Research Article - (2014) Volume 5, Issue 4
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
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].
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].
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).
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).
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
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.
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.