Design of HIV-1 Peptide-Based Vaccine from Matrix Protein p17: Immunoinformatics Approach


  • Rosario Trijuliamos Manalu National Institute of Science and Technology
  • Meilisa Rahmasari National Institute of Science and Technology
  • Fathin Hamida National Institute of Science and Technology



Epitop, HIV, Immunoinformatic, Vaccine Design


HIV/AIDS infection is a spectrum of infectious diseases of the immune system. Rapid transmission causes difficulty in overcoming this disease. This studied aims to determine potential peptides as vaccine candidates, and to determine the physicochemical properties and homologous properties of vaccine candidates. This studied used a processing method with an immunoinformatics approached and used samples from the p17 matrix protein sequence with PDB code 2HMX. All stages were carried out used the appropriate web server and application. From sequence analysis, selected T-cell and B-cell epitopes was obtained. After designing the vaccine candidate from T-cell and B-cell epitopes, the final stepped was to perform 2D and 3D visualization of the vaccine candidate. The researched shows that the peptide were as follows, adjuvant-EAAAK-GSEELRSLY-AAY-NNSQVSQNY-GPG PG-TGSEELRSLYNTIAV-KK-QPSLQTGSEELRS -KK-DVKDTKEALDK. The physicochemical properties of the HIV vaccine candidate had a total of 116 amino acids, a molecular weight of 12871.66 g/mol, a theoretical pI of 9.58, a number of negative residues 13, a number of positively charged residues 24, the extinction coefficient was 7825 m2/mol, the stability index was 59, 77, aliphatic index 64.74, average hydrophobicity -0.958. The results of the homologous analysis of the matrix protein p17 vaccine candidate stated that the amino acid residues that made up the peptide were not homologous or did not caused an autoimmune response when used as a vaccine candidate.


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How to Cite

Rosario Trijuliamos Manalu, Meilisa Rahmasari, & Fathin Hamida. (2023). Design of HIV-1 Peptide-Based Vaccine from Matrix Protein p17: Immunoinformatics Approach. Asian Journal of Healthcare Analytics, 2(1), 269–286.