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ISSN: 2157-7609
Journal of Drug Metabolism & Toxicology
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Identification of MHC Class, Transports Antigenic Peptides from Naja melanoleuca Long Neurotoxin 1

Sherkhane AS1, Changbhale SS1 and Gomase VS2*

1The Global Open University, Nagaland, India

2Dr Babasaheb Ambedkar Marathwada University, Aurangabad, India

*Corresponding Author:
Virendra S Gomase
Dr Babasaheb Ambedkar Marathwada University, Aurangabad, India
Tel: +91-9987770696
E-mail: [email protected]

Received Date: May 30, 2014; Accepted Date: July 23, 2014; Published Date: July 30, 2014

Citation: Sherkhane AS, Changbhale SS, Gomase VS (2014) Identification of MHC Class, Transports Antigenic Peptides from Naja melanoleuca Long Neurotoxin 1. J Drug Metab Toxicol 5:169. doi: 10.4172/2157-7609.1000169

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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Abstract

Long neurotoxin 1 is a dangerous protein occurs in N. melanoleuca. It is highly dangerous snake due to the quantity of venom inject in a single bite. Peptide fragments of N. Melanoleuca Long neurotoxin 1 antigen protein having 71 amino acids, which shows 63 nanomers can be used to select nanomers for use in synthetic peptide vaccine design and to increase the understanding of roles of the immune system against snake bite. We use to apply computational intelligence algorithm PSSM (Position Specific Scoring Matrices) for the Prediction of MHC class-I binding peptides, we also predict antigenicity, Solvent accessibility, polar and nonpolar residue to analyses the membrane-spanning regions (hydrophobic) or regions that are likely exposed on the surface of proteins (hydrophilic domains) that are potentially antigenic that allows potential drug targets to identify active sites, for protection of host form Snake bites and to design synthetic peptide vaccine.

Keywords

N. melanoleuca; Long neurotoxin 1; Antigenic peptides; MHC-Binders; Tap Pred; PSSM; Vaccine; Nanomers

Introduction

Naja melanoleuca (forest cobra, black cobra) is the largest in all the true cobra (Naja) species in the world [1,2]. It is highly dangerous snake due to the quantity of venom inject in a single bite and death can occur within 30 to 120 minutes of envenomation [3]. N. melanoleuca venom contains Long neurotoxin 1, which binds to muscular and neuronal nicotinic acetylcholine receptors and produces peripheral paralysis by blocking neuromuscular transmission at the postsynaptic site [4]. N. melanoleuca Long neurotoxin 1 antigenic peptides are most suitable for antigenic peptide vaccine development because an ample immune response can be generated even with single epitope. Major histocompatibility complex (MHC) molecules are cell surface proteins that binds to the peptides derived from host or antigenic proteins, and present them at the cell surface for recognition by T-cells [5,6]. T cell recognition is a fundamental mechanism of the adaptive immune system by which the host identifies and responds to foreign antigens [7,8]. There are two types of MHC molecule and are extremely polymorphic [9]. MHC class I molecules present peptides from intracellular proteins, which are targeted by proteasome, cleaved them into short peptides of 8-11 amino acids in length. These peptides are bound by the transmembrane peptide transporter (TAP) and translocate them from cytoplasm to endoplasmic reticulum, where they are bound by MHC molecule. The second and the C-terminal position of the peptide are the most important for binding [10,11]. These amino acids at each position contribute a certain binding energy [12]. These predicted MHC-binding peptides and T-cell epitopes helps improve our understanding of specificity of immune responses [13-15].

Materials and Methods

Database searching

The antigenic protein sequence of N. melanoleuca long neurotoxin 1 was retrieved from www.ncbi.nlm.nih.gov, Uni Prot databases are initially the most important [14-16].

Prediction of antigenicity

Prediction of antigenicity program predicts those segments from N. melanoleuca long neurotoxin 1 that are likely to be antigenic by eliciting an antibody response. Antigenic epitopes of N. melanoleuca long neurotoxin 1 are determined by using the Hopp and Woods, Welling, Parker, Bepipred, Kolaskar and Tongaonkar antigenicity methods [16-20].

Prediction of MHC binding peptide

The major histocompatibility complex (MHC) peptide binding of N. melanoleuca long neurotoxin 1 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 [21-28].

Prediction of antigenic peptides by cascade SVM based TAP Pred method

In the present study, we predict cascade SVM based several TAP binders which was based on the sequence and the features of amino acids [29]. We found the MHCI binding regions, the binding affinity of N. melanoleuca long neurotoxin 1.

Solvent accessible regions

We also 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 Emini et al. [30] and Karplus and Schulz [31]. 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., Kyte and Doolittle, Abraham and Leo, Bull and Breese, Miyazawa et al., Roseman, Wolfenden et al., Wilson et al., Cowan, Chothia [32-41].

Results and Discussion

A antigenic sequence of N. melanoleuca Long neurotoxin 1 is 71 residues long as- KRCYRTPDLKSQTCPPGEDLCYTKKWCADWCTSRGKVI ELGCVATCPKVKPYEQITCCSTDNCNPHPKMKP

Prediction of antigenic peptides

We predicted the antigenic determinants by finding the area of greatest local hydrophilicity. The Hopp-Woods scale Hydrophilicity Prediction Result Data was found to be high in position 4-5,8(1.014),9- 10,16-18 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 Prediction Result Data found high in position 7-8, 21-23(0.571) (Figure 2). We also study Hydrophobicity plot of HPLC/Parker Hydrophilicity Prediction Result Data found 10-KSQTCPP-16(4.143),11- SQTCPPG-17(4.143),12-QTCPPGE-18(4.329),13-TCPPGED- 19(4.900),56-TCCSTDN-62(5.243),57-CCSTDNC-63(4.700),58- CSTDNCN-64(5.500), 59-STDNCNP-65(5.600) (maximum), (Figure 3), Bepi Pred predicts the location of linear B-cell epitopes Result found that 4-Y-4,6-TPDLKSQTCPPGEDLC-21,47-PKVKPY-52, (Figure 4 and Table 1), Kolaskar and Tongaonkar [20] antigenicity methods Predicted peptides result found i.e. 9-LKSQTCPPGEDLCYTKKW-26, 34-RGKVIELGCVATCPKVKPYEQITCCSTD-61 (Figure 5 and Table 2). The maximal hydrophilicity region is assumed to be an antigenic site, having hydrophobic characteristics, because terminal regions of antigen protein are solvent accessible and unstructured; antibodies against those regions are also likely to recognize the native protein.

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Figure 1: Hydrophobicity plot of Hopp and Woods [16] of N. melanoleuca Long neurotoxin 1.

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Figure 2: Hydrophobicity plot of Welling et al. [17] of N. melanoleuca Long neurotoxin 1.

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Figure 3: Hydrophobicity plot of HPLC by Parker et al. [18] of N. melanoleuca Long neurotoxin 1.

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Figure 4: Bepipred Linear Epitope Prediction plot showing antibody recognized B-cell epitopes of N. melanoleuca Long neurotoxin 1.

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Figure 5: Kolaskar and Tongaonkar [20] antigenicity plot for the N. melanoleuca Long neurotoxin 1.

No. Start Position End Position Peptide Peptide Length
1 4 4 Y 1
2 6 21 TPDLKSQTCPPGEDLC 16
3 47 52 PKVKPY 6

Table 1: Predicted Antigenic epitopes of N. melanoleuca Long neurotoxin 1 Bepipred

No. Start Position End Position Peptide Peptide Length
1 9 26 LKSQTCPPGEDLCYTKKW 18
2 34 61 RGKVIELGCVATCPKVKPYEQITCCSTD 28

Table 2: Predicted Antigenic epitopes of N. melanoleuca Long neurotoxin 1.

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. Emini et al. [30] (Figure 6) predicts the highest probability i.e. found4-YRTPDL-9(2.103),5-RTPDLK- 10(2.684),47-PKVKPY-52(2.479),48-KVKPYE-53(2.777),49- VKPYEQ-54(2.405),64-NPHPKM-69(2.308),65-PHPKMK-70(2.871) (maximum), 66-HPKMKP-71(2.871), 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 [31] (Figure 7) High score is found in residue i.e. 7-PDLKSQT-13(1.084), 8-DLKSQTC-14(1.094 (maximum), 9-LKSQTCP-15(1.091), 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. [32] hydrophobicity prediction Result Data found high in position 23-24,39-41(0.367), Kyte and Doolittle result high in position 39-41(2.186),42-44, Abraham and Leo [34] result high in position 17-19,28-29,39-43(1.231),Bull and Breese [35] result high in position 13-15,59-65(0.546), Miyazawa et al. [36] result high in position 27-30,39-42(6.946),54-58, Roseman [37] result high in position 40-41(0.511),43-44, Wolfenden et al. [38] result high in position 43(0.177), Wilson et al. [39] 18-20, 28-30, 38-46(4.314), Cowan and Whittaker [40] 39-44(0.966), Chothia [41] 37-46 (0.453) (Figures 8-18).

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Figure 6: Emini et al. [30] surface accessibility prediction plot of N. melanoleuca Long neurotoxin 1.

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Figure 7: Karplus and Schulz [31] flexibility prediction of N. melanoleuca Long neurotoxin 1.

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Figure 8: Hydrophobicity plot of Sweet et al. [32] of N. melanoleuca Long neurotoxin 1.

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Figure 9: Kyte & Doolittle [33] hydrophobicity plot of N. melanoleuca Long neurotoxin 1.

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Figure 10: Abraham & Leo [34] hydrophobicity plot of N. melanoleuca Long neurotoxin 1.

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Figure 11: Bull & Breese [35] use surface tension to measure hydrophobicity and also uses negative values to describe the hydrophobicity of N. melanoleuca Long neurotoxin 1.

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Figure 12: Hydrophobicity plot of Guy of N. melanoleuca Long neurotoxin 1.

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Figure 13: Hydrophobicity plot of Miyazawa et al. [36] of N. melanoleuca Long neurotoxin 1.

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Figure 14: Hydrophobicity plot of Roseman [37] of N. melanoleuca Long neurotoxin 1.

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Figure 15: Hydrophobicity plot of Wolfenden et al. [38] of N. melanoleuca Long neurotoxin 1.

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Figure 16: Hydrophobicity/HPLC plot of Wilson et al. [39] of N. melanoleuca Long neurotoxin 1.

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Figure 17: Hydrophobicity/HPLC pH 3.4/ plot of Cowan [40] of N. melanoleuca Long neurotoxin 1.

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Figure 18: Hydrophobicity plot of Chothia [41] of N. melanoleuca Long neurotoxin 1.

Prediction of MHC binding peptide

We found binding of peptides to a number of different alleles using Position Specific Scoring Matrix. N. melanoleuca Long neurotoxin 1 sequence is 71 residues long, having 63 nanomers. MHC molecules are cell surface proteins, which actively participate in host immune reactions and involvement of MHC-I in response to almost all antigens. We have predicted MHC-I peptide binders of N. melanoleuca Long neurotoxin 1 was tested with on a set of 4 different alleles i.e. H2-Db (mouse) 8mer, H2-Db (mouse) 9mer, H2-Db (mouse) 10mer, H2-Db (mouse) 11mer (Tables 3a-3d). Here RANKPEP report 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. We also use a cascade SVM based TAP Pred method which found 20 High affinity TAP Transporter peptide regions which represents predicted TAP binders residues which occur at N and C termini from N. melanoleuca Long neurotoxin 1 (Table 4).

MHC-I Allele POS. N Sequence C MW (Da) Score % OPT.
8mer_H2_Db 42 ELG CVATCPKV KPY 802.01 15.402 29.34 %
8mer_H2_Db 31 ADW CTSRGKVI ELG 845.02 7.006 13.35 %
8mer_H2_Db 15 QTC PPGEDLCY TKK 874.98 4.918 9.37 %
8mer_H2_Db 33 WCT SRGKVIEL GCV 883.06 3.157 6.01 %
8mer_H2_Db 17 CPP GEDLCYTK KWC 910.01 2.172 4.14 %
8mer_H2_Db 48 TCP KVKPYEQI TCC 986.18 2.149 4.09 %
8mer_H2_Db 50 PKV KPYEQITC CST 963.12 0.227 0.43 %
8mer_H2_Db 2 K RCYRTPDL KSQ 1005.17 0.027 0.05 %
8mer_H2_Db 61 CST DNCNPHPK MKP 905.98 -4.024 -7.67 %
8mer_H2_Db 13 KSQ TCPPGEDL CYT 812.9 -5.168 -9.84 %
8mer_H2_Db 36 SRG KVIELGCV ATC 842.06 -5.296 -10.09 %
8mer_H2_Db 63 TDN CNPHPKMK P 936.15 -9.81 -18.69 %
8mer_H2_Db 43 LGC VATCPKVK PYE 827.04 -10.044 -19.13 %
8mer_H2_Db 23 LCY TKKWCADW CTS 973.17 -10.171 -19.38 %
8mer_H2_Db 27 KKW CADWCTSR GKV 900.03 -13.229 -25.20 %
8mer_H2_Db 45 CVA TCPKVKPY EQI 917.13 -13.527 -25.77 %
8mer_H2_Db 3 KR CYRTPDLK SQT 977.15 -14.346 -27.33 %
8mer_H2_Db 51 KVK PYEQITCC STD 938.09 -14.429 -27.49 %
8mer_H2_Db 19 PGE DLCYTKKW CAD 1015.22 -17.864 -34.03 %
8mer_H2_Db 14 SQT CPPGEDLC YTK 814.94 -20.054 -38.20 %

Table 3a: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites, 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 KSQ TCPPGEDLC YTK 916.04 11.234 22.31 %
9mer_H2_Db 60 CCS TDNCNPHPK MKP 1007.08 5.919 11.75 %
9mer_H2_Db 42 ELG CVATCPKVK PYE 930.18 4.654 9.24 %
9mer_H2_Db 2 K RCYRTPDLK SQT 1133.34 4.316 8.57 %
9mer_H2_Db 41 IEL GCVATCPKV KPY 859.06 1.441 2.86 %
9mer_H2_Db 62 STD NCNPHPKMK P 1050.25 -0.266 -0.53 %
9mer_H2_Db 30 CAD WCTSRGKVI ELG 1008.23 -0.46 -0.91 %
9mer_H2_Db 44 GCV ATCPKVKPY EQI 988.21 -3.842 -7.63 %
9mer_H2_Db 35 TSR GKVIELGCV ATC 899.11 -4.856 -9.64 %
9mer_H2_Db 47 ATC PKVKPYEQI TCC 1083.3 -4.938 -9.80 %
9mer_H2_Db 12 LKS QTCPPGEDL CYT 941.03 -5.15 -10.23 %
9mer_H2_Db 49 CPK VKPYEQITC CST 1062.25 -6.286 -12.48 %
9mer_H2_Db 14 SQT CPPGEDLCY TKK 978.12 -7.991 -15.87 %
9mer_H2_Db 32 DWC TSRGKVIEL GCV 984.16 -8.745 -17.36 %
9mer_H2_Db 16 TCP PGEDLCYTK KWC 1007.13 -8.946 -17.76 %
9mer_H2_Db 26 TKK WCADWCTSR GKV 1063.24 -10.603 -21.05 %
9mer_H2_Db 1 - KRCYRTPDL KSQ 1133.34 -10.828 -21.50 %
9mer_H2_Db 50 PKV KPYEQITCC STD 1066.26 -12.095 -24.01 %
9mer_H2_Db 22 DLC YTKKWCADW CTS 1136.35 -17.825 -35.39 %
9mer_H2_Db 18 PPG EDLCYTKKW CAD 1144.34 -18.176 -36.09 %

Table 3b: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites, 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 61 CST DNCNPHPKMK P 1165.34 2.595 4.41 %
10mer_H2_Db 49 CPK VKPYEQITCC STD 1165.39 2.44 4.15 %
10mer_H2_Db 11 DLK SQTCPPGEDL CYT 1028.11 0.818 1.39 %
10mer_H2_Db 1   KRCYRTPDLK SQT 1261.51 0.264 0.45 %
10mer_H2_Db 34 CTS RGKVIELGCV ATC 1055.3 -2.273 -3.86 %
10mer_H2_Db 40 VIE LGCVATCPKV KPY 972.22 -3.357 -5.70 %
10mer_H2_Db 13 KSQ TCPPGEDLCY TKK 1079.22 -4.556 -7.74 %
10mer_H2_Db 12 LKS QTCPPGEDLC YTK 1044.17 -6.559 -11.14 %
10mer_H2_Db 41 IEL GCVATCPKVK PYE 987.23 -9.316 -15.83 %
10mer_H2_Db 25 YTK KWCADWCTSR GKV 1191.41 -11.111 -18.88 %
10mer_H2_Db 59 TCC STDNCNPHPK MKP 1094.16 -13.201 -22.43 %
10mer_H2_Db 43 LGC VATCPKVKPY EQI 1087.34 -13.538 -23.00 %
10mer_H2_Db 31 ADW CTSRGKVIEL GCV 1087.3 -15.615 -26.53 %
10mer_H2_Db 48 TCP KVKPYEQITC CST 1190.42 -16.503 -28.04 %
10mer_H2_Db 29 WCA DWCTSRGKVI ELG 1123.32 -18.559 -31.53 %
10mer_H2_Db 46 VAT CPKVKPYEQI TCC 1186.44 -19.76 -33.57 %
10mer_H2_Db 17 CPP GEDLCYTKKW CAD 1201.39 -19.941 -33.88 %
10mer_H2_Db 15 QTC PPGEDLCYTK KWC 1104.25 -20.854 -35.43 %
10mer_H2_Db 21 EDL CYTKKWCADW CTS 1239.49 -25.799 -43.83 %

Table 3c: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites, 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 % OPT.
11mer_H2_Db 33 WCT SRGKVIELGCV ATC 1142.38 -0.276 -0.35 %
11mer_H2_Db 58 ITC CSTDNCNPHPK MKP 1197.3 -1.339 -1.68 %
11mer_H2_Db 12 LKS QTCPPGEDLCY TKK 1207.35 -2.425 -3.05 %
11mer_H2_Db 42 ELG CVATCPKVKPY EQI 1190.48 -7.703 -9.69 %
11mer_H2_Db 60 CCS TDNCNPHPKMK P 1266.44 -8.342 -10.49 %
11mer_H2_Db 47 ATC PKVKPYEQITC CST 1287.54 -8.838 -11.12 %
11mer_H2_Db 16 TCP PGEDLCYTKKW CAD 1298.51 -10.047 -12.64 %
11mer_H2_Db 45 CVA TCPKVKPYEQI TCC 1287.54 -11.861 -14.92 %
11mer_H2_Db 10 PDL KSQTCPPGEDL CYT 1156.28 -13.738 -17.28 %
11mer_H2_Db 28 KWC ADWCTSRGKVI ELG 1194.4 -14.642 -18.42 %
11mer_H2_Db 14 SQT CPPGEDLCYTK KWC 1207.39 -16.733 -21.05 %
11mer_H2_Db 48 TCP KVKPYEQITCC STD 1293.56 -16.815 -21.15 %
11mer_H2_Db 40 VIE LGCVATCPKVK PYE 1100.39 -18.496 -23.27 %
11mer_H2_Db 20 GED LCYTKKWCADW CTS 1352.65 -19.377 -24.38 %
11mer_H2_Db 39 KVI ELGCVATCPKV KPY 1101.34 -20.253 -25.48 %
11mer_H2_Db 24 CYT KKWCADWCTSR GKV 1319.58 -20.616 -25.93 %
11mer_H2_Db 30 CAD WCTSRGKVIEL GCV 1250.51 -21.4 -26.92 %
11mer_H2_Db 11 DLK SQTCPPGEDLC YTK 1131.25 -23.165 -29.14 %

Table 3d: Promiscuous MHC ligands, having C-terminal ends are proteosomal cleavage sites the binding potential (score) of antigenic peptide to the MHC-1 Allele i.e. 11mer_H2_Db.

Peptide Rank Start Position Sequence Score Predicted Affinity
1 42 CVATCPKVK 8.641 High
2 12 QTCPPGEDL 8.621 High
3 48 KVKPYEQIT 8.559 High
4 51 PYEQITCCS 8.444 High
5 4 YRTPDLKSQ 8.416 High
6 49 VKPYEQITC 8.411 High
7 41 GCVATCPKV 8.398 High
8 17 GEDLCYTKK 8.293 High
9 29 DWCTSRGKV 8.257 High
10 8 DLKSQTCPP 8.116 High
11 9 LKSQTCPPG 8.008 High
12 63 CNPHPKMKP 7.991 High
13 30 WCTSRGKVI 7.869 High
14 5 RTPDLKSQT 7.854 High
15 34 RGKVIELGC 7.813 High
16 25 KWCADWCTS 7.561 High
17 21 CYTKKWCAD 7.280 High
18 14 CPPGEDLCY 7.241 High
19 52 YEQITCCST 7.110 High
20 16 PGEDLCYTK 6.841 High

Table 4: Cascade SVM based High affinity TAP Binders of N. melanoleuca Long neurotoxin 1.

Prediction of protein secondary structure

The important concepts in secondary structure prediction are identified as: residue conformational propensities, sequence edge effects, moments of hydrophobicity, position of insertions and Deletions in aligned homologous sequence, moments of conservation, auto-correlation, residue ratios, secondary structure feedback effects, and filtering [42,43]. The Robson and Garnier method predicted the secondary structure of the N. melanoleuca Long neurotoxin 1. Each residue is assigned values for alpha helix, beta sheet, turns and coils using a window of 7 residues (Figure 19). 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.

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Figure 19: Secondary Structure of N. melanoleuca Long neurotoxin 1 showing helix (Red), Sheet (Blue), Coil (Pink) regions.

Discussion

The antigenic determinants predicted by finding the area of greatest local hydrophilicity. Hopp and Woods hydrophilicity scale is used to identify of potentially antigenic sites in proteins by analyzing amino acid sequences in order to find the point of greatest hydrophilic. Hydrophilicity Prediction result data found high in sequence position at 4-5, 8(1.014), 9-10, 16-18 in a protein this scale is basically a hydrophilic index where apolar residues have been assigned negative values. 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 scale is used information on the relative occurrence of amino acids in antigenic regions to make a scale which is useful for prediction of antigenic regions and the predicted result data found high in sequence position 7-8, 21-23(0.571). 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. We also study Hydrophobicity plot of HPLC/Parker Hydrophilicity Prediction Result Data found 10-KSQTCPP-16(4.143), 11-SQTCPPG- 17(4.143),12-QTCPPGE-18(4.329),13-TCPPGED-19(4.900),56- TCCSTDN-62(5.243),57-CCSTDNC-63(4.700),58-CSTDNCN- 64(5.500),59-STDNCNP-65(5.600) (maximum). BepiPred predicts the location of linear B-cell epitopes Result found that there are 3 predicted epitopes are found 4-Y-4,6-TPDLKSQTCPPGEDLC-21,47- PKVKPY-52 (Table 2). There are 2 antigenic determinant sequences is found by Kolaskar and Tongaonkar antigenicity scales the results show highest pick at position 9-LKSQTCPPGEDLCYTKKW-26, 34-RGKVIELGCVATCPKVKPYEQITCCSTD-61 (Figure 4). 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.

We predict Solvent accessibility by using Emani et al. [30] the result found the highest probability i.e. found 4-YRTPDL- 9(2.103),5-RTPDLK-10(2.684),47-PKVKPY-52(2.479),48-KVKPYE- 53(2.777),49-VKPYEQ-54(2.405),64-NPHPKM-69(2.308),65-PHPKMK-70(2.871) (maximum),66-HPKMKP-71(2.871), 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 predict backbone or chain flexibility on the basis of the known temperature B factors of the a-carbons here we found the result with High score is i.e. 7-PDLKSQT-13(1.084), 8-DLKSQTC-14(1.094 (maximum),9-LKSQTCP-15(1.091). We predict Solvent accessibility of N. melanoleuca Long neurotoxin 1 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 the i.e. Sweet et al. hydrophobicity prediction result data found high in position 23-24, 39-41(0.367), Kyte and Doolittle result high in position 39-41(2.186),42-44, Abraham & Leo result high in position 17-19,28-29,39-43(1.231), Bull and Breese result high in position 13-15,59-65(0.546), Guyresult high in position 4-5(0.627),7-10,13-15,50-51, Miyazawa result high in position 27-30, 39-42(6.946), 54-58, Roseman result high in position 40-41(0.511), 43- 44, Wolfenden result high in position 43(0.177), Wilson et al. 18-20,28- 30,38-46(4.314), Cowan 39-44 (0.966),Chothia 37-46 (0.453) (Figures 7-17). 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. Predicted MHC-I peptide binders of toxin protein for 8mer_H2_Db alleles with the consensus sequence QNWNCCTI that yields the maximum score i.e. 52.494, 9mer_H2_Db with, the consensus sequence FCIHNCDYM that yields the maximum score i.e. 50.365, 10mer_H2_Db with, the consensus sequence SGYYNFFWCL that yields the maximum score i.e. 58.858, 11mer_H2_Db with, the consensus sequence CGVYNFYYCCY that yields the maximum score i.e. 79.495. We also use a cascade SVM based TAP Pred method which found 20 High affinity TAP Transporter peptide regions which represents predicted TAP binders residues which occur at N and C termini from N. melanoleuca Long neurotoxin 1. 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. 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 N. melanoleuca Long neurotoxin 1. 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 specify is important for 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 ability of RANKPEP to predict MHC binding peptides, and thereby potential T-cell epitopes. The specificity of transporter associated with antigen processing (TAP) plays an important role in the transport of the antigenic peptide fragments of the proteolysed to the endoplasmic reticulum where they associate with the major histocompatibility complex (MHC) class I molecules. Therefore, prediction of TAP-binding peptides is highly helpful in identifying the MHC class I-restricted T-cell epitopes and hence useful in the synthetic peptide vaccine designing. Antigenic peptides should be located in solvent accessible regions containing both hydrophobic and hydrophilic residues. High peaks in the surface accessibility plot predict regions that have a higher chance of producing antibodies that can bind to native protein. This means the increase in affinity of MHC binding peptides may result in enhancement of immunogenicity of N. melanoleuca Long neurotoxin 1 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 N. melanoleuca Long neurotoxin 1. 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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