alexa Prediction of Wuchereria Bancrofti Troponin Antigenic Peptides: Application in Synthetic Vaccine Design to Counter Lymphatic Filariasis | OMICS International
ISSN: 2157-7560
Journal of Vaccines & Vaccination

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Prediction of Wuchereria Bancrofti Troponin Antigenic Peptides: Application in Synthetic Vaccine Design to Counter Lymphatic Filariasis

Gomase VS1*, Chitlange NR1, Sherkhane AS1, Changbhale SS1 and Kale KV2

1The Global Open University, Nagaland, India

2Professor and Head, Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, 431001, India

*Corresponding Author:
Gomase VS
Jagdishprasad Jhabarmal Tibrewala University
Jhunjhunu Rajasthan, India
Tel: 91-9987770696
E-mail: [email protected]

Received date: December 01, 2012; Accepted date: January 27, 2013; Published date: January 31, 2013

Citation: Gomase VS, Chitlange NR, Sherkhane AS, Changbhale SS, Kale KV (2013) Prediction of Wuchereria Bancrofti Troponin Antigenic Peptides: Application in Synthetic Vaccine Design to Counter Lymphatic Filariasis. J Vaccines Vaccin 4:169. doi: 10.4172/2157-7560.1000169

Copyright: © 2013 Gomase VS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Wuchereria bancrofti is a threadlike nematode one of the causative worm of lymphatic filariasis in which the
lymphatic and genital organs get disabled either temporarily or permanently; till date no effective drug or vaccine has been discovered to treat lymphatic filariasis. In this analysis we have predicted antigenic peptides from Wuchereria bancrofti troponin protein for synthetic peptide vaccine design against lymphatic filariasis because with a single protein subunit immune response can be generated in large population. Analysis shows predicted epitopes of Wuchereria bancrofti troponin protein are important determinant for protection against lymphatic filariasis. In this assay we have analysed the binding affinity of Wuchereria bancrofti troponin protein having 136 amino acids, which shows 128 nonamers. In this research work, we predicted CTL-epitopes by two different methods namely SVM (Support Vector Machine) and ANN (Artificial Neural Network), SVM based prediction shown sixteen valid epitopes having optimal score of 1.129 at cut off 0.36 whereas ANN based prediction shown thirty-one valid epitopes having optimal score of 1.000 at cut off 0.51. We also predicted cascade SVM based TAP binders and four potential antigenic epitopes as, 31-LRKLIRK-37, 49-DEFCALVYTVANT-61, 87-SRPTLKALLKE-97, 108-EAAVDE-113 (optimal propensity 1.223) predicted on the basis of highest local hydrophilicity; in addition to this we also have experimentally predicted tertiary structure of the two longest potential epitopes those can aid our understanding in
sequence-structure-function relationship of Wuchereria bancrofti troponin protein towards synthetic peptide vaccine design. Thus a small fragment of troponin protein can produce immune response against activity of Wuchereria bancrofti. This approach can be applied for designing subunit and synthetic peptide vaccines

Keywords

Lymphatic filariasis; Parasitic disease; Antigenic peptides; MHC; SVM; ANN; CTL; Nonamers; Synthetic peptide vaccines

Abbrevations

MHC: Major Histocompatibility Complex; CTL: Cytotoxic T lymphocytes; TAP: Transporter associated with Antigen Processing; SVM: Support Vector Machine; ANN: Artificial Neural Network

Introduction

Lymphatic filariasis

Lymphatic filariasis also known Elephantiasis is a parasitic infection caused by filarial roundworm, Wuchereria bancrofti. The infection is usually acquired in childhood, its indication of the existence occur later in life, causing temporary or permanent disability of an infected organ, causes severe damage and painful swelling, disfiguring swelling of the legs and genital organs is a classic symptom of late disease stage. In many tropical countries, lymphatic filariasis has a major social and economic impact, though World Health Organization is trying to eliminate it completely by the year 2020 yet there is no effective drug or vaccine has been invented to treat/prevent Elephantiasis (WHO, lymphatic Filariasis).

Pathogen transmission

An Infected mosquito deposits larvae on the individual’s skin while biting and larvae enter Wound. The Larvae migrates into lymphatic system where they grow, Adult male worms are about 3-4 cm long while female worms are 8-10 cm long. When male and female worms mate they form nests; these nests cause blockages in the human lymphatic system resulting symptoms like swelling and fever. Female worm produces microscopic worms called microfilaria. When mosquito bites to an infected individual, ingests microfilaria with blood and infects to healthy individual, Microfilaria develops into adult worm over a week and the cycle continues [WHO, lymphatic Filariasis].

Strategy

This approach is based on the phenomenon of cross-protection [1] hereby an individual infected with a mild strain of pathogen possess immunity against more severe strain of the same pathogen. Body proteins are necessary for its production in or on all food commodities. An exemption from the requirement of a tolerance is established for residues of the drugs or chemicals. The lymphatic system is an important component of the body’s immune system, it include several centres of initial infection so the immune response can be generated in the lymph organ even with single antigen subunit.

MHC class binding peptides

The new paradigm in vaccine design is emerging; following essential discoveries in immunology and development of new CTL binding peptides prediction tools [2]. MHC molecules are cell surface glycoproteins, which take active part in host immune reactions. The involvement of MHC class-I in response to almost all antigens and considering its binding affinity with peptides of 9 amino acids, we have predicted the 9 amino acid long epitopes from extracted data MHCBN Comprehensive data base of MHC-I and MHC-II binding as well as non-binding epitopes. MHC molecules have been well characterized in terms of their role in immune reactions. They bind to several peptide fragments generated after proteolytic cleavage of antigen [3]. This binding act like red flags for specific antigen and generates immune response against the parent antigen. So an antigen from Wuchereria bancrofti troponin subunit can induce immune response against Wuchereria bancrofti activity. CTL epitopes are most suitable for subunit vaccine development because with single epitope, the immune response can be generated in large population. MHC peptide complexes will be translocated on the surface of antigen presenting cells (APCs). This theme is implemented in developing subunit and synthetic peptide vaccines [4-7]. One of the important problems in subunit vaccine design is to search for antigenic regions in an antigen protein [8] that can stimulate T-cells called T-cell epitopes. In literature, fortunately, a large amount of data about such peptides is available. Previously and presently, a number of databases have been developed to provide comprehensive information related to T-cell epitopes [9-13].

Materials and Methods

Protein sequence analysis

Wuchereria bancrofti troponin protein is a diagnostic antigen against lymphatic filariasis. The antigenic protein sequence of W. bancrofti troponin antigen protein was analyzed to study the antigenicity solvent accessible regions and MHC class binding peptide, which allows potential drug targets to predict active sites against Lymphatic filariasis.

A Wuchereria bancrofti troponin (gi- 373938659) protein sequence is 136 amino acids long as-MFDRGKQGYIMATQIGQIMHAMEQDF DEKQLRKLIRKFDADGSGKLEFDEFCALVYTVANTVDKETLQKEL REAFRLFDKEGNGYISRPTLKALLKEIADDLSDEQLEAAVDEIDED GSGKIEFEEFWELMAGDAD

Antigenicity prediction

Antigenicity Prediction program results those segments from Wuchereria bancrofti troponin antigen protein that are likely to be antigenic by eliciting an antibody response. Antigenic epitopes are determined using the Gomase, (2007), Hopp and Woods, Welling, Parker, B-EpiPred Server and Kolaskar and Tongaonkar antigenicity methods [14-18].

Protein secondary structure prediction

The important concepts in secondary structure prediction are identified as: residue conformational propensities, sequence edge effects, hydrophobicity moments, insertions and Deletions positions in aligned homologous sequence, moments of conservation, autocorrelation, residue ratios, secondary structure feedback effects and filtering [19,20].

Finding the location in solvent accessible regions

Finding the location in solvent accessible regions in protein, type of plot determines the hydrophobic and hydrophilic scales and it is utilized for prediction. This may be useful in predicting membranespanning domains, potential antigenic sites and regions that are likely exposed on the protein surface [21-41].

CTL epitope prediction

The CTL Epitopes of Wuchereria bancrofti troponin are obtained from MHCBN comprehensive database of MHC binding and nonbinding peptides using two different methods firstly with Support Vector Machine based method (Cut off is 0.36) and then by Artificial Neural Network based method (Cut off is 0.51). In this work predicted MHC-Peptide binding is a log-transformed value related to the IC50 values in nM units.

The average accuracy of Support Vector Machine (SVM) based epitope prediction method is ~76% at cut off 0.36. SVM has been trained on the binary input of single amino acid sequence. In Case of Artificial Neural Network ANN based epitope prediction method the average accuracy is ~74% at the cut off score 0.51 [2].

TAP binding prediction

TAP (Transporter associated with Antigen Peptide) play an important role in transportation of MHC-Peptide complexes, which elicits the immune response for clearing various intracellular infections. The prediction of TAP binding peptides is crucial in identifying the MHC class-I restricted T cell epitopes. The Prediction is based on cascade SVM, using properties of amino acid sequence at correlation coefficient of 0.88 as per Jack-Knife validation test [42].

Peptide structure prediction

Peptide Structure prediction is a challenge, which would aid our understanding of sequence–structure–function relationships towards synthetic peptide vaccine design. Peptide Structure prediction depends on the complexity and the accuracy of the models used to represent them. We have used Hidden Markov Model derived structural alphabet (SA) based tool that discretizes peptide experimental conformation as series of overlapping fragments of four residues length. The predicted structure can be considered to have an average accuracy of ~1.1A rootmean- square deviation (RMSd) [43-46].

Result and Interpretation

Antigenic peptides prediction

In this assay we predicted the antigenic determinants by finding the area of highest local hydrophilicity. The Hopp & Woods scale was designed to predict the locations of antigenic determinants in linear antigen protein sequence, assuming that the antigenic determinants would be exposed on the protein surface and thus would be located in hydrophilic regions (Figure 1). Its values are derived from the transferfree energies for amino acid side chains between ethanol and water. Welling antigenicity plot gives value as the log of the quotient between percentage in a sample of known antigenic regions and percentage in average proteins (Figure 2). We also studied B-EpiPred Server, Parker, Kolaskar and Tongaonkar antigenicity methods and the predicted antigenic fragments can bind to MHC molecule is the first bottlenecks in vaccine design (Figures 3-6).

vaccines-vaccination-Hydrophobicity-plot-Hopp

Figure 1: Hydrophobicity plot of Hopp and Woods (1981) of Wuchereria bancrofti troponin.

vaccines-vaccination-plot-Welling

Figure 2: Hydrophobicity plot of Welling et al. (1985) of Wuchereria bancrofti troponin.

vaccines-vaccination-Wuchereria-bancrofti

Figure 3: B-cell epitopes are the sites of molecules that are recognized by antibodies of the immune system of the Wuchereria bancrofti troponin.

vaccines-vaccination-Tongaonkar-antigenicity

Figure 4: Kolaskar and Tongaonkar antigenicity are the sites of molecules that are recognized by antibodies of the immune system for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-HPLC

Figure 5: Hydrophobicity plot of HPLC / Parker et al. (1986) of Wuchereria bancrofti troponin.

vaccines-vaccination-Emini-Surface-Accessibility

Figure 6: Hydrophobicity plot of Emini Surface Accessibility Prediction (1990) of Wuchereria bancrofti troponin.

Secondary alignment

The Robson and Garnier method applied for secondary structure prediction of the Wuchereria bancrofti troponin protein. Each residue have specific assigned value for alpha helix (Shown in Red), beta sheet (Shown in Blue) and coil (Shown in Pink) using a window of 7 residues (Figure 7). Using these information parameters, the likelihood of a given residue assuming each of the four possible conformations alpha, beta, reverse turn or coils calculated and the conformation with the largest likelihood is assigned to the residue.

vaccines-vaccination-bancrofti-troponin

Figure 7: Secondary structure plot of the Wuchereria bancrofti troponin.

Solvent accessible regions

Solvent accessible scales for delineating hydrophobic and hydrophilic characteristics of amino acids and scales are developed for predicting potential antigenic sites of globular proteins, which are likely to be rich in charged and polar residues. It was shown that Wuchereria bancrofti troponin protein is hydrophobic in nature and contains segments of low complexity and high-predicted flexibility (Figures 8-28).

vaccines-vaccination-Hydrophobicity-plot-Rao

Figure 8: Hydrophobicity plot of Rao and Argos (1986) for the Wuchereria bancrofti troponin.

vaccines-vaccination-bancrofti-troponin

Figure 9: Hydrophobicity plot of Rose et al. (1985) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-Sweet

Figure 10: Hydrophobicity Sweet plot of OMH for the Wuchereria bancrofti troponin.

vaccines-vaccination-Kyte-Doolittle

Figure 11: Hydrophobicity plot of Kyte and Doolittle (1982) for the Wuchereria bancrofti troponin.

vaccines-vaccination-plot-Abraham-Leo

Figure 12: Hydrophobicity plot of Abraham and Leo (1987) for the Wuchereria bancrofti troponin.

vaccines-vaccination-plot-Bull-Breese

Figure 13: Hydrophobicity plot of Bull and Breese (1974) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Guy

Figure 14: Hydrophobicity plot of Guy (1985) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Miyazawa-Jernigen

Figure 15: Hydrophobicity plot of Miyazawa and Jernigen (1985) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Roseman

Figure 16: Hydrophobicity plot of Roseman (1988) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Wolfenden

Figure 17: Hydrophobicity plot of Wolfenden et al. (1981) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-Wilson

Figure 18: Hydrophobicity Wilson et al. (1981) plot of HPLC for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-Cowan-Whittaker

Figure 19: Hydrophobicity Cowan and Whittaker (1990) plot of HPLC pH 3.4 for the Wuchereria bancrofti troponin.

vaccines-vaccination-plot-RF-mobility

Figure 20: Hydrophobicity plot of RF mobility for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Chothia

Figure 21: Hydrophobicity plot of Chothia (1976) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Eisenberg

Figure 22: Hydrophobicity plot of Eisenberg et al. (1984) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Manavalan

Figure 23: Hydrophobicity plot of Manavalan and Ponnuswamy (1978) for the Wuchereria bancrofti troponin.

vaccines-vaccination-plot-Black-Mould

Figure 24: Hydrophobicity plot of Black and Mould (1991) for the Wuchereria bancrofti troponin.

vaccines-vaccination-plot-Fauchere-Pliska

Figure 25: Hydrophobicity plot of Fauchere and Pliska (1983) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Janin

Figure 26: Hydrophobicity plot of Janin (1979) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-plot-Tanford

Figure 27: Hydrophobicity plot of Tanford (1962) for the Wuchereria bancrofti troponin.

vaccines-vaccination-Hydrophobicity-Cowan-Whittaker

Figure 28: Hydrophobicity Cowan and Whittaker (1990) plot of HPLC pH 7.5 for the Wuchereria bancrofti troponin.

Prediction of MHC binding peptides

MHC molecules are cell surface glycoproteins, which take active part in host immune reactions and involvement of MHC class-I and MHC II in response to almost all antigens so these MHC binding peptides are sufficient for eliciting the desired immune response. In analysis we determined the CTL binding regions, TAP binding regions and several potential antigenic epitopes. In this study we predicted the binding affinity of Wuchereria bancrofti troponin protein having 136 amino acids, which shows number of peptides. The CTL epitope prediction is based on an elegant machine learning technique Support Vector Machine (SVM) and Artificial Neural Network (ANN). SVM has been trained on the binary input of single amino acid sequence. In this assay we have predicted the binding affinity of Wuchereria bancrofti troponin protein sequence having 136 amino acids, which shows 128 nonamers.The SVM based CTL epitopes, 86-ISRPTLKAL, 46-LEFDEFCAL, 84-GYISRPTLK, 122-IEFEEFWEL, 47-EFDEFCALV, 29-KQLRKLIRK, 80-KEGNGYISR, 87-SRPTLKALL, 69-KELREAFRL, 50-EFCALVYTV, 72-REAFRLFDK, 2-FDRGKQGYI, 11-MATQIGQIM, 4-RGKQGYIMA, 90-TLKALLKEI, 123-EFEEFWELM (optimal score is 1.129); the ANN based CTL epitopes recorded are, 60-NTVDKETLQ, 12-ATQIGQIMH, 36-RKFDADGSG, 85-YISRPTLKA, 109-AAVDEIDED, 76-RLFDKEGNG, 20-HAMEQDFDE, 69-KELREAFRL, 94-LLKEIADDL, 32-RKLIRKF-DA, 50-EFCALVYTV, 67-LQKELREAF, 112-DEIDEDGSG, 54-LVYTVANTV, 98-IADDLSDEQ, 41-DGSGKLEFD, 89-PTLKALLKE, 79-DKEGNGYIS, 82-GNGYISRPT, 104-DEQLEAAVD, 100-DDLSDEQLE, 40-ADGSGKLEF, 62-VDKETLQKE, 27-DEKQLRKLI, 90-TLKALLKEI, 108-EAAVDEIDE, 42-GSGKLEFDE, 52-CALVYTVAN, 43-SGKLEFDEF, 61-TVDKETLQK, 53-ALVYTVANT, which represented predicted binders from Wuchereria bancrofti troponin protein (Tables 1 and 2). In addition to the CTL epitopes we also have predicted several high Affinity TAP binders as 102-LSDEQLEAA, 23-EQDFDEKQL, 26-FDEKQLRKL, 12-ATQIGQIMH, 92-KALLKEIAD, 73-EAFRLFDKE, 98-IADDLSDEQ, 57-TVANTVDKE, 82-GNGYISRPT,125-EEFWELMAG, 35-IRKFDADGS, 9-YIMATQIGQ, 21-AMEQDFDEK, 74-AFRLFDKEG, 95-LKEIADDLS, 44-GKLEFDEFC, 11-MATQIGQIM, 36-RKFDADGSG, 94-LLKEIADDL, 66-TLQKELREA, 51-FCALVYTVA, 48-FDEFCALVY, 124-FEEFWELMA, 33-KLIRKFDAD, 37-KFDADGSGK, 45-KLEFDEFCA, 22-MEQDFDEKQ, 99-ADDLSDEQL, 53-ALVYTVANT, 96-KEIADDLSD, 63-DKETLQKEL, 70-ELREAFRLF, 90-TLKALLKEI, 10-IMATQIGQI, 88-RPTLKALLK, 24-QDFDEKQLR, 123-EFEEFWELM, 52-CALVYTVAN, 120-GKIEFEEFW, 14-QIGQ-IMHAM, 116-EDGSGKIEF, these TAP binders are important in generating immune response (Table 3). The optimal propensity for the Wuchereria bancrofti troponin protein found is 1.223 (Figure 4). All residues having above 1.0 propensity are always potentially antigenic (Table 4). The predicted segments in Wuchereria bancrofti troponin protein are 31-LRKLIRK-37, 49-DEFCALVYTVANT-61, 87-SRPTLKALLKE- 97, 108-EAAVDE-113 Fragments identified through this approach tend to be high-efficiency binders, which is a larger percentage of their atoms are directly involved in binding as compared to larger molecules. These MHC binding peptides are sufficient for inducing the desired immune response. Predicted MHC binding regions in Wuch-ereria bancrofti troponin sequence and these are actively taking part in immune reactions.

Peptide rank Start position Sequence Score
1 86 ISRPTLKAL 1.129
2 46 LEFDEFCAL 0.992
3 84 GYISRPTLK 0.971
4 122 IEFEEFWEL 0.912
5 47 EFDEFCALV 0.803
6 29 KQLRKLIRK 0.702
7 80 KEGNGYISR 0.679
8 87 SRPTLKALL 0.664
9 69 KELREAFRL 0.654
10 50 EFCALVYTV 0.594
11 72 REAFRLFDK 0.578
12 2 FDRGKQGYI 0.523
13 11 MATQIGQIM 0.405
14 4 RGKQGYIMA 0.383
15 90 TLKALLKEI 0.368
16 123 EFEEFWELM 0.363

Table 1: SVM based Predicted CTL-Epitopes of Wuchereria bancrofti troponin protein.

Peptide rank Start position Sequence Score
1 60 NTVDKETLQ 1.000
2 12 ATQIGQIMH 0.990
3 36 RKFDADGSG 0.990
4 85 YISRPTLKA 0.990
5 109 AAVDEIDED 0.990
6 76 RLFDKEGNG 0.970
7 20 HAMEQDFDE 0.930
8 69 KELREAFRL 0.930
9 94 LLKEIADDL 0.930
10 32 RKLIRKFDA 0.910
11 50 EFCALVYTV 0.910
12 67 LQKELREAF 0.910
13 112 DEIDEDGSG 0.900
14 54 LVYTVANTV 0.870
15 98 IADDLSDEQ 0.860
16 41 DGSGKLEFD 0.830
17 89 PTLKALLKE 0.830
18 79 DKEGNGYIS 0.800
19 82 GNGYISRPT 0.800
20 104 DEQLEAAVD 0.800
21 100 DDLSDEQLE 0.760
22 40 ADGSGKLEF 0.720
23 62 VDKETLQKE 0.710
24 27 DEKQLRKLI 0.660
25 90 TLKALLKEI 0.630
26 108 EAAVDEIDE 0.630
27 42 GSGKLEFDE 0.570
28 52 CALVYTVAN 0.550
29 43 SGKLEFDEF 0.540
30 61 TVDKETLQK 0.540
31 53 ALVYTVANT 0.530

Table 2: ANN based Predicted CTL-Epitopes of Wuchereria bancrofti troponin protein.

Peptide rank Start position Sequence Score
1 102 LSDEQLEAA 8.641
2 23 EQDFDEKQL 8.641
3 26 FDEKQLRKL 8.635
4 12 ATQIGQIMH 8.634
5 92 KALLKEIAD 8.633
6 73 EAFRLFDKE 8.602
7 98 IADDLSDEQ 8.598
8 57 TVANTVDKE 8.588
9 82 GNGYISRPT 8.563
10 125 EEFWELMAG 8.508
11 35 IRKFDADGS 8.315
12 9 YIMATQIGQ 8.266
13 21 AMEQDFDEK 8.266
14 74 AFRLFDKEG 8.251
15 95 LKEIADDLS 8.229
16 44 GKLEFDEFC 8.149
17 11 MATQIGQIM 8.148
18 36 RKFDADGSG 8.132
19 94 LLKEIADDL 8.113
20 66 TLQKELREA 8.112
21 51 FCALVYTVA 7.863
22 48 FDEFCALVY 7.805
23 124 FEEFWELMA 7.804
24 33 KLIRKFDAD 7.682
25 37 KFDADGSGK 7.669
26 45 KLEFDEFCA 7.521
27 22 MEQDFDEKQ 7.502
28 99 ADDLSDEQL 7.490
29 53 ALVYTVANT 7.335
30 96 KEIADDLSD 7.222
31 63 DKETLQKEL 7.175
32 70 ELREAFRLF 7.044
33 90 TLKALLKEI 6.969
34 10 IMATQIGQI 6.961
35 88 RPTLKALLK 6.933
36 24 QDFDEKQLR 6.612
37 123 EFEEFWELM 6.521
38 52 CALVYTVAN 6.408
39 120 GKIEFEEFW 6.349
40 14 QIGQIMHAM 6.301
41 116 EDGSGKIEF 6.046

Table 3: Cascade SVM based High affinity TAP epitopes of Wuchereria bancrofti troponin protein.

No. Start position End position Peptide Peptide length
1 31 37 LRKLIRK 7
2 49 61 DEFCALVYTVANT 13
3 87 97 SRPTLKALLKE 11
4 108 113 EAAVDE 6

Table 4: Potential Antigenic epitopes of Wuchereria bancrofti troponin protein.

Tertiary structure prediction of the predicted epitopes

We have predicted the experimentally confirmed structures of the two potential epitopes 49-DEFCALVYTVANT-61, 87-SRPTLKALLKE-97, these are the longest epitopes predicted from the Wuchereria bancrofti troponin protein showing the highest pick. The peptide structures are validated by applying A Hidden Markov Model based approach which predicts the tertiary confirmation of the peptide sequence at accuracy ~1.1 RMSd. The validated structures are shown in Balls & Sticks model over solvent-accessible surface (VDW+1.4 angstrom) (Figures 29 and 30) [47,48].

vaccines-vaccination-Solvent-Accessible

Figure 29: Experimentally Confirmed Structure of 49-DEFCALVYTVANT-61 epitope shown over Solvent-Accessible Surface.

vaccines-vaccination-Experimentally-Confirmed

Figure 30: Experimentally Confirmed Structure of 87-SRPTLKALLKE-97 epitope shown over Solvent-Accessible Surface.

Discussion and Conclusion

Gomase method (2007), B-EpiPred Server, Hopp and Woods, Welling, Parker, Kolaskar and Tongaonkar antigenicity scales were designed to predict the locations of antigenic determinants in Wuchereria bancrofti troponin protein sequence. It shows beta sheets regions, which have higher antigenic response than helical region of this peptide and shows high antigenicity (Figures 1-5) [49-52]. We also found the Sweet hydrophobicity, Kyte & Doolittle hydrophobicity, Abraham & Leo, Bull & Breese hydrophobicity, Guy, Miyazawa hydrophobicity, Roseman hydrophobicity, Cowan HPLC pH 7.5 hydrophobicity, Rose hydrophobicity, Eisenberg hydrophobicity, Manavalan hydrophobicity, Black hydrophobicity, Fauchere hydrophobicity, Janin hydrophobicity, Rao & Argos hydrophobicity, Wolfenden hydrophobicity, Wilson HPLC hydrophobicity, Cowan HPLC pH 3.4, Tanford hydrophobicity, RF mobility hydrophobicity and Chothia hydrophobicity scales, Theses scales are essentially a hydrophilic index, with a polar residues assigned negative values (Figures 8-28). In this assay we predicted the binding affinity of Wuchereria bancrofti troponin protein having 136 amino acids, which shows 128 nonamers. We predicted SVM and ANN based CTL epitopes (Tables 1 and 2) [53,54].

We have determined sixteen CTL predicted epitopes (Optimal score is 1.129) at cut off 0.36 using SVM based method (Table 1) and thirty one CTL predicted epitopes using ANN based method at cut off 0.51 (Optimal score is 1.000) (Table 2) which represents predicted peptide binders from Wuchereria bancrofti troponin protein. We also have predicted Cascade SVM based forty one High affinity TAP binding epitopes (Optimal score is 8.641) (Table 3) in addition to four potentially antigenic peptides recognized by antibodies of the immune system for troponin protein in the region of maximum local hydrophilicity (Table 4) [55]. Kolaskar and Tongaonkar antigenicity are the sites of molecules that are recognized by antibodies of the immune system for troponin protein, analysis shows epitopes present in the troponin protein eliciting desired immune response [18]. The region of maximal hydrophilicity is likely to be an antigenic site, having hydrophobic characteristics, because C- terminal regions of Wuchereria bancrofti troponin protein is solvent accessible and unstructured, antibodies against those regions are also likely to recognize the native protein. For the prediction of antigenic determinant site of Wuchereria bancrofti troponin protein, we predicted four antibody recognized antigenic determinant sites in the Wuchereria bancrofti troponin sequence. The highest pick is recorded between sequence of amino acid in the region are 49- DEFCALVYTVANT-61 and 87-SRPTLKALLKE-97 (Table 4) [56]. We also predicted the surface accessible tertiary structure for the peptide recorded with the highest pick; these are the longest peptides predicted in the antigenic sequence of the Wuchereria bancrofti troponin protein, the experimentally confirmed structures of the predicted peptides are considered to have an average accuracy of ~1.1A RMSd, the predicted peptide structures can be applied in synthetic peptide vaccine design approach to understand the sequence–structure–function relationship of the Wuchereria bancrofti troponin protein [57-59].

Future Perspectives

This method will be useful in cellular immunology, Vaccine design, immunodiagnostics, immunotherapeutics and molecular understanding of autoimmune susceptibility. Wuchereria bancrofti troponin protein sequence contains multiple antigenic components to direct and empower the immune system to protect an individual from lymphatic filariasis disease. MHC molecules are cell surface proteins, which actively participates in host immune reactions and involvement of MHC class in response to almost all antigens and it give effects on target sites. Predicted MHC binding regions acts like red flags for specific antigen and generate immune response against the whole antigen. So a small antigen fragment can generate immune response against entire antigen. The method integrates prediction of Peptide-MHC class binding; proteosomal C terminal cleavage and TAP transport efficiency. This approach is implemented in designing subunit and synthetic peptide vaccines.

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Chemistry Journals

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Clinical Journals

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Engineering Journals

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General Science

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Immunology & Microbiology Journals

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Materials Science Journals

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Medical Journals

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