A. Arwansyah, - and A.R. Arif, - and A. Kade, - and M. Taiyeb, - and I. Ramlie, - and T. Santoso, - and P. Ningsih, - and P. Ningsih, - and T. Tahrila, - and K. Uday Kumar, - Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation. SAR and QSAR in Environmental Research, 2022.
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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 vac- cines 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 var- iants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vac- cines 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 uti- lized 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 |
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Subjects: | Q Science > Q Science (General) |
Depositing User: | - Andi Anna |
Date Deposited: | 09 Nov 2022 01:46 |
Last Modified: | 09 Nov 2022 01:47 |
URI: | http://repository.unhas.ac.id:443/id/eprint/23080 |