Design of Epitope-Based Vaccine Against SARS-CoV-2: An Immuno-Informatics Study

Epitope-Based Vaccine Against SARS-CoV-2

Authors

  • Kavana Hafil Kusuma Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia
  • Muhammad Hermawan Widyananda Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia
  • Wirdatun Nafisah Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia
  • Rahmat Grahadi Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya
  • Yuyun Ika Christina Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia
  • Dinia Rizqi Dwijayanti Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia
  • Dewi Mustikaningtyas Department of Biology, Faculty of Mathematics and Natural Sciences, State University of Semarang, Semarang 50229, Central Java, Indonesia
  • Nashi Widodo Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia
  • Muhammad Sasmito Djati Department of Biology, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang 65145, East Java, Indonesia

DOI:

https://doi.org/10.11594/jtls.14.03.07

Keywords:

Epitope, Immuno-informatic, SARS-CoV-2, Vaccine

Abstract

This study aimed to develop an epitope-based vaccine of SARS-CoV-2 S protein through an immuno-informatics study. The whole genome of SARS-CoV-2 sequences was obtained from the GISAID database and then trimmed to obtain the S protein sequences. The alignment was done by Clustal-W of MEGA software. Epitope prediction and modeling were performed by Discotope BepiPred and the PepFold3 web server. The allergic responses and physicochemical characteristics of predicted epitopes were analyzed using the AlgPred and ProtParam from ExPASy. Molecular docking and dynamic stimulation were performed using AutoDock Vina and YASARA. Biovia Discovery Studio 2019 was used to visualize the molecular docking results. The study predicted 3 potential epitopes, including ‘GDEVRQIAPGQTGKIADYNYKLP’ (epitope 1), ‘YTMSLGAENSVAYSNN’ (epitope 2), and ‘VNNSYECDIPI’ (epitope 3) located in the spike head specifically RBD region. The epitopes did not show an allergen reaction based on IgE epitope mapping. The suitable overexpression for the host of epitopes was mammalian cells. Only epitopes 1 and 2 were stable (instability index above 40). Epitopes 1, 2, and 3 interacted with BCR with binding affinity values -6.6, -7.8, and -7.5 kcal/mol. Epitope 2 wasere stable when interacting with the BCR. Therefore, three epitopes were predicted to have high potency as the SARS-CoV-2 epitope-based vaccine.

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Published

2024-09-19

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