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Research Article - (2014) Volume 5, Issue 4

Identification of Antigenic Determinants, Solvent Accessibility and MHC Binders of Peb1a from Campylobacter jejuni

Sherkhane AS1, Waghmare Somnath2 and Gomase VS3*
1The Global Open University, Nagaland, India
2Department of Zoology, Nowrosjee Wadia College of Arts and Science, Pune, India
3Department of Computer Science and Information Engineering, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India
*Corresponding Author: Gomase VS, Department of Computer Science and Information Engineering, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India, Tel: 91- 9987770696 Email:

Abstract

Campylobacter jejuni is a foodborne, highly mutable in response to antibiotic, pathogen causing gastroenteritis in humans. In this study we summarize the potency of Peb1a from Campylobacter jejuni with 259 amino acids. Antigenic peptides of Peb1a from Campylobacter jejuni are most suitable for subunit vaccine development because with single epitope, the immune response can be generated in large population. In this research, we used PSSM and SVM algorithms for the prediction of MHC class I & II binding peptide, antigenicity, Solvent accessibility, polar and nonpolar residue to analyses the regions that are likely exposed on the surface of proteins which are potentially antigenic that allows potential drug targets to identify active sites against infection as well as to design effective drug to treat it.

Keywords: Campylobacter jejuni ; Peb1a; Antigenic peptides; MHCBinders; TapPred; PSSM; SVM; Nonamers

Introduction

Campylobacter jejuni is a gram-negative, microaerophilic, chemoorganotrophic bacterium, foodborne pathogen, causing gastroenteritis, diarrhea, fever, abdominal cramps and neuromuscular paralysis in humans [1-3]. The organism is transmitted to humans through contaminated water, milk and undercooked poultry meat. To recover the infection of Peb1a from Campylobacter jejuni there is need understand the function of Peb1a protein because it is highly mutable in response to antibiotic [4]. Antigenic peptides of Peb1a from from Campylobacter jejuni are most suitable for the development of peptide vaccine [4] because a single peptide can generate sufficient immune response. In this research work we have used the phenomenon of cross-protection, whereby an individual undertaken by a mild toxin can have immunity to survive against similar strong toxic effects. MHC molecules are cell surface protein that binds Peb1a from Campylobacter jejuni and present them to cell surface for recognition by T-cells. T cell recognition is an important mechanism of the adaptive immune system by which the host identifies and responds to Peb1a from Campylobacter jejuni [5,6]. There are two types of MHC molecule and are extremely polymorphic. MHC class I molecules present peptides Peb1a from Campylobacter jejuni synthesized within the cell, whereas, MHC class II molecule present peptides derived from endocytosed extracellular proteins. MHC molecules play an important role in immune reactions by taking active part in host immune reactions and involvement of MHC class molecule in response to almost all antigens and it give impacts on specific sites. The involvement of MHC class-I molecule in response to almost all antigens make the study very interesting. They bind to some of the peptide fragments generated after proteolytic cleavage of antigen [7]. Identification of MHC-binding peptides and T-cell epitopes helps improve our understanding of specificity of immune responses [8-11]. Antigenic peptides are most suitable for peptide vaccine development because single epitope can generate large the immune response [12-14].

Methodology

Database searching

The antigenic protein sequence of Peb1a from Campylobacter jejuni was retrieved from NCBI databases [15-17].

Prediction of antigenicity

Prediction of antigenicity program predicts those segments of Peb1a from Campylobacter jejuni that are likely to be antigenic by eliciting an antibody response. In this research work antigenic epitopes of Peb1a from Campylobacter jejuni are determined by using the Hopp and Woods, Welling, Parker, Bepipred , Kolaskar and Tongaonkar antigenicity methods [18-22].

Prediction of MHC binding peptide

The major histocompatibility complex (MHC) peptide binding of Peb1a from Campylobacter jejuni is predicted using neural networks trained on C terminals of known epitopes. Rankpep toll predicts peptide binders to MHC-I ligands whose C-terminal end is likely to be the result of proteosomal cleavage using Position Specific Scoring Matrices (PSSMs). Support Vector Machine (SVM) based method for prediction of promiscuous MHC class II binding peptides from protein sequence; SVM has been trained on the binary input of single amino acid sequence [23-27].

Prediction of antigenic peptides by cascade SVM based TAPPred method

We predict cascade SVM based several TAP binders which was based on the sequence and the features of amino acids (Table 3) [28].

Solvent accessible regions

We predict solvent accessible regions of proteins having highest probability that a given protein region lies on the surface of a protein Surface Accessibility, backbone or chain flexibility by Emani et al., [29] and Karplus and Schulz [30]. By using different scale we predict the hydrophobic and hydrophilic characteristics of amino acids that are rich in charged and polar residues i.e. Sweet et al. [31], Kyte and Doolittle [32], Abraham and Leo [33], Bull and Breese [34], Miyazawa, et al. [35], Roseman [36], Wolfenden et al. [37], Wilson et al. [38], Cowan [39], Chothia [40].

Results and Interpretations

Protein sequence of Peb1a from Campylobacter jejuni contain long residue of 259 amino acids with 251 nonamers [GI:433552054].

MVFRKSLLKLAVFALGACVAFSNANAAEGKLESIKSKGQLIVGVKNDVPHYALLDQATGEIKGFEVDVAK

LLAKSILGDDKKIKLVAVNAKTRGPLLDNGSVDAVIATFTITPERKRIYNFSEPYYQDAIGLLVLKEKKYKSLA

DMKGANIGVAQAATTKKAIGEAAKKIGIDVKFSEFPDYPSIKAALDAKRVDAFSVDKSILLGYVDDKSEILP

DSFEPQSYGIVTKKDDPAFAKYVDDFVKEHKNEIDALAKKWGL

Prediction of antigenic peptides

Antigencity predicted by using Hopp-Woods scale the result found high in position 81, 82, 114-117, and 229-232 in a protein, assuming that the antigenic determinants would be exposed on the surface of the protein and thus would be located in hydrophilic regions (Figure 1). 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 and Result found high in position 71-72, 138-141 and 189-190 (Figure 2). We also study Hydrophobicity plot of HPLC / Parker Hydrophilicity Result found 98-DNGSVDA-104-(5.371), 228-TKKDDPA-234 (5.829) (maximum), BepiPred predicts the location of linear B-cell epitopes Result found that 24-ANAAEGKLESIK-35, 90-AKTRGPLLDNGSV-102,154-AQAATTKKAIGE-165,209 DDKSEILPDSFEPQSYGIVTKKDDPAFA-236, Kolaskar and Tongaonkar antigenicity methods Predicted peptides result found i.e. 4-RKSLLKLAVFALGACVAFS-22, 37-KGQLIVGVKNDVPHYALLDQ-56, 121-FSEPYYQDAIGLLVLKE-137, 179-FPDYPSIKAALDAKRVDAFSVDKSILLGYVDDK-211 and the predicted antigenic fragments can bind to MHC molecule is the first bottlenecks in vaccine design (Figures 3-5).

bacteriology-parasitology-Resolution

Figure 1: X-Ray Diffraction with Resolution 1.49 Å 3D Structure of the Peb1a from Campylobacter jejuni

bacteriology-parasitology-Hopp-Woods

Figure 2: Hydrophobicity plot of Hopp and Woods [17] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Welling

Figure 3: Hydrophobicity plot of Welling et al. [18] of Peb1a from Campylobacter

bacteriology-parasitology-Hydrophobicity-plot

Figure 4: Hydrophobicity plot of HPLC / Parker et al. [19] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Epitope-Prediction

Figure 5: Bepipred Linear Epitope Prediction plot showing antibody recognized B-cell epitopes of Peb1a from Campylobacter jejuni

Solvent accessible regions

We also predict solvent accessible regions in proteins; different measurement was performed for the prediction of antigenic activity, surface region of peptides. Emani et al., (Figure 6) predicts the highest probability i.e. found 112-TPERKRI-118,121-FSEPYYQ-127,136-KEKKYKS-142,242-FVKEHKNE-249, that a given protein region lies on the surface of a protein and are used to identify antigenic determinants on the surface of proteins. Karplus and Schulz (Figure 7) High score is found i.e. found 1.075 maximum in 32-ESIKSKGSIKSKGQIKSKGQL-40, 89-NAKTRGPAKTRGPLKTRGPLL-97. Predict backbone or chain flexibility on the basis of the known temperature B factors of the a-carbons. The hydrophobicity and hydrophilic characteristics of amino acids is determined by using different scales that are rich in charged and polar residues i.e. Sweet et al. hydrophobicity Result found high in position 10-13, 108-109,205-206, Kyte and Doolittle result high in position 11-18,104-108,131-134, Abraham and Leo result high in position 10-16, 131-133,205-207, Bull and Breese result high in position 25-27,90-92,157-159, Guy result high in position 114-117,138-141, Miyazawa result high in position 4-6,11-21, 41-4374-75,85-86,106-108, 131-134, Roseman result high in position 14-16,107-108,131-133,204-206, Wolfenden result high in position 132-132, Wilson et 4-5,9-13,40-43,50-54,122-123,131-134,204-207, Cowan 10-16,107-109,131-133, Chothia 13-19,40-43,107-108,131-134,150-154 (Figure 7).

bacteriology-parasitology-antigenicity-plot

Figure 6: Kolaskar and Tongaonkar [21] antigenicity plot of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Surface-Accessibility

Figure 7: Emini Surface Accessibility Prediction plot of Peb1a from Campylobacter jejuni

Prediction of MHC binding peptide

We found binding of peptides to a number of different alleles using Position Specific Scoring Matrix. Peb1a Campylobacter jejuni sequence is 259 residues long, having 65 nonamers. MHC molecules are cell surface proteins, which actively participate in host immune reactions and involvement of MHC-I and MHC-II in response to almost all antigens. We predict MHC-I peptide binders of Peb1a Campylobacter jejuni was tested with on a set of 4 different alleles i.e. H2-Db (mouse) 8mer, H2-Db (mouse) 9mer, H2-Db (mouse) 10mer and H2-Db (mouse) 11mer (Tables 1a, 1b, 1c and 1d) and MHC-II peptide binders for I_Ab.p, I_Ad.p alleles highlighted in red represent predicted binders (Tables 2a, 2b and 2c). Here PSSM-specific binding threshold and is obtained by scoring all the antigenic peptide sequences included in the alignment from which a profile is derived, and is defined as the score value that includes 85% of the peptides within the set. Peptides whose score is above the binding threshold will appear highlighted in red and peptides produced by the cleavage prediction model are highlighted in violet (Figure 8-19). We also use a cascade SVM based TAPPred method which found 80 High affinity TAP Transporter peptide regions which represents predicted TAP binders residues which occur at N and C termini of Peb1a from Campylobacter jejuni (Table 3).

MHC-I Allele POS. N SEQUENCE C MW (Da) SCORE % OPT.
8mer_H2_Db 104 SVD AVIATFTI TPE 816.99 18.033 34.35 %
8mer_H2_Db 44 IVG VKNDVPHY ALL 953.06 12.117 23.08 %
8mer_H2_Db 34 LES IKSKGQLI VGV 868.08 6.856 13.06 %
8mer_H2_Db 217 ILP DSFEPQSY GIV 953.98 6.586 12.55 %
8mer_H2_Db 119 KRI YNFSEPYY QDA 1064.14 5.626 10.72 %
8mer_H2_Db 90 AVN AKTRGPLL DNG 837.03 4.556 8.68 %
8mer_H2_Db 112 FTI TPERKRIY NFS 1044.23 3.653 6.96 %
8mer_H2_Db 144 KSL ADMKGANI GVA 800.92 2.872 5.47 %
8mer_H2_Db 86 IKL VAVNAKTR GPL 839.98 1.977 3.77 %
8mer_H2_Db 54 YAL LDQATGEI KGF 827.89 1.511 2.88 %
8mer_H2_Db 76 AKS ILGDDKKI KLV 883.05 1.366 2.60 %
8mer_H2_Db 175 IDV KFSEFPDY PSI 1014.12 1.32 2.51 %
8mer_H2_Db 222 FEP QSYGIVTK KDD 877.0 1.231 2.35 %
8mer_H2_Db 178 KFS EFPDYPSI KAA 949.05 1.17 2.23 %
8mer_H2_Db 167 GEA AKKIGIDV KFS 825.01 1.028 1.96 %
8mer_H2_Db 165 AIG EAAKKIGI DVK 810.99 0.645 1.23 %

Table 1a: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites of Peb1a from Campylobacter jejuni . The binding potential (score) of antigenic peptide to the MHC-1 Allele i.e. 8mer_H2_Db.

MHC-I Allele POS. N SEQUENCE C MW (Da) SCORE % OPT.
9mer_H2_Db 13 LAV FALGACVAF SNA 880.08 9.782 19.42 %
9mer_H2_Db 122 YNF SEPYYQDAI GLL 1067.14 7.856 15.60 %
9mer_H2_Db 46 GVK NDVPHYALL DQA 1023.16 7.504 14.90 %
9mer_H2_Db 197 VDA FSVDKSILL GYV 1003.21 3.668 7.28 %
9mer_H2_Db 235 DPA FAKYVDDFV KEH 1085.23 3.403 6.76 %
9mer_H2_Db 85 KIK LVAVNAKTR GPL 953.14 3.346 6.64 %
9mer_H2_Db 177 VKF SEFPDYPSI KAA 1036.13 3.159 6.27 %
9mer_H2_Db 103 GSV DAVIATFTI TPE 932.08 3.14 6.23 %
9mer_H2_Db 75 LAK SILGDDKKI KLV 970.13 2.323 4.61 %
9mer_H2_Db 162 TKK AIGEAAKKI GID 882.07 1.216 2.41 %
9mer_H2_Db 23 AFS NANAAEGKL ESI 868.94 0.952 1.89 %
9mer_H2_Db 171 KKI GIDVKFSEF PDY 1023.16 0.901 1.79 %

Table 1b: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites of Peb1a from Campylobacter jejuni . The binding potential (score) of antigenic peptide to the MHC-1 Allele i.e. 9mer_H2_Db.

MHC-I Allele POS. N SEQUENCE C MW (Da) SCORE % OPT.
10mer_H2_Db 244 DFV KEHKNEIDAL AKK 1178.31 11.229 19.08 %
10mer_H2_Db 116 PER KRIYNFSEPY YQD 1298.48 10.554 17.93 %
10mer_H2_Db 161 TTK KAIGEAAKKI GID 1010.24 8.65 14.70 %
10mer_H2_Db 42 QLI VGVKNDVPHY ALL 1109.24 8.568 14.56 %
10mer_H2_Db 170 AKK IGIDVKFSEF PDY 1136.32 7.352 12.49 %
10mer_H2_Db 151 GAN IGVAQAATTK KAI 941.08 4.813 8.18 %
10mer_H2_Db 229 IVT KKDDPAFAKY VDD 1164.33 4.544 7.72 %
10mer_H2_Db 248 EHK NEIDALAKKW GL 1146.34 3.871 6.58 %
10mer_H2_Db 195 KRV DAFSVDKSIL LGY 1076.22 3.654 6.21 %
10mer_H2_Db 22 VAF SNANAAEGKL ESI 956.02 3.617 6.15 %
10mer_H2_Db 45 VGV KNDVPHYALL DQA 1151.33 2.711 4.61 %
10mer_H2_Db 154 IGV AQAATTKKAI GEA 984.15 1.993 3.39 %
10mer_H2_Db 138 LKE KKYKSLADMK GAN 1193.46 1.857 3.16 %
10mer_H2_Db 10 LLK LAVFALGACV AFS 945.19 1.677 2.85 %
10mer_H2_Db 62 GEI KGFEVDVAKL LAK 1087.28 0.783 1.33 %
10mer_H2_Db 233 KDD PAFAKYVDDF VKE 1154.3 0.665 1.13 %
10mer_H2_Db 177 VKF SEFPDYPSIK AAL 1164.3 0.417 0.71 %

Table 1c: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites of Peb1a from Campylobacter jejuni . The binding potential (score) of antigenic peptide to the MHC-1 Allele i.e. 10mer_H2_Db.

MHC-I Allele POS. N SEQUENCE C MW (Da) SCORE
11mer_H2_Db 116 PER KRIYNFSEPYY QDA 1461.66 20.317
11mer_H2_Db 160 ATT KKAIGEAAKKI GID 1138.41 19.105
11mer_H2_Db 61 TGE IKGFEVDVAKL LAK 1200.44 4.79
11mer_H2_Db 21 CVA FSNANAAEGKL ESI 1103.2 4.092
11mer_H2_Db 5 VFR KSLLKLAVFAL GAC 1184.53 3.721
11mer_H2_Db 9 SLL KLAVFALGACV AFS 1073.36 3.683
11mer_H2_Db 243 DDF VKEHKNEIDAL AKK 1277.44 3.405
11mer_H2_Db 197 VDA FSVDKSILLGY VDD 1223.44 2.702
11mer_H2_Db 41 GQL IVGVKNDVPHY ALL 1222.4 2.646
11mer_H2_Db 32 GKL ESIKSKGQLIV GVK 1183.41 2.248
11mer_H2_Db 122 YNF SEPYYQDAIGL LVL 1237.35 1.713
11mer_H2_Db 31 EGK LESIKSKGQLI VGV 1197.44 1.612
11mer_H2_Db 151 GAN IGVAQAATTKK AIG 1069.25 1.048
11mer_H2_Db 141 KKY KSLADMKGANI GVA 1129.33 0.812
11mer_H2_Db 214 KSE ILPDSFEPQSY GIV 1277.42 0.378

Table 1d: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites of Peb1a from Campylobacter jejuni . The binding potential (score) of antigenic peptide to the MHC-1 Allele i.e. 11mer_H2_Db.

MHC-II Allele POS. N SEQUENCE C MW (Da) SCORE % OPT.
MHC-II I_Ab 179 FSE FPDYPSIKA ALD 1019.18 13.645 38.29 %
MHC-II I_Ab 146 LAD MKGANIGVA QAA 842.01 11.916 33.44 %
MHC-II I_Ab 85 KIK LVAVNAKTR GPL 953.14 11.351 31.86 %
MHC-II I_Ab 19 GAC VAFSNANAA EGK 845.91 11.064 31.05 %
MHC-II I_Ab 18 LGA CVAFSNANA AEG 877.97 10.604 29.76 %
MHC-II I_Ab 121 IYN FSEPYYQDA IGL 1101.16 9.738 27.33 %
MHC-II I_Ab 21 CVA FSNANAAEG KLE 861.87 9.738 27.33 %
MHC-II I_Ab 179 FSE FPDYPSIKA ALD 1019.18 13.645 38.29 %

Table 2a: Prediction of MHCII ligands all rows highlighted in red represent predicted binders to the MHC-II Allele i.e. MHC-II I_Ab.

MHC-II Allele POS. N SEQUENCE C MW (Da) SCORE % OPT.
MHC-II I_Ad 15 VFA LGACVAFSN ANA 863.0 20.639 38.84 %
MHC-II I_Ad 155 GVA QAATTKKAI GEA 913.07 12.13 22.82 %
MHC-II I_Ad 103 GSV DAVIATFTI TPE 932.08 9.318 17.53 %
MHC-II I_Ad 170 AKK IGIDVKFSE FPD 989.14 8.149 15.33 %
MHC-II I_Ad 107 AVI ATFTITPER KRI 1017.15 7.964 14.99 %
MHC-II I_Ad 147 ADM KGANIGVAQ AAT 838.95 7.653 14.40 %
MHC-II I_Ad 62 GEI KGFEVDVAK LLA 974.12 7.529 14.17 %
MHC-II I_Ad 149 MKG ANIGVAQAA TTK 795.89 7.296 13.73 %

Table 2b: Prediction of MHCII ligands all rows highlighted in red represent predicted binders to the MHC-II Allele i.e. MHC-II I_Ad.

MHC-II Allele POS. N SEQUENCE C MW (Da) SCORE % OPT.
MHC-II I_Ag7 186 PSI KAALDAKRV DAF 953.15 14.202 34.75 %
MHC-II I_Ag7 230 VTK KDDPAFAKY VDD 1036.16 14.11 34.52 %
MHC-II I_Ag7 237 AFA KYVDDFVKE HKN 1124.26 14.021 34.30 %
MHC-II I_Ag7 162 TKK AIGEAAKKI GID 882.07 13.775 33.70 %
MHC-II I_Ag7 92 NAK TRGPLLDNG SVD 924.02 13.075 31.99 %
MHC-II I_Ag7 39 SKG QLIVGVKND VPH 967.12 10.196 24.95 %
MHC-II I_Ag7 248 EHK NEIDALAKK WGL 983.13 10.021 24.52 %
MHC-II I_Ag7 184 DYP SIKAALDAK RVD 898.07 9.809 24.00 %
MHC-II I_Ag7 85 KIK LVAVNAKTR GPL 953.14 9.195 22.50 %
MHC-II I_Ag7 192 LDA KRVDAFSVD KSI 1018.14 8.875 21.71 %

Table 2c: Prediction of MHCII ligands all rows highlighted in red represent predicted binders to the MHC-II Allele i.e. MHC-II I_Ag7.

Peptide Rank Start Position Sequence Score Predicted Affinity
1 143 LADMKGANI 8.646 High
2 92 TRGPLLDNG 8.639 High
3 100 GSVDAVIAT 8.632 High
4 235 FAKYVDDFV 8.627 High
5 63 GFEVDVAKL 8.626 High
6 62 KGFEVDVAK 8.624 High
7 153 VAQAATTKK 8.613 High
8 225 GIVTKKDDP 8.610 High
9 142 SLADMKGAN 8.595 High
10 17 ACVAFSNAN 8.591 High
11 233 PAFAKYVDD 8.590 High
12 159 TKKAIGEAA 8.588 High
13 67 DVAKLLAKS 8.587 High
14 122 SEPYYQDAI 8.584 High
15 193 RVDAFSVDK 8.584 High
16 83 IKLVAVNAK 8.563 High
17 61 IKGFEVDVA 8.539 High
18 134 VLKEKKYKS 8.529 High
19 79 DDKKIKLVA 8.527 High
20 41 IVGVKNDVP 8.526 High
21 212 SEILPDSFE 8.524 High
22 184 SIKAALDAK 8.523 High
23 23 NANAAEGKL 8.512 High
24 75 SILGDDKKI 8.463 High
25 66 VDVAKLLAK 8.446 High
26 158 TTKKAIGEA 8.443 High
27 226 IVTKKDDPA 8.434 High
28 74 KSILGDDKK 8.422 High
29 198 SVDKSILLG 8.407 High
30 50 HYALLDQAT 8.388 High
31 181 DYPSIKAAL 8.358 High
32 206 GYVDDKSEI 8.352 High
33 115 RKRIYNFSE 8.324 High
34 34 IKSKGQLIV 8.314 High
35 147 KGANIGVAQ 8.304 High
36 156 AATTKKAIG 8.276 High
37 33 SIKSKGQLI 8.249 High
38 157 ATTKKAIGE 8.231 High
39 125 YYQDAIGLL 8.231 High
40 201 KSILLGYVD 8.190 High
41 65 EVDVAKLLA 8.140 High
42 32 ESIKSKGQL 8.077 High
43 35 KSKGQLIVG 8.073 High
44 126 YQDAIGLLV 8.043 High
45 141 KSLADMKGA 8.038 High
46 223 SYGIVTKKD 7.936 High
47 180 PDYPSIKAA 7.915 High
48 139 KYKSLADMK 7.901 High
49 131 GLLVLKEKK 7.845 High
50 247 KNEIDALAK 7.790 High
51 29 GKLESIKSK 7.779 High
52 245 EHKNEIDAL 7.745 High
53 161 KAIGEAAKK 7.585 High
54 129 AIGLLVLKE 7.560 High
55 12 VFALGACVA 7.482 High
56 216 PDSFEPQSY 7.478 High
57 160 KKAIGEAAK 7.283 High
58 96 LLDNGSVDA 7.125 High
59 40 LIVGVKNDV 7.119 High
60 146 MKGANIGVA 7.044 High
61 228 TKKDDPAFA 7.033 High
62 249 EIDALAKKW 7.029 High
63 102 VDAVIATFT 6.991 High
64 44 VKNDVPHYA 6.974 High
65 52 ALLDQATGE 6.965 High
66 171 GIDVKFSEF 6.913 High
67 207 YVDDKSEIL 6.895 High
68 200 DKSILLGYV 6.890 High
69 10 LAVFALGAC 6.875 High
70 91 KTRGPLLDN 6.862 High
71 140 YKSLADMKG 6.776 High
72 149 ANIGVAQAA 6.694 High
73 57 ATGEIKGFE 6.693 High
74 183 PSIKAALDA 6.633 High
75 82 KIKLVAVNA 6.629 High
76 86 VAVNAKTRG 6.582 High
77 188 ALDAKRVDA 6.578 High
78 169 KIGIDVKFS 6.515 High
79 145 DMKGANIGV 6.477 High
80 119 YNFSEPYYQ 6.437 High

Table 3: cascade SVM based High affinity TAP Binders of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Flexibility-Prediction

Figure 8: Karplus and Schulz [28] Flexibility Prediction of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Sweet

Figure 9: Hydrophobicity plot of Sweet et al. [29] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Kyte-Doolittle

Figure 10: Kyte and Doolittle [30] hydrophobicity plot of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Abraham-Leo

Figure 11: Abraham and Leo [31] hydrophobicity plot of Peb1a from Campylobacter jejuni

bacteriology-parasitology-surface-tension

Figure 12: Bull and Breese [32] use surface tension to measure hydrophobicity and also uses negative values to describe the hydrophobicity of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Miyazawa

Figure 13: Hydrophobicity plot of Miyazawa et al. [33] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Roseman

Figure 14: Hydrophobicity plot of Roseman [34] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Wolfenden

Figure 15: Hydrophobicity plot of Wolfenden et al. [35] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Hydrophobicity-plot

Figure 16: Hydrophobicity plot of Roseman MA [34] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-Wilson

Figure 17: Hydrophobicity/HPLC plot of Wilson et al. [36] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Cowan

Figure 18: Hydrophobicity/HPLC pH 3.4/ plot of Cowan [37] of Peb1a from Campylobacter jejuni

bacteriology-parasitology-plot-Chothia

Figure 19: Hydrophobicity plot of Chothia [38] of Peb1a from Campylobacter jejuni

Discussion

Antigenecity is predicted by using Hopp and Woods ilicity scale to identify potentially antigenic sites in proteins by analyzing amino acid sequences in order to find the point of greatest hydrophilic. The Window size of 5-7 is good for finding hydrophilic regions, greater than 0 values are consider as hydrophilic which is consider as antigenic. Welling used information on the relative occurrence of amino acids in antigenic regions to make a scale which is useful for prediction of antigenic regions. Welling antigenicity plot gives value as the log of the quotient between percentage in sample of known antigenic regions and percentage in average proteins. Hydrophobicity plot of HPLC / Parker Hydrophilicity. BepiPred predicts the location of linear B-cell. There are 3 antigenic determinant sequences is found by Kolaskar and Tongaonkar antigenicity scales.

Result of determined antigenic sites on proteins has revealed that the hydrophobic residues if they occur on the surface of a protein are more likely to be a part of antigenic sites. This method can predict antigenic determinants with about 75% accuracy and also gives the information of surface accessibility and flexibility. Further this region form beta sheet which show high antigenic response than helical region of this peptide and shows highly antigenicity. X-Ray Diffraction with Resolution 1.49 Å 3D Structure of the Peb1a from Campylobacter jejuni is predicted by PDB vive. Sequence analysis of the chosen target and then structure determined the target experimentally to evaluate their similarity to known protein structures and to determine possible relationships that are identifiable from protein sequence alone.

The target structure will also serve as a detailed model for determining the structure of peptide within that protein structure. We predict Solvent accessibility by using Emini et al. [27], the result found the highest probability that a given protein region lies on the surface of a protein and are used to identify antigenic determinants on the surface of proteins. This algorithm also used to identify the antigenic determinants on the surface of proteins and Karplus and Schulz [28] predict backbone or chain flexibility on the basis of the known temperature B factors of the a-carbons.

We predict Solvent accessibility of Peb1a from Campylobacter jejuni for delineating hydrophobic and hydrophilic characteristics of amino acids. Solvent accessibility used to identify active site of functionally important residues in membrane proteins. Solvent-accessible surface areas and backbone angles are continuously varying because proteins can move freely in a three-dimensional space. The mobility of protein segments which are located on the surface of a protein due to an entropic energy potential and which seem to correlate well with known antigenic determinants. We also found hydrophobicity by Sweet et al. [29], Kyte and Doolittle [30], Abraham and Leo [31], Bull and Breese [32], Guy Miyazawa [33], Roseman [34], Wolfenden [35], Wilson et al. [36], Cowan [37], Chothia [38].

These scales are a hydrophilic with a polar residues assigned negative value. Because the N- and C- terminal regions of proteins are usually solvent accessible and unstructured, antibodies against those regions recognize the antigenic protein. In this study, we found predicted MHC-I peptide binders of Peb1a from Campylobacter jejuni for 8mer_H2_Db alleles, 9mer_H2_Db, 10mer_H2_Db with, 11mer_H2_Db and I_Ab, I_Ad, MHC-II I_Ag7 for MHC II allele was tasted. We also use a cascade SVM based TAPPred method which found 80 High affinity TAP Transporter peptide regions which represents predicted TAP binders residues which occur at N and C termini Peb1a from Campylobacter jejuni. TAP is an important transporter that transports antigenic peptides from cytosol to ER. TAP binds and translocate selective antigenic peptides for binding to specific MHC molecules. The efficiency of TAP-mediated translocation of antigenic peptides is directly proportional to its TAP binding affinity. Thus, by understanding the nature of peptides, that bind to TAP with high affinity, is important steps in endogenous antigen processing. The correlation coefficient of 0.88 was obtained by using jackknife validation test.

The MHCI and MHCII binding regions

T cell immune responses are derived by antigenic epitopes hence their identification is important for design synthetic peptide vaccine. T cell epitopes are recognized by MHCI molecules producing a strong defensive immune response against Peb1a from Campylobacter jejuni. Therefore, the prediction of peptide binding to MHCI molecules by appropriate processing of antigen peptides occurs by their binding to the relevant MHC molecules. Because, the C-terminus of MHCI-restricted epitopes results from cleavage by the proteasome and thus, proteasome specificity is important to determine T-cell epitopes. Consequently, RANKPEP also focus on the prediction of conserved epitopes. C-terminus of MHCI-restricted peptides is generated by the proteasome, and thus RANKPEP also determines whether the C-terminus of the predicted MHCI-peptide binders is the result of proteasomal cleavage. Moreover, these sequences are highlighted in purple in the output results. Proteasomal cleavage predictions are carried out using three optional models obtained applying statistical language models to a set of known epitopes restricted by human MHCI molecules as indicated here.

Conclusion

From the above result and discussion it is concluded that the increase in affinity of MHC binding peptides may result in enhancement of immunogenicity of Peb1a from Campylobacter jejuni and are helpful in the designing of synthetic peptide vaccine. This approach can help reduce the time and cost of experimentation for determining functional properties of Peb1a from Campylobacter jejuni. Overall, the results are encouraging, both the ‘sites of action’ and ‘physiological functions’ can be predicted with very high accuracies helping minimize the number of validation experiments.

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Citation: Sherkhane AS, Somnath W, Gomase VS (2014) Identification of Antigenic Determinants, Solvent Accessibility and MHC Binders of Peb1a from Campylobacter jejuni. J Bacteriol Parasitol 5:1000193.

Copyright: © 2014 Sherkhane AS, 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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