Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation


Arwansyah, A.R. Arif, A. Kade, M. Taiyeb, I. Ramli and T. Santoso, P. Ningsih, H. Natsir, T. Tahril and K. Uday Kumar (2022) Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation. SAR and QSAR in Environmental Research Vol 33, Issue 9, pp. 1-27.

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Abstract (Abstrak)

The pandemic of COVID-19 caused by SARS-CoV-2 has made a worldwide health emergency. Despite the fact that current vaccines are readily available, several SARSCoV-2 variants affecting the existing vaccine are to be less effective due to the mutations in the structural proteins. Furthermore, the appearance of the new variants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vaccines are still pivotal works for preventing the spread of the virus. In the present investigation, the computational analysis through immunoinformatics, molecular docking, and molecular dynamics (MD) simulation is employed to construct an effective vaccine against SARS-CoV2. The structural proteins of SARS-CoV2 are utilized to create a multiepitope-based vaccine (MEV). According to our findings presented by systematic procedures in the current investigation, the MEV construct may be able to trigger a strong immunological response against the virus. Therefore, the designed MEV could be a potential vaccine candidate against SARS-CoV-2, and also it is expected to be effective for other variants

Item Type: Article
Uncontrolled Keywords: MEV; SARS-CoV2; immunoinformatics; in silico; vaccine design
Divisions (Program Studi): Fakultas Matematika dan Ilmu Peng. Alam > Kimia
Depositing User: Dr. Iskandar Iskandar
Date Deposited: 15 Sep 2022 05:42
Last Modified: 15 Sep 2022 05:42
URI: http://repository.unhas.ac.id:443/id/eprint/19089

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