, Shinde P, Kothari S, Warke R, Chowdhary A and Deshmukh RA: A Novel Tetravalent Recombinant Envelope Domain III Vaccine against Dengue: An In Silico Approach. Int J Pharm Sci Res 2015; 6(6): 2441-50.doi: 10.13040/IJPSR.0975-8232.6(6).2441-50.
All © 2013 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Article Information
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English
Ijpsr
A. Kulkarni *, P. Shinde, S. Kothari, R. Warke, A. Chowdhary and R. A. Deshmukh
Department of Virology , Haffkine Institute for Training, Research and Testing, Acharya Donde Marg, Parel, Mumbai, India
ajitakulkarni76@gmail.com
15 October, 2014
12 December, 2014
04 February, 2015
10.13040/IJPSR.0975-8232.6(6).2441-50
01 June, 2015