In silico epitope prediction and multi-epitope vaccine design targeting human elongation factor 1-Alpha 1 (EF1A1)
| bracu.degree.level | Undergraduate | |
| bracu.type.group | Student Works | |
| datacite.rights | Open Access | |
| dc.contributor.advisor | Siam, Mohammad Kawsar Sharif | |
| dc.contributor.author | Alif, Mottakian Ahamed | |
| dc.contributor.department | School of Pharmacy | |
| dc.date.accessioned | 2026-08-24T08:07:34Z | |
| dc.date.available | 2026-08-24T08:07:34Z | |
| dc.date.copyright | 2026 | |
| dc.date.issued | 2026-06 | |
| dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2026. | |
| dc.description | Cataloged from PDF version of thesis. | |
| dc.description | Includes bibliographical references (pages 41-47). | |
| dc.description.abstract | Worldwide dissemination of SARS-CoV-2 have accentuated the necessity for effective vaccines. Here, a design for multiepitope vaccine (MEV) was applied. The epitope pools were computationally predicted, and many tests were done for CTL, HTL and B-cell epitopes. The chosen epitopes were connected to form a single construct using appropriate linkers in order to maintain structural configuration and maximise immunogenicity. The vaccine's physicochemical properties and stability were tested utilizing ProtParam, its 3D structure predicted through Phyre2 and validated via Ramachandran plots, ERRAT, QMEAN affirming a credible stereochemical conformation. The docking study of interaction with Toll-like receptor 8 (TLR8) is for binding affinity of the design. In silico simulations utilizing C-ImmSim indicated strong antibody responses (IgM, IgG1, IgG2), activated CD4⁺ and CD8⁺ T cells in balanced states with quality memory formation based on combined Th1/Th2-derived cytokine profiles. In summary, the in-silico analyses suggest that it is highly immunogenic, not structurally unstable. Now it should provide a logic basis for experimental validation and rapid vaccine development against current and emergent viral variants. | |
| dc.description.degree | Bachelor of Pharmacy | |
| dc.description.statementofresponsibility | Mottakian Ahamed Alif | |
| dc.format.extent | 60 pages | |
| dc.identifier.other | ID 22146020 | |
| dc.identifier.uri | https://hdl.handle.net/10361/29492 | |
| dc.language.iso | en_US | |
| dc.publisher | BRAC University | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights | BRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | SARS-CoV-2 | |
| dc.subject | Molecular docking | |
| dc.subject | Multi-epitope vaccines | |
| dc.subject | Immunogenicity | |
| dc.subject | HTL epitope | |
| dc.subject | CTL epitope | |
| dc.subject | B-cell epitope | |
| dc.subject | Epitope mapping | |
| dc.subject.lcsh | Vaccines--Design. | |
| dc.subject.lcsh | Immunological tolerance--Computer simulation. | |
| dc.subject.lcsh | Immune response. | |
| dc.title | In silico epitope prediction and multi-epitope vaccine design targeting human elongation factor 1-Alpha 1 (EF1A1) | |
| dc.type | Thesis |