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Arya Dwi Wijaya Saputra1 
, Nadaa Ramadhia Hariyanto1 , Tharisa Sabrina Ardya Gharini1 , Maharani Retna Duhita2
, Nadaa Ramadhia Hariyanto1 , Tharisa Sabrina Ardya Gharini1 , Maharani Retna Duhita2
1- Department Biology, Faculty of Science and Technology, UIN Maulana Malik Ibrahim Malang
2- Department Biology, Faculty of Science and Technology, UIN Maulana Malik Ibrahim Malang ,maharaniretna.duhita@uin-malang.ac.id
2- Department Biology, Faculty of Science and Technology, UIN Maulana Malik Ibrahim Malang ,
Abstract: (12 Views)
Background and Objective: Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health challenge, with existing vaccines like BCG showing limited efficacy, particularly in adults. This highlights the urgent need for innovative vaccine designs. In silico approaches offer significant advantages, such as enhanced time efficiency, reduced costs, and the ability to predict epitope properties with high precision, making them a valuable tool for developing next-generation vaccines. This study identifies and characterizes the ERv 57-64 epitope as a potential peptide-based vaccine candidate.
Methods: Epitope selection was based on antigenic regions within the ERv protein sequence. ERv 53–63 was chosen due to higher predicted antigenicity and favorable binding potential. VaxiJen was used for antigenicity assessment, AllerTOP v2.0 for allergenicity, and ToxinPred for toxicity evaluation. Structural docking simulations were conducted using PyMOL, with a human B-cell receptor (PDB ID: 5DRW) as the docking target to evaluate epitope–receptor interaction.
Results: ERv 53-63 demonstrated high antigenicity (VaxiJen score: 0.9599), was predicted as non-allergenic and non-toxic, and exhibited strong binding affinity with the B-cell receptor (interaction energy: –877.8 kcal/mol), indicating stable complex formation.
Conclusion: These findings support ERv 53–63 as a novel and promising in silico-derived B-cell epitope, outperforming prior candidates such as ERv 105–118. It holds strong potential for peptide-based TB vaccine development. Further in vitro and in vivo studies are recommended to validate its immunogenicity and safety
Methods: Epitope selection was based on antigenic regions within the ERv protein sequence. ERv 53–63 was chosen due to higher predicted antigenicity and favorable binding potential. VaxiJen was used for antigenicity assessment, AllerTOP v2.0 for allergenicity, and ToxinPred for toxicity evaluation. Structural docking simulations were conducted using PyMOL, with a human B-cell receptor (PDB ID: 5DRW) as the docking target to evaluate epitope–receptor interaction.
Results: ERv 53-63 demonstrated high antigenicity (VaxiJen score: 0.9599), was predicted as non-allergenic and non-toxic, and exhibited strong binding affinity with the B-cell receptor (interaction energy: –877.8 kcal/mol), indicating stable complex formation.
Conclusion: These findings support ERv 53–63 as a novel and promising in silico-derived B-cell epitope, outperforming prior candidates such as ERv 105–118. It holds strong potential for peptide-based TB vaccine development. Further in vitro and in vivo studies are recommended to validate its immunogenicity and safety
Keywords: ER 53-63 epitope, B cell receptor, in silico vaccine design, peptide-based vaccine, tuberculosis
Type of Study: Original Research Article |
Subject:
Microbial Bioinformatics
Received: 2025/02/4 | Accepted: 2025/06/30
Received: 2025/02/4 | Accepted: 2025/06/30
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Iranian Journal of Medical Microbiology by Farname is licensed under CC BY-NC 4.0
