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In silico homology modelling and prediction of novel epitopic peptides from P24 protein of Haemonchus contortus
Gene 703 (2019) 102–111
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Gene journal homepage: www.elsevier.com/locate/gene
Short communication
In silico homology modelling and prediction of novel epitopic peptides from P24 protein of Haemonchus contortus Vedamurthy G.V.a,
T
⁎,1
a b
, Haseen Ahmada,1, Suneel Kumar Onterua, Vijay Kumar Saxenab
Animal Biochemistry Division, National Dairy Research Institute, ICAR-NDRI, Karnal, Haryana 132001, India Molecular Physiology Laboratory, Division of Physiology and Biochemistry, Central Sheep and Wool Research Institute, ICAR-CSWRI, Avikanagar 304501, India
ARTICLE INFO
ABSTRACT
Keywords: Haemonchus contortus HCP24 Excretory/secretory antigen MHC Homology modelling Epitopes
Haemonchus contortus (HC) causes Haemonchosis in sheep and goats, with high mortality and morbidity due to lack of effective vaccine and increasing resistance to anthelmintic drugs. The present study was aimed at developing the 3D model of HCP24 protein and to identify the candidate epitopic peptides for effective humoral and cell-mediated immune-response. The HCP24 protein was homology modelled using the Swiss server and developed model was validated by ERRAT, VERIFY3D, PROQ, RAMPAGE and PROCHECK servers. Linear and prominent antigenic epitopes were predicted by SVMTrip and Immuno-medicine group tool. Conformational Bcell epitopes were predicted by Ellipro. MHC-I and MHC-II binding peptides were predicted by MHCPRED2, MHC2PRED and Propred I server. Proteosomal cleavage sites were predicted by Netchop server, to assess the stability of peptides. Reverse and three frame translation was done by EMBOSS tool. Bepipred and IEDB analysis also confirmed that both the predicted peptides (pep-1 and pep-2) were important antigenic region but pep-1 should have better hydrophobicity and stability. The degree of confidence achieved on scientific validation of the generated 3D model of the protein allows us to prescribe its use for research purpose. We could determine the peptide Pep-1(EDCKCTNCVCSRDEAL) should be a conformational B cell epitope with high antigenic potential and should demonstrate good binding affinity with host MHC-II and MHC-I alleles as well as stability inside host. Thus, it could be an ideal vaccine candidate for developing sub-unit vaccine against the parasite and should be assessed for protective immune response by in vitro and in-vivo studies.
1. Introduction Haemonchosis is one of the predominant global parasitic disease of sheep and goat, which is caused by a highly pathogenic gastrointestinal nematode (GIN), H. contortus (Newton and Munn, 1999). Adult parasite and larva (L4 and L5 stages) larvae suck up to 30 μl of blood, causing anaemia and death in severe acute infection. H. contortus has negative effect both on the health of animals as well as of consumers due to reduction in production scores and presence of pharmacologically active residues in meat and milk respectively. H. contortus is one of the most dreaded parasites having world-wide occurrence. It demonstrates very good ability to adapt to a wide range of environments (Waller and
Chandrawanthani, 2005). Hence, haemonchosis is a continual threat in the wet tropic zones of both hemispheres, between latitudes 23.5°N and °S (O'Connor et al., 2006), especially in warmer months, which is conducive for egg hatching and larval development. Although H. contortus is endemic to the warm, wet conditions of the tropics/subtropics, but periodic outbreaks occur more widely during periods of transient environmental favourability. There is an apparently growing importance of this parasite in the temperate countries of Europe especially in U.K.: (Jackson and Coop, 2000), France (Hoste et al., 2002) as well as in Netherlands and Denmark (Waller and Chandrawanthani, 2005). The effective prevention of haemonchosis is essential for the sustainable management of sheep and goats. Chemical method is commonly
Abbreviations: Asp, aspartic acid; ASP2, Ancylostoma secreted protein 2; 3D, three dimensional; E/S, excretory/secretory; E. coli, Escherichia coli; FMD, foot and mouth disease; HC, Haemonchus contortus; HCP, Haemonchus contortus protein; MHC, major histocompatibility complex; GIN, gastrointestinal nematode; rHc23, recombinant Haemonchus contortus 23 kDa protein; H11, Haemonchus 110 kDa protein; H-gal-GP, Haemonchus galactose glycoprotein; HIV, human immunodeficiency virus; HPV, human papilloma virus; HCV, hepatitis C virus; HLA, human leukocyte antigen; kDa, kilo dalton; IC50, Inhibitory Concentration 50; Met, methionine; nM, nano moles; PDB, protein data bank; pI, isoelectric point; PMDB, protein model data base; PROQ, protein quality predictor; SVM, support vector machine ⁎ Corresponding author. E-mail address: [email protected] (G.V. Vedamurthy). 1 These authors have contributed equally in this work and these are the first authors. https://doi.org/10.1016/j.gene.2019.03.056 Received 20 December 2018; Received in revised form 23 March 2019; Accepted 25 March 2019 Available online 28 March 2019 0378-1119/ © 2019 Elsevier B.V. All rights reserved.
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employed for the control of H. contortus, because ease of administration and availability. However, anthelminthic resistance has been detected in several H. contortus strains (Van Wyk et al., 1997; Jackson and Coop, 2000; Kotze and Prichard, 2016; Lamb et al., 2017), and resistance is observed for bezimidazole (Drudge et al. 1964), salicylanilides (Rolfe et al., 1990), organophosphates (Green et al., 1981), macrocyclic lactones (Borgsteede et al., 2007), amino-acetonitrile derivatives (Mederos et al., 2014: Van den Brom et al., 2015). Thus, use of preventive vaccination to control the parasite should be a viable and alternative option for exploration. There are many studies describing antigenic potential of H. contortus' proteins for vaccine development but efficient vaccine candidates are very much limited, as only one commercial vaccine (Barbervax®) derived from nematode gut membrane glycoprotein is available till date, reportedly providing 65% protection against H. contortus infection. Protection trials with rHc23 (Somatic antigen) has shown to confer over 80% protection. Variable protection levels were reported with gut membrane proteins H11/H-gal-GP as well. (Tavernor et al., 1992; McLeod, 2004; De Matos et al., 2017). Unfortunately, none of the recombinant counterparts of the native antigens induced full protection. Therefore, there is an urgent need to screen potential antigenic candidates for effective vaccine development against H. contortus. Recently, peptide based vaccines are gaining more importance due to their efficacy as well as zero chances of reversion of virulence. Therefore epitopes/peptide based vaccines can be an alternative strategy for an efficient vaccine production, to induce positive humoral and cell mediated immune responses (Sesardic, 1993; Li et al., 2014). There are many peptide based vaccines which are under development to combat several disease, such for anthrax (Oscherwitz et al., 2010), hepatitis C virus (HCV) (Kolesanova et al., 2013), malaria (Epstein et al., 2007)], foot and mouth disease (FMD) (Volpina et al., 1993),
swine fever (Tarradas et al., 2011), influenza (Stanekova et al., 2011), human immunodeficiency virus (HIV) (Liu et al., 2007), human papilloma virus (HPV) (Solares et al., 2011). As far as Hemonchus contortus is concerned, parasite's Excretory/ Secretory (E/S) products are a continuous source of natural or exposed antigens to the host. The excretory/secretory (E/S) products of adult H. contortus comprise at least 100 polypeptides with molecular weights ranging from 10 to > 100 kDa. The E/S products of H. contortus larval stages were characterized after in vitro cultivation (Ray Gamble and Mansfield, 1996; Neilson, 1969). E/S proteins may originate from the pharyngeal glands, the excretory system, epithelial cells of the intestine (e.g. digestive enzymes), or rectal and vaginal cells (Bird and Bird, 1991). These molecules may perform diverse functions such as aid in tissue penetration and degradation of host proteins for nourishment (Cox et al., 1990; Karanu et al., 1993), modulation of host immune response, prevention of blood clotting (Joshi and Singh, 2000; Suchitra and Joshi, 2005), immune evasion as well as in moulting process has been reported (Hong et al., 1993; Loukas and Maizels, 2000). It is well established that parasite E/S products are primarily involved in the activation of both cellular and humoral arms of host immune system after initial encounter by host (Mohandas et al., 2015). Therefore, E/S products are considered as potential vaccine candidates for H. contortus (Wang et al., 2017). Among all the polypeptides of E/S products, one higher molecular weight protein H11/H-gal-GP (110–230 kDa) (Smith et al., 1993, 1997) and few low molecular weight (15–24 kDa) proteins were mainly studied for vaccine candidate assessment, banking on their potent immunogenic properties (Schallig et al., 1997; Gadahi et al., 2016). A few reports on 24 kDa protein of H. contortus suggested its antigenic property (Gadahi et al., 2016). Therefore, the HCP24 proteins may be one of the major antigenic proteins but the important peptides/ epitopes from the HCP24 protein are yet to be determined.
Fig. 1. (a): Amino acid sequences of HCP24 protein. (b) 3D model of HCP24 protein. (c): Secondary structure of HCP24 protein predicted by PSIPRED server representing the alpha helix, beta sheet or coil on the basis of colour.. (d): Ramachandran plot of HCP24 protein predicted by PROCHECK and RAMPAGE server in which 98.5% residues are present in most favoured and allowed regions. 103
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Fig. 1. (continued)
With the advancement in the field of bioinformatics, there are algorithms to pick up potential immunogenic B-cell and T-cell epitopes for sub-unit vaccine application and to also determine the conformation, flexibility, binding affinity of selected epitopic peptide with target molecule. Therefore, the main aim of the present study was to perform homology modelling and validation of the 3D structure for HCP24 protein and to predict potential epitopic vaccine candidates against H. contortus.
suitable template based on maximum identity and 3D structure of that related protein should be known by NMR or X-ray crystallography. A suitable protein template for 3D modelling of HCP24 protein was searched in PDB by Swiss server with default parameters. Based on maximum identity and lowest E-value, crystal structure of ASP2 (ancylostoma secreted protein 2) of human hookworm Necator americanus (PDB ID: 4nui.1) was selected as a template (Mason et al., 2014). The target and template sequences were aligned using ClustralW2 software (Shen et al., 2013). The aligned sequences were analysed and attuned manually to check the gaps and insertions. After selecting the template, modelling was done by Swiss model, an automated server that takes only amino acid sequences to build a 3D model (Schwede et al., 2003; Arnold et al., 2006).
2. Material and methods 2.1. 3-D modelling of the protein Construction of 3D model of H. contortus P24 protein (HCP24) was required to predict its potential conformational B-cell epitopes. The 3D model of HCP24 protein was not available in Protein Data Bank (PDB). Therefore, we aimed for constructing the 3D model of the protein. The amino acid sequences of HCP24 protein was retrieved from GenPept database (ID: AEG76952.1) of NCBI using the URL (https://www.ncbi. nlm.nih.gov/protein/AEG76952.1). Physiochemical properties like molecular weight, isoelectric point (pI), amino acid composition, estimated half-life and instability index were determined by ProtParam tool (http://web.expasy.org/protparam/). The secondary structure of the protein was predicted by PSIPRED server (http://bioinf.cs.ucl.ac. uk/psipred/). The model of the protein was constructed following homology modelling approach, which refers to constructing an atomicresolution model of the “target” protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein (Cavasotto and Phatak, 2009). It requires identifying a
2.2. Validation of constructed 3D model of HCP24 protein Once the 3D model was generated, the quality and reliability of the constructed model were checked by the default quality parameters of the ERRAT and VERIFY3D software. Packaging volume, hydrogen bonds, accessible surface area and dihedral angles were also predicted by the default parameters of the VADAR software (Willard et al., 2003). In addition, the PROCHECK and RAMPAGE software were used to validate the constructed 3D model of the protein by the Ramachandran plot, which judge the backbone conformation on the basis of phi/psi distribution and the presence of non-GLY residues at the disallowed regions in the model. The overall quality of protein is again checked by ProQ server. After complete evaluation and validation of the generated 3D model of HCP24 protein, it was successfully submitted in PMDB. 104
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Fig. 2. (a): ERRAT plot, in which x-axis represents the residues number and y-axis represents the error values. The quality of modelled HCP24 protein was very good with overall quality factor 97.382. The overall quality factor for a good quality model should be 95 or above, (b): VERIFY3D plot, in which x-axis represents the residues number and y-axis represents the average 3D-1D score. First and last 10 residues were not showing any fluctuation and error whereas rest all were showing. In this model, 82.5% residues had 3D-1D score > 0.2. It should he at least 80% (average 3D-1D score) to pass the model.
2.3. Linear B-cell epitope prediction
2.4. Conformational B-cell epitope prediction
The linear antigenic B-cell epitopes from the sequence of HCP24 protein were predicted by Support Vector Machine TriP tool which is based on the machine learning algorithm (Yao et al., 2012). Its linearity depends on the amino acid properties by assuming that hydrophilic regions of proteins are mainly found on the surface, so that they are potentially antigenic. Immuno-medicine Group tool (http://imed.med. ucm.es/Tools/antigenic.pl) was also used for the prediction of antigenic peptides in this protein sequence. This tool is based on Kolaskar and Tongaonkar method with approximately 80% accuracy as reported and the prediction is based on the table that reflects the existence of amino acids with available known segmental epitopes. The size of the segments should be at least 8 residues long (Kolaskar and Tongaonkar, 1990; Ingale, 2010). The Linear B cell epitopes were also evaluated by using BEPIPRED tools of immune epitope database with default settings. Bepipred used Hidden Markov model for the prediction of B cell epitopes (Larsen et al., 2006; Potocnakova et al., 2016).
Conformational B cell epitopes from the 3D model of HCP24 protein was predicted by ElliPro (http://tools.iedb.org/ellipro/). It is a webtool designed by Thornton's method together with MODELLER program of a residue clustering algorithm and Jmol viewer (Ponomarenko et al., 2008). The P24 protein model used in ElliPro was refined and validated by different tools/software as mentioned above (e.g., ERRAT, VERIFY3D, and ProQ). The ElliPro score of predicted peptides as conformational B-cell epitopes should be in the range of 0.5 to 0.8, and the maximum distance for residue clustering was defined as 6.0 Å (Gurung et al., 2012). 2.5. T-cell epitope prediction MHC-I binding peptides within the HCP24 protein were predicted by Propred-1 server (http://crdd.osdd.net/raghava/propred1/). It is a matrix based prediction server consisting of 47 MHC-I alleles. We used 105
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3. Results
Table 1 Predicted antigenic peptides of HCP24 protein by Immuno-medicine Group tool.
Number 1 2 3 4 5 6 7 8 9 10 a
Start Position Peptides 4 42 67 84 115 149 162 172 191 203
LATVALLMLLST AYRTLVAK RMLKVKYDC FAKKCVFAH KTVAAAESVDLWF GVGHYTQVVW NKIGCAVEW SDMTFVACEY PIYEVGN EDCKCTNCVCSRDEAL
3.1. Physiochemical properties and secondary structure conformation of the protein
En d Position 15 49 75 92 127 158 170 181 197 218
The physiochemical properties of HCP24 protein on the basis of ProtParam analysis revealed the molecular weight was 24,755 Da and isoelectric point was 5.22, indicating it as a negatively charged protein. In particular, the protein contained 24 negatively charged residues (Asp + Glu) and18 positively charged residues (Arg + Lys). Alanine, aspartate and glutamate were found to be rich in this protein. The computed instability index of 36.99 indicated that the protein is stable as the obtained value is less than the cut off of 40. Similarly, the Nterminal sequence containing M (Met) indicated that the half-life of this protein is 30 h in mammalian reticulocytes (in vitro), > 20 h in yeast (in vivo) and > 10 h in E. coli (in vivo). The secondary structure of HCP24 protein contained alpha helices (36.49%), random coils (34.68%) extended strands (20.27%) and 19 beta turns (8.56%) Fig. 1(c), in which the hydrophobic alanine and leucine were normally buried in the core protein, and the polar glutamate and asparagine were found more in alpha helix importing positive charge.
The peptides are predicted to be highly antigenic.
HLA–A20 cattle allele in this study as it was the only one cattle allele available on the server. Later, MHC-II promiscuous binding peptides were also predicted by MHC2PRED server (http://crdd.osdd.net/ raghava/mhc2pred/) with all 42 alleles available in the server. This server is based on an elegant machine learning technique of SVM method. Further MHCPRED2 (http://www.ddg-pharmfac.net/ mhcpred/MHCPred/) server was also used to predict MHC-II binding peptides of HCP24 protein with the selected DRB0101, DRB0401 and DRB0701 alleles. This server predicts the MHC-II and I binding peptide by measuring the half-maximal inhibitory concentration (IC50) value. The binding affinity is inversely proportional to IC50 value, meaning that lower the IC50 values, higher would be the binding affinity to host MHC alleles. The IC50 values are divided in three different parts i.e. high-affinity binding = IC50 < 50 nM, intermediate-affinity binding = IC50 < 500 nM and low-affinity binding = IC50 < 5000 nM (Guan et al., 2003; Gurung et al., 2012). The peptides having high and intermediate IC50 values were considered as strong binding epitopes whereas peptides having IC50 > 5000 nM were not considered to be binding to host alleles.
3.2. 3D modelling of the HCP24 protein Crystal structure of ASP2 (ancylostoma secreted protein 2) of Necator americanus (PDB ID: 4nui.1) was selected as a template for the 3D modelling of HCP24 protein in Swiss server. There were a total of 50 templates found by Swiss model server for the modelling of HCP24 protein. We selected 4nui.1 as a suitable template for the modelling of the targeted protein on the basis of maximum identity (47.60%), similarity (0.45), GMQE score (0.72) and presence of minimum number of gaps (only 1) and maximum query coverage of the alignment between the sequences of target and template. The sequence identity between HCP24 and the selected template was 46.89%, which is more than the required 30% sequence homology for generating useful models (Xiang, 2006). The total three models were constructed by Swiss model server in which we considered model 1 as a final model after assessing its GMQE score, global quality estimate, local quality estimate score of the model. The overall quality factor of the predicted HCP24 protein model (Fig. 1b) was 97.38 by the ERRAT. The predicted protein model with a quality score of 95 or above is considered as a good quality model as shown in Fig. 2(a). The predicted HCP24 model was also concurred by VERIFY3D showing 82.5% of the residues with an averaged 3D-1D score ≥ 0.2. At least, it should be 80% for a good model as shown in Fig. 2(b). Ramachandran assessment was done by PROCHECK and RAMPAGE servers (Lovell et al., 2003) and both the software showed 98.5% residues in most favoured and allowed region and only 1.5% residues in outlier regions, as shown in Fig. (1d). The quality of protein model was very good as assessed by ProQ server with the LG score of 2.844. The LG score > 2.5 shows very good model (Cristobal et al., 2001). After complete evaluation and validation, the generated model was successfully submitted in Protein model database with a PMDB ID: PM0081352.
2.6. Proteosomal cleavage sites prediction To explore the proteosomal cleavage sites in the selected peptides, total proteosomal cleavage sites were predicted in HCP24 protein by Netchop server and analysed manually on the basis of highest score above threshold (0.5). The NetChop server produces neural network predictions for cleavage sites of the proteasome. (Keşmir et al., 2002). 2.7. IEDB analysis of the protein Kolaskar and Tongaonkar antigenicity prediction method of the IEDB was used to analyse and evaluate the selected epitopes (pep-1 and pep-2) as it is a semi-empirical method which makes use of physicochemical properties of amino acid residues and their frequencies of occurrence in experimentally known segmental epitopes. The method also has high regard owing to claimed accuracy of 75%. The protein was evaluated using Kolaskar and Tangaonkar antigenicity method (Kolaskar and Tongaonkar, 1990) with a default threshold value 0.9. Hydrophilicity of the antigenic epitopes, which is an important parameter for accessibility of epitopes to antibodies, were evaluated using Parker Hydrophilicity method (Parker et al., 1986) at a threshold value of 1.88. Flexibility and Beta turns were checked using Karplus and Schulz Flexibility (Karplus and Schulz, 1985) and Chou and Fasman Beta-turn methods (Chou and Fasman, 1978) respectively, with a threshold of 1.00 for both.
3.3. Epitope prediction a) B-cell epitopes prediction 1) Antigenic peptides and linear B-cell epitopes prediction The whole sequence of HCP24 protein was analysed for antigenic peptide prediction due to lack of information on its structural and specific antigenic peptide attributes. 10 antigenic peptides were predicted by immune-medicine group tool (Table 1) with average antigenic propensity score of 1.0241. It means the segment greater than average antigenic propensity (1.0241) will be potentially antigenic. The highest peak is observed for peptide named pep-1 (EDCKCTNCVCSRDEAL) 106
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Fig. 3. Antigenic peptides plot in which x-axis represents the residues number and y-axis represent the average antigenic prosperity.
(lysine with score 0.57) positions. The selected pep-1 may be converted into two different segments of 8 residues after proteosomal cleavage. The 8 residues long peptide can also be used for antibody production as they do not loose antigenic activity. As 8 cleavage were observed in the pep-2 at position 4 (lysine with score 0.82), 7 (valine with score 0.64), 8 (alanine with score 0.51), 9–10 (lysine with score 0.88 and 0.91), 11 (methionine with score 0.95), 12–13 (lysine with score 0.96 and 0.92), Therefore, pep-2 has a disadvantage of proteosomal instability which precludes it from qualifying as an immunogenic peptide.
from amino acids 203 to 218 with an antigenic propensity score of 1.2 and the second highest peak for pep-2 (LATVALLMLLST) from amino acids 4 to 15 with an antigenic propensity of 1.19. Therefore, both peptides (Table 1 and Fig. 3) were predicted to be highly antigenic that can be considered for effective immunization or immune-diagnosis. Similarly, SVM trip identified 8 linear B-cell epitopes, out of which 4 could qualify to be antigenic as determined by the algorithm based on machine learning method (Table 2). Bepipred also confirmed that both pep-1 and pep-2 were important antigenic region as predicted earlier (Fig. 4). 2) Conformational B-cell epitopes prediction The conformational B-cell epitopes (Table 3) of HCP24 protein model were predicted by Ellipro. The highest score (0.762) was achieved by epitope no.1 (VGNPCTNNEDCKCTNCVCSRDEA) from amino acids 195 to 217. This predicted epitope also contained the segment of highly antigenic peptide-1 recommended by SVMTriP server and Immuno-medicine Group tool. Therefore, the highly antigenic region (EDCKCTNCVCSRDEAL) of this pep-1 was selected whereas the other antigenic pep-2 (LATVALLMLLST) was not predicted by Ellipro as a conformational B-cell epitopes. All the epitopes predicted by Ellipro were visualized in Jmol to show its 3D structure or relative orientation of protein and peptide molecule (Fig. 5). The amino acid positions of each predicted epitope was also confirmed by Jmol viewer.
d) IEDB analysis of the protein Kolaskar and Tongaonkar antigenicity prediction results revealed that both pep-1 and pep-2 are in the region of major antigenicity of the protein (Fig. 6(a). The results of Karpus hydrophilic prediction suggested that the region of pep-1 peptide was hydrophilic while pep-2 was not hydrophilic (Fig. 6(b). Again the pep-1 was much more flexible in comparison to pep-2 as analysed by the Chou and Fasman Beta-Turn prediction plot (Fig. 6(c). 4. Discussion The aim of the study was to identify the potent antigenic peptides of HCP24. Developing a successful vaccine against any pathogen requires the identification of potent antigenic B and T-cell epitopes/peptides, prior knowledge about binding interaction of these peptides to MHC alleles and host immune cells (Gurung et al., 2012; Assis et al., 2014). Identification of important peptidic epitopes does also contribute to the development of diagnostic test for the pathogens (Saxena et al., 2012). Such detailed information can be generated in silico with the help of various bioinformatics tools/software. The generated information can be used to test the predicted function of these peptides by in-vitro and in-vivo experiments. In the present study, we analysed the sequence of HCP24 protein by Protparam tool to get its detailed information like molecular weight, pI, amino acid composition, half-life and stability, which are important for antigenicity of any molecule (Abbas et al., 2017). HCP24 contained negatively charged residues i.e., alanine, aspartate and glutamate in higher amount, which are polar and hydrophilic in nature. It has been reported that hydrophilic amino acids are mainly found on the surface of antigen and constitute a major part of potential surface epitopes (Ingale, 2010) as they are accessible to surrounding solvent environment. Since they are potentially antigenic they may be useful in immunization and for early immune-diagnosis. Swiss model server was
b) T-cell epitope prediction The top ten MHC-I binding peptides of host were predicted by Propred-I on the basis of highest score (Table 4) whereas 214 MHC-II binding peptide were predicted by MHC2PRED server. We could observe the presence of both the peptides in the predicted peptides list within an allelic repository of 36 alleles in the algorithm except the other 6 alleles which are HLA-DR5, HLA-DR51, HLA-DRB1*02, HLADRB*1101, HLA-DRB*1105 and I-As. MHCPRED2 server also validated the binding ability of the selected peptides (Pep-1 and Pep-2) (Table 5). Pep-1 was predicted to be a good binder to both the MHC-I and II alleles whereas pep-2 was showing binding only with MHC-II alleles. c) Peptides stability prediction Netchop server was used to determine the proteosomal cleavage sites in HCP24 protein sequence as it's important to assess the stability of the immunogen in the host system. This server found a total of 55 cleavage sites in HCP24 protein sequence in which two sites were observed in the selected pep-1 at 211 (valine with score 0.57) and 218 107
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Table 2 Predicted B-cell epitopes of HCP24 protein by SVMTriP tool.
Rank 1 2 3
Start Epitopes 115 KTVAAAESVDLWFDELQQNG 141 MTMEVFNRGVGHYTQVVWQW
End Score 134 1.000 160 0.986
203 EDCKCTNCVCSRDEALCIAP
Recommended Yes Yes
222 0.926
Yes
4
35 TFVNKHNAYRTLVAKGEAKN
54 0.919
5
6 TVALLMLLSTSGHASMCPDT
25 0.897
Yes
6
93 NSYSDRNNWGQNLYMTSILN
112 0.856
No
7
60 GYAPKAARMLKVKYDCAIEE
79 0.736
No
8
167 AVEWCSDMTFVACEYDSAGN
186 0.715
No
No
The first four epitopes are recommended by software which are marked by flags. Fig. 4. The graph showing the results of lineal B-cell epitopes of HCP24 protein predicted by Bepipred software of IEDB in which the x-axis represents the position whereas y-axis represents score of predicted amino acids in the sequence. The red line is indicating the threshold value (0.5) for epitopes prediction and the yellow region is representing the linear B-cell epitopes in the sequence. Both the peptides (Pep-1 & Pep-2) were found to be linear B-cell epitopes. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Table 3 Conformational B-cell epitopes predicted by Ellipro server. S.No Epitopes
Start
End
1. 2. 3. 4. 5. 6. 7.
195 22 107 49 86 130 186
217 31 117 62 101 149 190
VGNPCTNNEDCKCTNCVCSRDEA CPDTNGMSDE MTSILNQNKTV KGEAKNAKEIGGYA KKCVFAHNSYSDRNNW LQQNGVPYDNVMTMEVFNRG NYMGM
used for modelling as it's fully automated and provides complete stoichiometry and the overall structure of the complex as inferred by homology modelling (Waterhouse et al., 2018). The constructed 3D model of HCP24 qualified to be a very good representative model for the protein and demonstrated chiefly alpha helical secondary conformation (36%) signifying the orderliness of the structure of the protein. Linear antigenic and conformational B-cell epitopes were generally suggested as the potential epitopes for immuno-response in the host (Ingale, 2010; Gurung et al., 2012; Assis et al., 2014). Therefore, to predict linear antigenic B-cell epitopes in HCP24 protein, we used SVMTrip tool. Among eight predicted linear antigenic B-cell epitopes, the top four in order of prediction were recommended to be the best antigenic peptides. However, we included fifth epitope also because it encompassed in the predicted segment of second highly antigenic
No. of residues 23 10 11 14 16 20 5
Score 0.762 0.747 0.714 0.698 0.658 0.609 0.56
peptide of the Immuno-medicine group algorithm (Table 1). The segments of first highly antigenic peptide (pep-1) predicted by Immunomedicine group were present in the epitope no. 3 of HCP24, which was identified by SVMTrip tool (Table 2). Therefore, we selected both, first highly antigenic peptide as pep-1 and second highly antigenic peptide as pep-2 in the whole P24 protein of H. contortus. Both the selected epitopes were also encompassed in the linear antigenic prediction region as suggested by Bepipred, giving further strength to our findings. The important prerequisite molecular event to initiate humoral and cell-mediated immune-response is binding of antigenic peptides with the host MHC-II and MHC-I molecules (Ingale, 2010; Gurung et al., 2012). Therefore, the binding of both the selected peptides to the HLAA20 cattle allele of MHC-I molecules was predicted by Propred-I. Among the selected peptides, only pep-1 segment was present in top ten 108
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Fig. 5. Conformational B-ell epitopes of IIaemonchus contortus P24 protein predicted by Ellipro from 3D structure template PDB 1D 4UWcIK in ball and stick model. In which yellow balls are the residues of predicted peptides and white sticks are the non-epitope residues of protein. Each epitope is predicted with residue number and position mentioned in Table 6: A: (VGNPCTNNEDCKCTNCVCSRDEA)195–217, B: (CPDTNGMSDE)22–31, C: (MTSILNQNKTV)107–117, D: KGEAKNAKEIGGYA) 49–62, F: (KKCVFAHNSYSDRNNW)86–101. F: (LQQNGVPYDNVMTMEVFNRG)130–149, G: (NYMGM)186–190. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Table 4 Predicted MHC-I binding peptides of HCP24 protein by Propred-I server. Rank
Peptides
1 2 3 4 5 6 7 8 9 10
AKGEAKNAK NKHNAYRTL LKVKYDCAI VMTMEVFNR AKKCVFAHN KKCVFAHNS NKTVAAAES NKIGCAVEW CKCTNCVCS TNGMSDEVR
Residue No. 48 38 69 140 85 86 114 162 205 25
Real Score
Log Score
1000.000 500.000 300.000 200.000 100.000 100.000 100.000 100.000 100.000 80.000
6.9078 6.2146 5.7038 5.2983 4.6052 4.6052 4.6052 4.6052 4.6052 4.3820
predicted peptides of HCP24 towards MHC-1 binding. The pep-2 did not show any binding ability to HLA-A20 cattle allele of MHC-I molecules. The HLA-A20 allele was selected because it is the only one allele of ruminant (cattle) available in the database. However, both the peptides (Pep-1 and Pep-2) showed good binding affinity with 36 alleles of MHC-II as predicted by MHCPRED2 server. MHC2PRED server also shows that both the selected peptides had a good binding ability with MHC-II DRB0101 allele and intermediate binding with DRB0401 and DRB0701 alleles. However, Ellipro server also predicted only pep-1
Table 5 Predicted MHC-II binding peptides of HCP24 protein by MHCPRED2 server. Allele
Peptides
Start
End
No. of residues
DRB0101
FSLATVALL CSRDEALCI FSLATVALL CKCTNCVCS FSLATVALL CKCTNCVCS
2 212 2 205 2 205
10 220 10 213 10 213
9 9 9 9 9 9
DRB0401 DRB0701
% of Highest on log scale 83.29 74.93 68.77 63.88 55.52 55.52 55.52 55.52 55.52 52.83
Predicted IC50 Value (nM) 1.88 3.21 63.68 203.24 101.86 100.69
Table 6 Overlapping sequences of selected peptide by different tools/software. Peptide/Epitope B cell Antigenic MHCI MHCII Conformational B cell
Sequence EDCKCTNCVCSRDEALCIAP EDCKCTNCVCSRDEAL CKCTNCVCS CKCTNCVCS VGNPCTNNEDCKCTNCVCSR DEA 109
Position 203-222 203-218 205-213 205-203 195-217
Tools/software SVMTrip Immuno-medicine Propred I MHCPRED2 Ellipro
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Fig. 6. (a): Antigenicity Prediction (b) Hydrophilicity Prediction (c) Beta turns & Flexibility Prediction by IEDB. The x-axis in the graph representing the position whereas y-axis signifies the score of predicted amino acids in the sequence. The red line is indicating the threshold value for epitopes prediction and the yellow region is representing the predicted epitopes in the sequence. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
(with highest score 0.762) as a conformational B cell epitope (Table 3 and Fig. 4). Therefore, pep-1 can be strongly hypothesized to be good in eliciting a very strong humoral and cellular immune-response owing to its binding ability with both MHC-I and MHC-II, whereas the pep-2 can be used only for humoral response. Proteosomal cleavage analysis suggested that pep-1 may be a stable peptide inside the host since it contains only two protease cleavage sites at 211 (valine) and 218 (lysine) positions. After cleavage, this peptide may be converted into two segments of 8 residues each. Hence both the 8 residues peptide can also be used for eliciting antibody as well as cell mediated immune response. It was observed that as many as 8 cleavage sites were identified in pep-2 at lysine, valine, alanine, and methionine positions with more than basal threshold score (> 0.5). Therefore, pep2 may not be a good antigenic peptide due to the presence of many proteosomal cleavage sites and may undergo a rapid cleavage in host gut or in the enzymatic environment. Kolaskar and Tongaonkar antigenicity prediction method also confirmed that both pep-1 and pep-2 should be the potential epitopes. Pep1 was found also to be superior than pep-2 as far as hydrophilicity and flexibility of the peptide is concerned which gives better accessibility and flexibility to interact with its corresponding paratope on the antibody molecule.
(pep-1) was concluded to be a very good antigenic peptide candidate for subunit vaccine in Haemonchus contortus. This peptide may also be helpful for immuno-diagnosis of H. contortus infection because the peptide based diagnosis of parasitic diseases is nowadays a cheaper, simpler and reproducible strategy for large scale testing. Acknowledgement Authors are thankful to Department of Science and Technology, Govt. of India for the financial assistance (Grant number-ECR/2016/ 000135). References Abbas, A., Lichtman, A.H., Pillai, S., 2017. Cellular and Molecular Immunology. Elsevier (608 pp.). Arnold, K., Bordoli, L., Kopp, J., Schwede, T., 2006. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22 (2), 195–201. Assis, L.M.D., Sousa, J.R., Pinto, N.F.S., Silva, A.A., Vaz, A.F.D.M., Andrade, P.P., De Melo, M.A., 2014. B-cell epitopes of antigenic proteins in Leishmania infantum: an in silico analysis. Parasite Immunol. 36 (7), 313–323. Bird, A. F., & Bird, J. (1991). The Structure of Nematodes, 2nd edition. Academic Press Ltd., London. Pg, 167–229. Borgsteede, F.H., Dercksen, D.D., Huijbers, R., 2007. Doramectin and albendazole resistance in sheep in the Netherlands. Vet. Parasitol. 144, 180–183. Cavasotto, C.N., Phatak, S.S., 2009. Homology modeling in drug discovery: current trends and applications. Drug Discov. Today 14, 676–683. Chou, P.Y., Fasman, G.D., 1978. Empirical predictions of protein conformation. Annu. Rev. Biochem. 47 (1), 251–276. Cox, G.N., Pratt, D., Hageman, R., Biosvenue, R.J., 1990. Molecular cloning and primary sequencing of a cysteine protease expressed by Haemonchus contortus adult worms. Mol. Biochem. Parasitol. 41, 25–34. Cristobal, S., Zemla, A., Fischer, D., Rychlewski, L., Elofsson, A., 2001. A study of quality measures for protein threading models. BMC Bioinf. 2 (1), 5.
5. Conclusion In summary, the 3D model of HCP24 protein was successfully constructed and validated. In addition, we predicted two potential antigenic peptides (pep-1 and pep-2) of HCP24 protein. However, on the basis of stability prediction in the host, very good binding affinity with host MHC-I and II alleles, hydrophilicity and the flexibility, the peptide 110
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of major trichostrongylid parasites of sheep. Vet. Parasitol. 42, 1–15. Oscherwitz, J., Yu, F., Cease, K.B., 2010. A synthetic peptide vaccine directed against the 2β2–2β3 loop of domain 2 of protective antigen protects rabbits from inhalation anthrax. J. Immunol. 1001749. Parker, J.M.R., Guo, D., Hodges, R.S., 1986. New hydrophilicity scale derived from highperformance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry 25 (19), 5425–5432. Ponomarenko, J., Bui, H.H., Li, W., Fusseder, N., Bourne, P.E., Sette, A., Peters, B., 2008. ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinf. 9 (1), 514. Potocnakova, L., Bhide, M., Pulzova, L.B., 2016. An introduction to B-cell epitope mapping and in silico epitope prediction. J Immunol Res 2016. Ray Gamble, H., Mansfield, L.S., 1996. 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Wang, C., Li, F., Zhang, Z., Yang, X., Ahmad, A.A., Li, X., Hu, M., 2017. Recent research Progress in China on Haemonchus contortus. Front. Microbiol. 8, 1509. Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Lepore, R., 2018. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 46 (W1), W296–W303. Willard, L., Ranjan, A., Zhang, H., Monzavi, H., Boyko, R.F., Sykes, B.D., Wishart, D.S., 2003. VADAR: a web server for quantitative evaluation of protein structure quality. Nucleic Acids Res. 31 (13), 3316–3319. Xiang, Z., 2006. Advances in homology protein structure modeling. Curr. Protein Pept. Sci. 7 (3), 217–227. Yao, B., Zhang, L., Liang, S., Zhang, C., 2012. SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity. PLoS One 7 (9), e45152.
De Matos, A.F.I.M., Nobre, C.O.R., Monteiro, J.P., Bevilaqua, C.M.L., Smith, W.D., Teixeira, M., 2017. Attempt to control Haemonchus contortus in dairy goats with Barbervax®, a vaccine derived from the nematode gut membrane glycoproteins. Small Rumin. Res. 151, 1–4. Drudge, J.H., Szanto, J., Wyant, Z.N., Elam, G., 1964. Field studies on parasite control in sheep: comparison of thiabendazole, ruelene, and phenothiazine. Am. J. Vet. Res. 25, 1512–1518. Epstein, J.E., Giersing, B., Mullen, G., Moorthy, V., Richie, T.L., 2007. Malaria vaccines: are we getting closer? Curr. Opin. Mol. Ther. 9 (1), 12–24. Gadahi, J.A., Yongqian, B., Ehsan, M., Zhang, Z.C., Wang, S., Yan, R.F., Li, X.R., 2016. Haemonchus contortus excretory and secretory proteins (HcESPs) suppress functions of goat PBMCs in vitro. Oncotarget 7 (24), 35670. Green, P.E., Forsyth, B.A., Rowan, K.J., Payne, G., 1981. The isolation of a field strain of Haemonchus contortus in Queensland showing multiple anthelmintic resistance. Aust. Vet. J. 57, 79–84. Guan, P., Doytchinova, I.A., Zygouri, C., Flower, D.R., 2003. MHCPred: a server for quantitative prediction of peptide–MHC binding. Nucleic Acids Res. 31 (13), 3621–3624. Gurung, R.B., Purdie, A.C., Begg, D.J, Whittington, R.J., 2012. In silico identification of epitopes in Mycobacterium avium subsp paratuberculosis proteins that were upregulated under stress conditions. Clin. Vaccine Immunol. 19 (6), 855–864. Hong, X., Bouvier, J., Wong, M.M., Yamagata, G.Y.L., McKerrow, J.H., 1993. Brugia pahangi: identification and characterization of an aminopeptidase associated with larval molting. Exp.Parasitol 76, 127–133. Hoste, H., Chartier, C., Le Frileux, Y., 2002. Control of gastrointestinal parasitism with nematodes by treating the host category at risk. Vet. Res. 33, 531–545. Ingale, A.G., 2010. In-silico homology modeling and epitope prediction of nucleocapsid protein region from Japanese encephalitis virus. J. Comput. Sci. Syst. Biol 3, 53–58. 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Kolesanova, E.F., Sanzhakov, M.A., Kharybin, O.N., 2013. Development of the schedule for multiple parallel “difficult” peptide synthesis on pins. Int. J. Pept. 2013. Kotze, A.C., Prichard, R.K., 2016. Anthelmintic resistance in Haemonchus contortus: History, mechanisms and diagnosis. In: Advances in Parasitology. vol. 93. pp. 397–428. Lamb, J., Elliott, T., Chambers, M., Chick, B., 2017. Broad spectrum anthelmintic resistance of Haemonchus contortus in northern NSW of Australia. Vet. Parasitol. 241, 48–51. Larsen, J.E.P., Lund, O., Nielsen, M., 2006. Improved method for predicting linear B-cell epitopes. Immunol. Res. 2 (1), 2. Li, W., Joshi, M., Singhania, S., Ramsey, K., Murthy, A., 2014. Peptide vaccine: progress and challenges. Vaccines 2 (3), 515–536. Liu, Y., McNevin, J., Zhao, H., Tebit, D.M., Troyer, R.M., McSweyn, M., Mullins, J.I., 2007. Evolution of human immunodeficiency virus type 1 cytotoxic T-lymphocyte epitopes: fitness-balanced escape. J. Virol. 81 (22), 12179–12188. 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Short communication
In silico homology modelling and prediction of novel epitopic peptides from P24 protein of Haemonchus contortus Vedamurthy G.V.a,
T
⁎,1
a b
, Haseen Ahmada,1, Suneel Kumar Onterua, Vijay Kumar Saxenab
Animal Biochemistry Division, National Dairy Research Institute, ICAR-NDRI, Karnal, Haryana 132001, India Molecular Physiology Laboratory, Division of Physiology and Biochemistry, Central Sheep and Wool Research Institute, ICAR-CSWRI, Avikanagar 304501, India
ARTICLE INFO
ABSTRACT
Keywords: Haemonchus contortus HCP24 Excretory/secretory antigen MHC Homology modelling Epitopes
Haemonchus contortus (HC) causes Haemonchosis in sheep and goats, with high mortality and morbidity due to lack of effective vaccine and increasing resistance to anthelmintic drugs. The present study was aimed at developing the 3D model of HCP24 protein and to identify the candidate epitopic peptides for effective humoral and cell-mediated immune-response. The HCP24 protein was homology modelled using the Swiss server and developed model was validated by ERRAT, VERIFY3D, PROQ, RAMPAGE and PROCHECK servers. Linear and prominent antigenic epitopes were predicted by SVMTrip and Immuno-medicine group tool. Conformational Bcell epitopes were predicted by Ellipro. MHC-I and MHC-II binding peptides were predicted by MHCPRED2, MHC2PRED and Propred I server. Proteosomal cleavage sites were predicted by Netchop server, to assess the stability of peptides. Reverse and three frame translation was done by EMBOSS tool. Bepipred and IEDB analysis also confirmed that both the predicted peptides (pep-1 and pep-2) were important antigenic region but pep-1 should have better hydrophobicity and stability. The degree of confidence achieved on scientific validation of the generated 3D model of the protein allows us to prescribe its use for research purpose. We could determine the peptide Pep-1(EDCKCTNCVCSRDEAL) should be a conformational B cell epitope with high antigenic potential and should demonstrate good binding affinity with host MHC-II and MHC-I alleles as well as stability inside host. Thus, it could be an ideal vaccine candidate for developing sub-unit vaccine against the parasite and should be assessed for protective immune response by in vitro and in-vivo studies.
1. Introduction Haemonchosis is one of the predominant global parasitic disease of sheep and goat, which is caused by a highly pathogenic gastrointestinal nematode (GIN), H. contortus (Newton and Munn, 1999). Adult parasite and larva (L4 and L5 stages) larvae suck up to 30 μl of blood, causing anaemia and death in severe acute infection. H. contortus has negative effect both on the health of animals as well as of consumers due to reduction in production scores and presence of pharmacologically active residues in meat and milk respectively. H. contortus is one of the most dreaded parasites having world-wide occurrence. It demonstrates very good ability to adapt to a wide range of environments (Waller and
Chandrawanthani, 2005). Hence, haemonchosis is a continual threat in the wet tropic zones of both hemispheres, between latitudes 23.5°N and °S (O'Connor et al., 2006), especially in warmer months, which is conducive for egg hatching and larval development. Although H. contortus is endemic to the warm, wet conditions of the tropics/subtropics, but periodic outbreaks occur more widely during periods of transient environmental favourability. There is an apparently growing importance of this parasite in the temperate countries of Europe especially in U.K.: (Jackson and Coop, 2000), France (Hoste et al., 2002) as well as in Netherlands and Denmark (Waller and Chandrawanthani, 2005). The effective prevention of haemonchosis is essential for the sustainable management of sheep and goats. Chemical method is commonly
Abbreviations: Asp, aspartic acid; ASP2, Ancylostoma secreted protein 2; 3D, three dimensional; E/S, excretory/secretory; E. coli, Escherichia coli; FMD, foot and mouth disease; HC, Haemonchus contortus; HCP, Haemonchus contortus protein; MHC, major histocompatibility complex; GIN, gastrointestinal nematode; rHc23, recombinant Haemonchus contortus 23 kDa protein; H11, Haemonchus 110 kDa protein; H-gal-GP, Haemonchus galactose glycoprotein; HIV, human immunodeficiency virus; HPV, human papilloma virus; HCV, hepatitis C virus; HLA, human leukocyte antigen; kDa, kilo dalton; IC50, Inhibitory Concentration 50; Met, methionine; nM, nano moles; PDB, protein data bank; pI, isoelectric point; PMDB, protein model data base; PROQ, protein quality predictor; SVM, support vector machine ⁎ Corresponding author. E-mail address: [email protected] (G.V. Vedamurthy). 1 These authors have contributed equally in this work and these are the first authors. https://doi.org/10.1016/j.gene.2019.03.056 Received 20 December 2018; Received in revised form 23 March 2019; Accepted 25 March 2019 Available online 28 March 2019 0378-1119/ © 2019 Elsevier B.V. All rights reserved.
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employed for the control of H. contortus, because ease of administration and availability. However, anthelminthic resistance has been detected in several H. contortus strains (Van Wyk et al., 1997; Jackson and Coop, 2000; Kotze and Prichard, 2016; Lamb et al., 2017), and resistance is observed for bezimidazole (Drudge et al. 1964), salicylanilides (Rolfe et al., 1990), organophosphates (Green et al., 1981), macrocyclic lactones (Borgsteede et al., 2007), amino-acetonitrile derivatives (Mederos et al., 2014: Van den Brom et al., 2015). Thus, use of preventive vaccination to control the parasite should be a viable and alternative option for exploration. There are many studies describing antigenic potential of H. contortus' proteins for vaccine development but efficient vaccine candidates are very much limited, as only one commercial vaccine (Barbervax®) derived from nematode gut membrane glycoprotein is available till date, reportedly providing 65% protection against H. contortus infection. Protection trials with rHc23 (Somatic antigen) has shown to confer over 80% protection. Variable protection levels were reported with gut membrane proteins H11/H-gal-GP as well. (Tavernor et al., 1992; McLeod, 2004; De Matos et al., 2017). Unfortunately, none of the recombinant counterparts of the native antigens induced full protection. Therefore, there is an urgent need to screen potential antigenic candidates for effective vaccine development against H. contortus. Recently, peptide based vaccines are gaining more importance due to their efficacy as well as zero chances of reversion of virulence. Therefore epitopes/peptide based vaccines can be an alternative strategy for an efficient vaccine production, to induce positive humoral and cell mediated immune responses (Sesardic, 1993; Li et al., 2014). There are many peptide based vaccines which are under development to combat several disease, such for anthrax (Oscherwitz et al., 2010), hepatitis C virus (HCV) (Kolesanova et al., 2013), malaria (Epstein et al., 2007)], foot and mouth disease (FMD) (Volpina et al., 1993),
swine fever (Tarradas et al., 2011), influenza (Stanekova et al., 2011), human immunodeficiency virus (HIV) (Liu et al., 2007), human papilloma virus (HPV) (Solares et al., 2011). As far as Hemonchus contortus is concerned, parasite's Excretory/ Secretory (E/S) products are a continuous source of natural or exposed antigens to the host. The excretory/secretory (E/S) products of adult H. contortus comprise at least 100 polypeptides with molecular weights ranging from 10 to > 100 kDa. The E/S products of H. contortus larval stages were characterized after in vitro cultivation (Ray Gamble and Mansfield, 1996; Neilson, 1969). E/S proteins may originate from the pharyngeal glands, the excretory system, epithelial cells of the intestine (e.g. digestive enzymes), or rectal and vaginal cells (Bird and Bird, 1991). These molecules may perform diverse functions such as aid in tissue penetration and degradation of host proteins for nourishment (Cox et al., 1990; Karanu et al., 1993), modulation of host immune response, prevention of blood clotting (Joshi and Singh, 2000; Suchitra and Joshi, 2005), immune evasion as well as in moulting process has been reported (Hong et al., 1993; Loukas and Maizels, 2000). It is well established that parasite E/S products are primarily involved in the activation of both cellular and humoral arms of host immune system after initial encounter by host (Mohandas et al., 2015). Therefore, E/S products are considered as potential vaccine candidates for H. contortus (Wang et al., 2017). Among all the polypeptides of E/S products, one higher molecular weight protein H11/H-gal-GP (110–230 kDa) (Smith et al., 1993, 1997) and few low molecular weight (15–24 kDa) proteins were mainly studied for vaccine candidate assessment, banking on their potent immunogenic properties (Schallig et al., 1997; Gadahi et al., 2016). A few reports on 24 kDa protein of H. contortus suggested its antigenic property (Gadahi et al., 2016). Therefore, the HCP24 proteins may be one of the major antigenic proteins but the important peptides/ epitopes from the HCP24 protein are yet to be determined.
Fig. 1. (a): Amino acid sequences of HCP24 protein. (b) 3D model of HCP24 protein. (c): Secondary structure of HCP24 protein predicted by PSIPRED server representing the alpha helix, beta sheet or coil on the basis of colour.. (d): Ramachandran plot of HCP24 protein predicted by PROCHECK and RAMPAGE server in which 98.5% residues are present in most favoured and allowed regions. 103
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Fig. 1. (continued)
With the advancement in the field of bioinformatics, there are algorithms to pick up potential immunogenic B-cell and T-cell epitopes for sub-unit vaccine application and to also determine the conformation, flexibility, binding affinity of selected epitopic peptide with target molecule. Therefore, the main aim of the present study was to perform homology modelling and validation of the 3D structure for HCP24 protein and to predict potential epitopic vaccine candidates against H. contortus.
suitable template based on maximum identity and 3D structure of that related protein should be known by NMR or X-ray crystallography. A suitable protein template for 3D modelling of HCP24 protein was searched in PDB by Swiss server with default parameters. Based on maximum identity and lowest E-value, crystal structure of ASP2 (ancylostoma secreted protein 2) of human hookworm Necator americanus (PDB ID: 4nui.1) was selected as a template (Mason et al., 2014). The target and template sequences were aligned using ClustralW2 software (Shen et al., 2013). The aligned sequences were analysed and attuned manually to check the gaps and insertions. After selecting the template, modelling was done by Swiss model, an automated server that takes only amino acid sequences to build a 3D model (Schwede et al., 2003; Arnold et al., 2006).
2. Material and methods 2.1. 3-D modelling of the protein Construction of 3D model of H. contortus P24 protein (HCP24) was required to predict its potential conformational B-cell epitopes. The 3D model of HCP24 protein was not available in Protein Data Bank (PDB). Therefore, we aimed for constructing the 3D model of the protein. The amino acid sequences of HCP24 protein was retrieved from GenPept database (ID: AEG76952.1) of NCBI using the URL (https://www.ncbi. nlm.nih.gov/protein/AEG76952.1). Physiochemical properties like molecular weight, isoelectric point (pI), amino acid composition, estimated half-life and instability index were determined by ProtParam tool (http://web.expasy.org/protparam/). The secondary structure of the protein was predicted by PSIPRED server (http://bioinf.cs.ucl.ac. uk/psipred/). The model of the protein was constructed following homology modelling approach, which refers to constructing an atomicresolution model of the “target” protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein (Cavasotto and Phatak, 2009). It requires identifying a
2.2. Validation of constructed 3D model of HCP24 protein Once the 3D model was generated, the quality and reliability of the constructed model were checked by the default quality parameters of the ERRAT and VERIFY3D software. Packaging volume, hydrogen bonds, accessible surface area and dihedral angles were also predicted by the default parameters of the VADAR software (Willard et al., 2003). In addition, the PROCHECK and RAMPAGE software were used to validate the constructed 3D model of the protein by the Ramachandran plot, which judge the backbone conformation on the basis of phi/psi distribution and the presence of non-GLY residues at the disallowed regions in the model. The overall quality of protein is again checked by ProQ server. After complete evaluation and validation of the generated 3D model of HCP24 protein, it was successfully submitted in PMDB. 104
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Fig. 2. (a): ERRAT plot, in which x-axis represents the residues number and y-axis represents the error values. The quality of modelled HCP24 protein was very good with overall quality factor 97.382. The overall quality factor for a good quality model should be 95 or above, (b): VERIFY3D plot, in which x-axis represents the residues number and y-axis represents the average 3D-1D score. First and last 10 residues were not showing any fluctuation and error whereas rest all were showing. In this model, 82.5% residues had 3D-1D score > 0.2. It should he at least 80% (average 3D-1D score) to pass the model.
2.3. Linear B-cell epitope prediction
2.4. Conformational B-cell epitope prediction
The linear antigenic B-cell epitopes from the sequence of HCP24 protein were predicted by Support Vector Machine TriP tool which is based on the machine learning algorithm (Yao et al., 2012). Its linearity depends on the amino acid properties by assuming that hydrophilic regions of proteins are mainly found on the surface, so that they are potentially antigenic. Immuno-medicine Group tool (http://imed.med. ucm.es/Tools/antigenic.pl) was also used for the prediction of antigenic peptides in this protein sequence. This tool is based on Kolaskar and Tongaonkar method with approximately 80% accuracy as reported and the prediction is based on the table that reflects the existence of amino acids with available known segmental epitopes. The size of the segments should be at least 8 residues long (Kolaskar and Tongaonkar, 1990; Ingale, 2010). The Linear B cell epitopes were also evaluated by using BEPIPRED tools of immune epitope database with default settings. Bepipred used Hidden Markov model for the prediction of B cell epitopes (Larsen et al., 2006; Potocnakova et al., 2016).
Conformational B cell epitopes from the 3D model of HCP24 protein was predicted by ElliPro (http://tools.iedb.org/ellipro/). It is a webtool designed by Thornton's method together with MODELLER program of a residue clustering algorithm and Jmol viewer (Ponomarenko et al., 2008). The P24 protein model used in ElliPro was refined and validated by different tools/software as mentioned above (e.g., ERRAT, VERIFY3D, and ProQ). The ElliPro score of predicted peptides as conformational B-cell epitopes should be in the range of 0.5 to 0.8, and the maximum distance for residue clustering was defined as 6.0 Å (Gurung et al., 2012). 2.5. T-cell epitope prediction MHC-I binding peptides within the HCP24 protein were predicted by Propred-1 server (http://crdd.osdd.net/raghava/propred1/). It is a matrix based prediction server consisting of 47 MHC-I alleles. We used 105
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3. Results
Table 1 Predicted antigenic peptides of HCP24 protein by Immuno-medicine Group tool.
Number 1 2 3 4 5 6 7 8 9 10 a
Start Position Peptides 4 42 67 84 115 149 162 172 191 203
LATVALLMLLST AYRTLVAK RMLKVKYDC FAKKCVFAH KTVAAAESVDLWF GVGHYTQVVW NKIGCAVEW SDMTFVACEY PIYEVGN EDCKCTNCVCSRDEAL
3.1. Physiochemical properties and secondary structure conformation of the protein
En d Position 15 49 75 92 127 158 170 181 197 218
The physiochemical properties of HCP24 protein on the basis of ProtParam analysis revealed the molecular weight was 24,755 Da and isoelectric point was 5.22, indicating it as a negatively charged protein. In particular, the protein contained 24 negatively charged residues (Asp + Glu) and18 positively charged residues (Arg + Lys). Alanine, aspartate and glutamate were found to be rich in this protein. The computed instability index of 36.99 indicated that the protein is stable as the obtained value is less than the cut off of 40. Similarly, the Nterminal sequence containing M (Met) indicated that the half-life of this protein is 30 h in mammalian reticulocytes (in vitro), > 20 h in yeast (in vivo) and > 10 h in E. coli (in vivo). The secondary structure of HCP24 protein contained alpha helices (36.49%), random coils (34.68%) extended strands (20.27%) and 19 beta turns (8.56%) Fig. 1(c), in which the hydrophobic alanine and leucine were normally buried in the core protein, and the polar glutamate and asparagine were found more in alpha helix importing positive charge.
The peptides are predicted to be highly antigenic.
HLA–A20 cattle allele in this study as it was the only one cattle allele available on the server. Later, MHC-II promiscuous binding peptides were also predicted by MHC2PRED server (http://crdd.osdd.net/ raghava/mhc2pred/) with all 42 alleles available in the server. This server is based on an elegant machine learning technique of SVM method. Further MHCPRED2 (http://www.ddg-pharmfac.net/ mhcpred/MHCPred/) server was also used to predict MHC-II binding peptides of HCP24 protein with the selected DRB0101, DRB0401 and DRB0701 alleles. This server predicts the MHC-II and I binding peptide by measuring the half-maximal inhibitory concentration (IC50) value. The binding affinity is inversely proportional to IC50 value, meaning that lower the IC50 values, higher would be the binding affinity to host MHC alleles. The IC50 values are divided in three different parts i.e. high-affinity binding = IC50 < 50 nM, intermediate-affinity binding = IC50 < 500 nM and low-affinity binding = IC50 < 5000 nM (Guan et al., 2003; Gurung et al., 2012). The peptides having high and intermediate IC50 values were considered as strong binding epitopes whereas peptides having IC50 > 5000 nM were not considered to be binding to host alleles.
3.2. 3D modelling of the HCP24 protein Crystal structure of ASP2 (ancylostoma secreted protein 2) of Necator americanus (PDB ID: 4nui.1) was selected as a template for the 3D modelling of HCP24 protein in Swiss server. There were a total of 50 templates found by Swiss model server for the modelling of HCP24 protein. We selected 4nui.1 as a suitable template for the modelling of the targeted protein on the basis of maximum identity (47.60%), similarity (0.45), GMQE score (0.72) and presence of minimum number of gaps (only 1) and maximum query coverage of the alignment between the sequences of target and template. The sequence identity between HCP24 and the selected template was 46.89%, which is more than the required 30% sequence homology for generating useful models (Xiang, 2006). The total three models were constructed by Swiss model server in which we considered model 1 as a final model after assessing its GMQE score, global quality estimate, local quality estimate score of the model. The overall quality factor of the predicted HCP24 protein model (Fig. 1b) was 97.38 by the ERRAT. The predicted protein model with a quality score of 95 or above is considered as a good quality model as shown in Fig. 2(a). The predicted HCP24 model was also concurred by VERIFY3D showing 82.5% of the residues with an averaged 3D-1D score ≥ 0.2. At least, it should be 80% for a good model as shown in Fig. 2(b). Ramachandran assessment was done by PROCHECK and RAMPAGE servers (Lovell et al., 2003) and both the software showed 98.5% residues in most favoured and allowed region and only 1.5% residues in outlier regions, as shown in Fig. (1d). The quality of protein model was very good as assessed by ProQ server with the LG score of 2.844. The LG score > 2.5 shows very good model (Cristobal et al., 2001). After complete evaluation and validation, the generated model was successfully submitted in Protein model database with a PMDB ID: PM0081352.
2.6. Proteosomal cleavage sites prediction To explore the proteosomal cleavage sites in the selected peptides, total proteosomal cleavage sites were predicted in HCP24 protein by Netchop server and analysed manually on the basis of highest score above threshold (0.5). The NetChop server produces neural network predictions for cleavage sites of the proteasome. (Keşmir et al., 2002). 2.7. IEDB analysis of the protein Kolaskar and Tongaonkar antigenicity prediction method of the IEDB was used to analyse and evaluate the selected epitopes (pep-1 and pep-2) as it is a semi-empirical method which makes use of physicochemical properties of amino acid residues and their frequencies of occurrence in experimentally known segmental epitopes. The method also has high regard owing to claimed accuracy of 75%. The protein was evaluated using Kolaskar and Tangaonkar antigenicity method (Kolaskar and Tongaonkar, 1990) with a default threshold value 0.9. Hydrophilicity of the antigenic epitopes, which is an important parameter for accessibility of epitopes to antibodies, were evaluated using Parker Hydrophilicity method (Parker et al., 1986) at a threshold value of 1.88. Flexibility and Beta turns were checked using Karplus and Schulz Flexibility (Karplus and Schulz, 1985) and Chou and Fasman Beta-turn methods (Chou and Fasman, 1978) respectively, with a threshold of 1.00 for both.
3.3. Epitope prediction a) B-cell epitopes prediction 1) Antigenic peptides and linear B-cell epitopes prediction The whole sequence of HCP24 protein was analysed for antigenic peptide prediction due to lack of information on its structural and specific antigenic peptide attributes. 10 antigenic peptides were predicted by immune-medicine group tool (Table 1) with average antigenic propensity score of 1.0241. It means the segment greater than average antigenic propensity (1.0241) will be potentially antigenic. The highest peak is observed for peptide named pep-1 (EDCKCTNCVCSRDEAL) 106
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Fig. 3. Antigenic peptides plot in which x-axis represents the residues number and y-axis represent the average antigenic prosperity.
(lysine with score 0.57) positions. The selected pep-1 may be converted into two different segments of 8 residues after proteosomal cleavage. The 8 residues long peptide can also be used for antibody production as they do not loose antigenic activity. As 8 cleavage were observed in the pep-2 at position 4 (lysine with score 0.82), 7 (valine with score 0.64), 8 (alanine with score 0.51), 9–10 (lysine with score 0.88 and 0.91), 11 (methionine with score 0.95), 12–13 (lysine with score 0.96 and 0.92), Therefore, pep-2 has a disadvantage of proteosomal instability which precludes it from qualifying as an immunogenic peptide.
from amino acids 203 to 218 with an antigenic propensity score of 1.2 and the second highest peak for pep-2 (LATVALLMLLST) from amino acids 4 to 15 with an antigenic propensity of 1.19. Therefore, both peptides (Table 1 and Fig. 3) were predicted to be highly antigenic that can be considered for effective immunization or immune-diagnosis. Similarly, SVM trip identified 8 linear B-cell epitopes, out of which 4 could qualify to be antigenic as determined by the algorithm based on machine learning method (Table 2). Bepipred also confirmed that both pep-1 and pep-2 were important antigenic region as predicted earlier (Fig. 4). 2) Conformational B-cell epitopes prediction The conformational B-cell epitopes (Table 3) of HCP24 protein model were predicted by Ellipro. The highest score (0.762) was achieved by epitope no.1 (VGNPCTNNEDCKCTNCVCSRDEA) from amino acids 195 to 217. This predicted epitope also contained the segment of highly antigenic peptide-1 recommended by SVMTriP server and Immuno-medicine Group tool. Therefore, the highly antigenic region (EDCKCTNCVCSRDEAL) of this pep-1 was selected whereas the other antigenic pep-2 (LATVALLMLLST) was not predicted by Ellipro as a conformational B-cell epitopes. All the epitopes predicted by Ellipro were visualized in Jmol to show its 3D structure or relative orientation of protein and peptide molecule (Fig. 5). The amino acid positions of each predicted epitope was also confirmed by Jmol viewer.
d) IEDB analysis of the protein Kolaskar and Tongaonkar antigenicity prediction results revealed that both pep-1 and pep-2 are in the region of major antigenicity of the protein (Fig. 6(a). The results of Karpus hydrophilic prediction suggested that the region of pep-1 peptide was hydrophilic while pep-2 was not hydrophilic (Fig. 6(b). Again the pep-1 was much more flexible in comparison to pep-2 as analysed by the Chou and Fasman Beta-Turn prediction plot (Fig. 6(c). 4. Discussion The aim of the study was to identify the potent antigenic peptides of HCP24. Developing a successful vaccine against any pathogen requires the identification of potent antigenic B and T-cell epitopes/peptides, prior knowledge about binding interaction of these peptides to MHC alleles and host immune cells (Gurung et al., 2012; Assis et al., 2014). Identification of important peptidic epitopes does also contribute to the development of diagnostic test for the pathogens (Saxena et al., 2012). Such detailed information can be generated in silico with the help of various bioinformatics tools/software. The generated information can be used to test the predicted function of these peptides by in-vitro and in-vivo experiments. In the present study, we analysed the sequence of HCP24 protein by Protparam tool to get its detailed information like molecular weight, pI, amino acid composition, half-life and stability, which are important for antigenicity of any molecule (Abbas et al., 2017). HCP24 contained negatively charged residues i.e., alanine, aspartate and glutamate in higher amount, which are polar and hydrophilic in nature. It has been reported that hydrophilic amino acids are mainly found on the surface of antigen and constitute a major part of potential surface epitopes (Ingale, 2010) as they are accessible to surrounding solvent environment. Since they are potentially antigenic they may be useful in immunization and for early immune-diagnosis. Swiss model server was
b) T-cell epitope prediction The top ten MHC-I binding peptides of host were predicted by Propred-I on the basis of highest score (Table 4) whereas 214 MHC-II binding peptide were predicted by MHC2PRED server. We could observe the presence of both the peptides in the predicted peptides list within an allelic repository of 36 alleles in the algorithm except the other 6 alleles which are HLA-DR5, HLA-DR51, HLA-DRB1*02, HLADRB*1101, HLA-DRB*1105 and I-As. MHCPRED2 server also validated the binding ability of the selected peptides (Pep-1 and Pep-2) (Table 5). Pep-1 was predicted to be a good binder to both the MHC-I and II alleles whereas pep-2 was showing binding only with MHC-II alleles. c) Peptides stability prediction Netchop server was used to determine the proteosomal cleavage sites in HCP24 protein sequence as it's important to assess the stability of the immunogen in the host system. This server found a total of 55 cleavage sites in HCP24 protein sequence in which two sites were observed in the selected pep-1 at 211 (valine with score 0.57) and 218 107
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Table 2 Predicted B-cell epitopes of HCP24 protein by SVMTriP tool.
Rank 1 2 3
Start Epitopes 115 KTVAAAESVDLWFDELQQNG 141 MTMEVFNRGVGHYTQVVWQW
End Score 134 1.000 160 0.986
203 EDCKCTNCVCSRDEALCIAP
Recommended Yes Yes
222 0.926
Yes
4
35 TFVNKHNAYRTLVAKGEAKN
54 0.919
5
6 TVALLMLLSTSGHASMCPDT
25 0.897
Yes
6
93 NSYSDRNNWGQNLYMTSILN
112 0.856
No
7
60 GYAPKAARMLKVKYDCAIEE
79 0.736
No
8
167 AVEWCSDMTFVACEYDSAGN
186 0.715
No
No
The first four epitopes are recommended by software which are marked by flags. Fig. 4. The graph showing the results of lineal B-cell epitopes of HCP24 protein predicted by Bepipred software of IEDB in which the x-axis represents the position whereas y-axis represents score of predicted amino acids in the sequence. The red line is indicating the threshold value (0.5) for epitopes prediction and the yellow region is representing the linear B-cell epitopes in the sequence. Both the peptides (Pep-1 & Pep-2) were found to be linear B-cell epitopes. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Table 3 Conformational B-cell epitopes predicted by Ellipro server. S.No Epitopes
Start
End
1. 2. 3. 4. 5. 6. 7.
195 22 107 49 86 130 186
217 31 117 62 101 149 190
VGNPCTNNEDCKCTNCVCSRDEA CPDTNGMSDE MTSILNQNKTV KGEAKNAKEIGGYA KKCVFAHNSYSDRNNW LQQNGVPYDNVMTMEVFNRG NYMGM
used for modelling as it's fully automated and provides complete stoichiometry and the overall structure of the complex as inferred by homology modelling (Waterhouse et al., 2018). The constructed 3D model of HCP24 qualified to be a very good representative model for the protein and demonstrated chiefly alpha helical secondary conformation (36%) signifying the orderliness of the structure of the protein. Linear antigenic and conformational B-cell epitopes were generally suggested as the potential epitopes for immuno-response in the host (Ingale, 2010; Gurung et al., 2012; Assis et al., 2014). Therefore, to predict linear antigenic B-cell epitopes in HCP24 protein, we used SVMTrip tool. Among eight predicted linear antigenic B-cell epitopes, the top four in order of prediction were recommended to be the best antigenic peptides. However, we included fifth epitope also because it encompassed in the predicted segment of second highly antigenic
No. of residues 23 10 11 14 16 20 5
Score 0.762 0.747 0.714 0.698 0.658 0.609 0.56
peptide of the Immuno-medicine group algorithm (Table 1). The segments of first highly antigenic peptide (pep-1) predicted by Immunomedicine group were present in the epitope no. 3 of HCP24, which was identified by SVMTrip tool (Table 2). Therefore, we selected both, first highly antigenic peptide as pep-1 and second highly antigenic peptide as pep-2 in the whole P24 protein of H. contortus. Both the selected epitopes were also encompassed in the linear antigenic prediction region as suggested by Bepipred, giving further strength to our findings. The important prerequisite molecular event to initiate humoral and cell-mediated immune-response is binding of antigenic peptides with the host MHC-II and MHC-I molecules (Ingale, 2010; Gurung et al., 2012). Therefore, the binding of both the selected peptides to the HLAA20 cattle allele of MHC-I molecules was predicted by Propred-I. Among the selected peptides, only pep-1 segment was present in top ten 108
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Fig. 5. Conformational B-ell epitopes of IIaemonchus contortus P24 protein predicted by Ellipro from 3D structure template PDB 1D 4UWcIK in ball and stick model. In which yellow balls are the residues of predicted peptides and white sticks are the non-epitope residues of protein. Each epitope is predicted with residue number and position mentioned in Table 6: A: (VGNPCTNNEDCKCTNCVCSRDEA)195–217, B: (CPDTNGMSDE)22–31, C: (MTSILNQNKTV)107–117, D: KGEAKNAKEIGGYA) 49–62, F: (KKCVFAHNSYSDRNNW)86–101. F: (LQQNGVPYDNVMTMEVFNRG)130–149, G: (NYMGM)186–190. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Table 4 Predicted MHC-I binding peptides of HCP24 protein by Propred-I server. Rank
Peptides
1 2 3 4 5 6 7 8 9 10
AKGEAKNAK NKHNAYRTL LKVKYDCAI VMTMEVFNR AKKCVFAHN KKCVFAHNS NKTVAAAES NKIGCAVEW CKCTNCVCS TNGMSDEVR
Residue No. 48 38 69 140 85 86 114 162 205 25
Real Score
Log Score
1000.000 500.000 300.000 200.000 100.000 100.000 100.000 100.000 100.000 80.000
6.9078 6.2146 5.7038 5.2983 4.6052 4.6052 4.6052 4.6052 4.6052 4.3820
predicted peptides of HCP24 towards MHC-1 binding. The pep-2 did not show any binding ability to HLA-A20 cattle allele of MHC-I molecules. The HLA-A20 allele was selected because it is the only one allele of ruminant (cattle) available in the database. However, both the peptides (Pep-1 and Pep-2) showed good binding affinity with 36 alleles of MHC-II as predicted by MHCPRED2 server. MHC2PRED server also shows that both the selected peptides had a good binding ability with MHC-II DRB0101 allele and intermediate binding with DRB0401 and DRB0701 alleles. However, Ellipro server also predicted only pep-1
Table 5 Predicted MHC-II binding peptides of HCP24 protein by MHCPRED2 server. Allele
Peptides
Start
End
No. of residues
DRB0101
FSLATVALL CSRDEALCI FSLATVALL CKCTNCVCS FSLATVALL CKCTNCVCS
2 212 2 205 2 205
10 220 10 213 10 213
9 9 9 9 9 9
DRB0401 DRB0701
% of Highest on log scale 83.29 74.93 68.77 63.88 55.52 55.52 55.52 55.52 55.52 52.83
Predicted IC50 Value (nM) 1.88 3.21 63.68 203.24 101.86 100.69
Table 6 Overlapping sequences of selected peptide by different tools/software. Peptide/Epitope B cell Antigenic MHCI MHCII Conformational B cell
Sequence EDCKCTNCVCSRDEALCIAP EDCKCTNCVCSRDEAL CKCTNCVCS CKCTNCVCS VGNPCTNNEDCKCTNCVCSR DEA 109
Position 203-222 203-218 205-213 205-203 195-217
Tools/software SVMTrip Immuno-medicine Propred I MHCPRED2 Ellipro
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Fig. 6. (a): Antigenicity Prediction (b) Hydrophilicity Prediction (c) Beta turns & Flexibility Prediction by IEDB. The x-axis in the graph representing the position whereas y-axis signifies the score of predicted amino acids in the sequence. The red line is indicating the threshold value for epitopes prediction and the yellow region is representing the predicted epitopes in the sequence. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
(with highest score 0.762) as a conformational B cell epitope (Table 3 and Fig. 4). Therefore, pep-1 can be strongly hypothesized to be good in eliciting a very strong humoral and cellular immune-response owing to its binding ability with both MHC-I and MHC-II, whereas the pep-2 can be used only for humoral response. Proteosomal cleavage analysis suggested that pep-1 may be a stable peptide inside the host since it contains only two protease cleavage sites at 211 (valine) and 218 (lysine) positions. After cleavage, this peptide may be converted into two segments of 8 residues each. Hence both the 8 residues peptide can also be used for eliciting antibody as well as cell mediated immune response. It was observed that as many as 8 cleavage sites were identified in pep-2 at lysine, valine, alanine, and methionine positions with more than basal threshold score (> 0.5). Therefore, pep2 may not be a good antigenic peptide due to the presence of many proteosomal cleavage sites and may undergo a rapid cleavage in host gut or in the enzymatic environment. Kolaskar and Tongaonkar antigenicity prediction method also confirmed that both pep-1 and pep-2 should be the potential epitopes. Pep1 was found also to be superior than pep-2 as far as hydrophilicity and flexibility of the peptide is concerned which gives better accessibility and flexibility to interact with its corresponding paratope on the antibody molecule.
(pep-1) was concluded to be a very good antigenic peptide candidate for subunit vaccine in Haemonchus contortus. This peptide may also be helpful for immuno-diagnosis of H. contortus infection because the peptide based diagnosis of parasitic diseases is nowadays a cheaper, simpler and reproducible strategy for large scale testing. Acknowledgement Authors are thankful to Department of Science and Technology, Govt. of India for the financial assistance (Grant number-ECR/2016/ 000135). References Abbas, A., Lichtman, A.H., Pillai, S., 2017. Cellular and Molecular Immunology. Elsevier (608 pp.). Arnold, K., Bordoli, L., Kopp, J., Schwede, T., 2006. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22 (2), 195–201. Assis, L.M.D., Sousa, J.R., Pinto, N.F.S., Silva, A.A., Vaz, A.F.D.M., Andrade, P.P., De Melo, M.A., 2014. B-cell epitopes of antigenic proteins in Leishmania infantum: an in silico analysis. Parasite Immunol. 36 (7), 313–323. Bird, A. F., & Bird, J. (1991). The Structure of Nematodes, 2nd edition. Academic Press Ltd., London. Pg, 167–229. Borgsteede, F.H., Dercksen, D.D., Huijbers, R., 2007. Doramectin and albendazole resistance in sheep in the Netherlands. Vet. Parasitol. 144, 180–183. Cavasotto, C.N., Phatak, S.S., 2009. Homology modeling in drug discovery: current trends and applications. Drug Discov. Today 14, 676–683. Chou, P.Y., Fasman, G.D., 1978. Empirical predictions of protein conformation. Annu. Rev. Biochem. 47 (1), 251–276. Cox, G.N., Pratt, D., Hageman, R., Biosvenue, R.J., 1990. Molecular cloning and primary sequencing of a cysteine protease expressed by Haemonchus contortus adult worms. Mol. Biochem. Parasitol. 41, 25–34. Cristobal, S., Zemla, A., Fischer, D., Rychlewski, L., Elofsson, A., 2001. A study of quality measures for protein threading models. BMC Bioinf. 2 (1), 5.
5. Conclusion In summary, the 3D model of HCP24 protein was successfully constructed and validated. In addition, we predicted two potential antigenic peptides (pep-1 and pep-2) of HCP24 protein. However, on the basis of stability prediction in the host, very good binding affinity with host MHC-I and II alleles, hydrophilicity and the flexibility, the peptide 110
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