Immunogenicity study of a Novel DNA-Based HCV vaccine candidate….. Supplementary Data ….. |
The Egyptian Journal of Immunology E-ISSN (2090-2506) Volume 31 (3), July, 2024 Pages: 01–09. www.Ejimmunology.org https://doi.org/10.55133/eji.310310 |
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| Eman A. Salem1, Ashraf Tabll1, 2, Tamer Z. Salem3, Yasmine S. El-Abd1, Reem El-Shenawy1, Heba Shawky4, and Sahar Shoman5 |
| 1Department of Microbial Biotechnology, Biotechnology Research Institute, National Research Centre, Cairo, Egypt.2Egypt Center for Research and Regenerative Medicine (ECRRM), Cairo, Egypt.
3Molecular Biology & Virology Lab, Center for X-Ray Determination of the Structure of Matter (CXDS), Zewail City of Science & Technology, Giza, Egypt. 4Department of Therapeutic Chemistry, Pharmaceutical & Drug Research Institute, National Research Centre, Cairo, Egypt.5Department of Microbiology, Faculty of Science, Ain Shams University, Cairo, Egypt. |
Corresponding author: Yasmine S. El Abd, Department of Microbial Biotechnology, Biotechnology Research Institute, National Research Centre, Cairo, Egypt. Email: yasminco@yahoo.com |
Table of Contents
Physicochemical properties, antigenicity, and allergenicity of the HCV-CE candidate……………………………………….. 2
Tertiary structure modeling, refinement, and validation. 2
In-silico prediction of B-cell and T-cell epitopes. 2
Supplementary Table 1: Linear B-cell epitopes predicted from primary HCV-CE peptide sequence. 4
Supplementary Table 2: Discontinuous B-cell epitopes predicted from modeled HCV-CE 3D-structure. 5
Supplementary Table 3: CTL epitopes predicted from primary HCV-CE peptide sequence. 6
Supplementary Table 4: HTL epitopes predicted from primary HCV-CE peptide sequence. 7
Supplementary Table 5: Residues of HCV-CE with polar contacts with the nAb residues. 8
Supplementary Methods:
Physicochemical properties, antigenicity, and allergenicity of the HCV-CE candidate
The complete translated amino acid sequence of the HCV-CE vaccine candidate was used to predict different physicochemical properties, including molecular weight, theoretical isoelectric point (pI), instability index, and grand average of hydropathicity, through the use of the ProtParam online tool.1 The online server VaxiJen v2.0 (http://www.ddgpharmfac.net/ vaxijen/VaxiJen/VaxiJen.html), which predicts antigenicity depending on the target organism with an accuracy range of 70-89% based on the physicochemical properties of proteins, was used for antigenicity prediction.2 To evaluate allergenicity, the vaccine construct was analyzed through the AllerTOP v2.0 server (https://www.ddgpharmfac.net/Aller TOP/ index.html), which utilizes an algorithm based on auto/cross-covariance transformation and the k-nearest neighbors methods to categorize peptide sequences as allergens or non-allergens with a reported accuracy of 85.3%.3
Tertiary structure modeling, refinement, and validation
The secondary structure of the vaccine construct was predicted through the software PSIPRED v4.0 (http://bioinf.cs.ucl.ac.uk/ psipred/), and then the 3D structure of the vaccine construct was generated by a fragment assembly based design approach of a de novo protein scaffold through the FoldDesign server (https://zhanggroup.org/ FoldDesign/index.html) using user-defined constraints, including secondary structure and/or contact and distance maps. The modeled structure was then subjected to a two-step refinement procedure through the GalaxyRefine tool (https://galaxy. seoklab.org/cgi-bin/submit.cgi?type=REFINE) followed by loop refinement using the GalaxyLoop server (https://galaxy.seoklab.org/cgi-bin/submit.cgi?type=LOOP). The refined model was then validated for structure quality using ProSA (https://prosa.services.came. sbg.ac.at/prosa.php) and the SAVES v6.0 toolkit, which includes a suite of tools (WHAT_CHECK, ERRAT, VERIFY_3D, and PROCHECK) for predicting different stereochemical parameters of the protein structure (https://saves.mbi.ucla.edu/?job= 1311167).
In-silico prediction of B-cell and T-cell epitopes
The translated amino acids of the full-length HCV-CE sequence were assessed for potential binding with T-cell and B-cell receptors required for the induction of specific immune responses. The B-cell epitopes were predicted using the BCPred online server with 75% specificity criteria for epitope prediction,4 while conformational B-epitopes were predicted by the DiscoTope web server.5 The peptide sequence was also subjected to helper T- lymphocyte and cytotoxic T-lymphocyte (HTL and CTL, respectively) epitope prediction using the MHC-II epitope prediction module of the Immune Epitope Database (IEDB) database and the NetCTL 1.2 server, respectively.6,7 The generated HTL epitopes with IC50 values ≤ 50 nM were selected for further investigation. CTL epitopes with a combined score > 0.75 were selected and further submitted to the IEDB MHC-I binder predictor using default parameters. All epitopes were filtered according to their antigenicity and ability to induce interferon-γ (IFN-) using the VaxiJen2 and IFNepitope8 servers, respectively. Both T-cell and B-cell epitopes were analyzed for their conservancy among different HCV genotypes and population coverage based on the MHC allele distribution using the IEDB epitope conservancy analysis (http://tools.iedb.org/conservancy/)9 and population coverage tool (http://tools.iedb.org/population/),10 respectively.
Molecular docking
To evaluate the potential immunoreactivity of the HCV-CE vaccine candidate to broadly neutralizing antibodies (nAbs), flexible protein‒protein molecular docking was performed through the ClusPro 2.0 (https://cluspro.bu.edu/publications.php) server using the HCV-nAbs, AR3C [pdb:4MWF] and HEPC3 [pdb:6MEI], as receptors and the modeled tertiary structure of the HCV-CE vaccine candidate as a ligand in the “Antibody Mode” with masking of the non-complementarity-determining regions (CDR) regions in the receptor (nAb). The crystal structures of the heavy and light chains were retrieved from the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (https://www.rcsb.org/), and the Molecular Graphics Laboratory (MGL) Tools software suite was used for the analysis of docked structures. The best complex (lowest energy score) was chosen for evaluation, and the powerful molecular graphics program PyMol (http://www.pymol.org) was used for visualization.
Immune simulation
C-ImmSim is an online server agent-based model that predicts peptide interactions with the immune system using position-specific scoring matrices (PSSMs) and machine learning techniques. Therefore, the server was used to simulate and characterize the immunogenicity of the designed vaccine and the anticipated immune responses. Two doses were introduced, with a two-week interval between them, and the simulation was run for 100 and 400 steps (step = 8 h).
Supplementary Data – Full Text