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. 2020 Jul;9(2):81-96.
doi: 10.7774/cevr.2020.9.2.81. Epub 2020 Jul 31.

Antigenic properties of dense granule antigen 12 protein using bioinformatics tools in order to improve vaccine design against Toxoplasma gondii

Ali Dalir Ghaffari  1 , Abdolhossein Dalimi  1 , Fatemeh Ghaffarifar  1 , Majid Pirestani  1
Affiliations

Antigenic properties of dense granule antigen 12 protein using bioinformatics tools in order to improve vaccine design against Toxoplasma gondii

Ali Dalir Ghaffari et al. Clin Exp Vaccine Res. 2020 Jul.

Abstract

Purpose: Toxoplasma gondii is an opportunistic parasite infecting all warm-blooded animals including humans. The dense granule antigens (GRAs) play an important role in parasite survival and virulence and in forming the parasitophorous vacuole. Identification of protein characteristics increases our knowledge about them and leads to develop the vaccine and diagnostic studies.

Materials and methods: This paper gave a comprehensive definition of the important aspects of GRA12 protein, including physico-chemical features, a transmembrane domain, subcellular position, secondary and tertiary structure, potential epitopes of B-cells and T-cells, and other important features of this protein using different and reliable bioinformatics methods to determine potential epitopes for designing of a high-efficient vaccine.

Results: The findings showed that GRA12 protein had 53 potential post-translational modification sites. Also, only one transmembrane domain was recognized for this protein. The secondary structure of GRA12 protein comprises 35.55% alpha-helix, 19.50% extended strand, and 44.95% random coil. Moreover, several potential B- and T-cell epitopes were identified for GRA12. Based on the results of the Ramachandran plot, 79.26% of amino acid residues were located in favored, 11.85% in allowed and 8.89% in outlier regions. Furthermore, the results of the antigenicity and allergenicity assessment noted that GRA12 is immunogenic and non-allergenic.

Conclusion: This research provided important basic and conceptual data on GRA12 to develop an effective vaccine against acute and chronic toxoplasmosis for further in vivo investigations. More studies are required on vaccine development using the GRA12 alone or combined with other antigens in the future.

Keywords: Computational biology; Epitope mapping; Toxoplasma gondii; Vaccines.

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Conflict of interest statement

No potential conflict of interest relevant to this article was reported.

Figures

Fig. 1
Fig. 1. Bioinformatics analysis of the phosphorylation sites of GRA12. (A) If the residue is predicted not to be phosphorylated, either because the score is below the threshold or because the residue is not serine, threonine, or tyrosine, that position is marked by a dot (‘.’). Residues having a prediction score above the threshold are indicated by ‘S’, ‘T’, or ‘Y’, respectively (http://www.cbs.dtu.dk/services/NetPhos-2.0/output.php). (B) Predicted phosphorylation sites in GRA12 sequence. GRA, dense granule antigens.
Fig. 2
Fig. 2. Prediction of transmembrane helices in GRA12 proteins. (A) Some statistics and a list of the location of the predicted transmembrane helices and the predicted location of the intervening loop regions. (B) Analysis of the transmembrane domain of GRA12. Number of predicted TMHs, the number of predicted transmembrane helices; exp number of AAs in TMHs, the expected number of amino acids in transmembrane helices (if this number is larger than 18, it is very likely to be a transmembrane protein [OR have a signal peptide]); exp number–first 60 AAs, the expected number of amino acids in transmembrane helices in the first 60 amino acids of the protein (if this number more than a few, you should be warned that a predicted transmembrane helix in the N-term could be a signal peptide); total prob. of N-in, the total probability that the N-term is on the cytoplasmic side of the membrane; possible N-term signal sequence, a warning that is produced when “exp number–first 60 AAs” is larger than 10 (http://www.cbs.dtu.dk/services/TMHMM-2.0/TMHMM2.0.guide.html#output); GRA, dense granule antigens.
Fig. 3
Fig. 3. Analysis of secondary structure of GRA12 using GOR IV. (A) Predicted secondary structure. (B) Graphical frame of secondary structure prediction of GRA12 protein. GRA, dense granule antigens; h, helix; e, extended strand; c, coil.
Fig. 4
Fig. 4. Graphical result from secondary structure prediction of vaccine using PSIPRED.
Fig. 5
Fig. 5. Analysis of 3D structure constructed for GRA12 protein using SWISS-MODEL. (A) 3D structure prediction of GRA12 protein. (B) Model-template alignment. (C) Global quality estimate; QMEAN, a composite estimator, contains four individual terms all atoms, solvation, torsion, and Cβ atoms. Positive values demonstrate that the model scores higher than experimental structures on average. Negative numbers demonstrate that the model scores lower than experimental structures on average. The QMEAN Z-score itself is shown on top. (D) Local quality estimate; typically, it is expected that residues with a rating under 0.6 will be of low quality. (E) Comparison with non-redundant set of protein data bank structures; protein length (number of residues) is showed in x-axis and the normalized QMEAN score is showed in y-axis. The actual design is shown as a red star. (F) Sequence coverage and identity. 3D, three-dimensional; GRA, dense granule antigens.
Fig. 6
Fig. 6. Validation of 3D model of GRA12 protein using Ramachandran plot. (A, B) The z-score plot for 3D structure of predicted vaccine before and after refinement with ProSA-web server. The z-score of the initial model was −0.61 and after refinement processes was −0.98. (C, D) The analysis of Ramachandran plot of initial model showed 79.26%, 11.85%, and 8.89% of residues were located in favored, allowed, and outlier regions, respectively. The results after refinement were changed as follow: 91.85%, 6.67%, and 1.48% of residues were located in favored, allowed, and outlier regions, respectively. 3D, three-dimensional; GRA, dense granule antigens.
Fig. 7
Fig. 7. The output of IEDB (Immune Epitope Database) online server. (A) Bepipred linear epitope prediction; (B) beta-turn; (C) surface accessibility; (D) flexibility; (E) antigenicity; (F) hydrophilicity. The x-axes represent the residue positions in the sequence, while the y-axes represent for each residue the correspondent score; The straight red line demonstrates the threshold or the average score; yellow colors representing that the residue might have a higher probability to be a part of the epitope; and green colors representing the unfavorable regions relevant to the properties of interest.
Fig. 8
Fig. 8. Predicted discontinuous B-cell epitopes by ElliPro tool.
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