Rehman, Hafiz Muzzammel and Mirza, Muhammad Usman and Ahmad, Mian Azhar and Saleem, Mahjabeen and Froeyen, Matheus and Ahmad, Sarfraz and Gul, Roquyya and Alghamdi, Huda Ahmed and Aslam, Muhammad Shahbaz and Sajjad, Muhammad and Bhinder, Munir Ahmad (2020) A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS-COV-2 by Comprehensive Immunoinformatic and Molecular Modelling Approach. Biology-Basel, 9 (9). ISSN 20797737, DOI https://doi.org/10.3390/biology9090296.
Full text not available from this repository.Abstract
Simple Summary COVID-19, caused by a novel coronavirus, SARS-CoV-2, first emerged in China in December 2019, and then spread around the globe with more than 29 million confirmed infections. Immunoinformatics and molecular modelling techniques are time-efficient methods that are used to accelerate the discovery and design of the candidate peptides for vaccine development against SARS-COV-2. Recently, the use of multiepitope vaccines has proved to be a promising immunization strategy against different viruses and other pathogens. In the current study a comprehensive in silico strategy was used to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins which include, spike, main protease, non-structural protein 12 (polymerase), and Nsp13 (helicase) with the help of adjuvants and linkers. Molecular dynamics studies revealed that the MVC displayed favourable molecular interactions with human Toll-like receptors (TLRs), which are known in triggering an innate and adaptive immune response. Furthermore, the MVC was checked for its recombinant production in Escherichia coli using a well-known expression system. The MVC showed a stable three-dimensional structure and could serve as a potential candidate for vaccine production, which warrant further experimental research for validation. The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the World Health Organization has declared it a pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. The urgency of the situation requires the development of SARS-CoV-2-based vaccines. Immunoinformatic and molecular modelling are time-efficient methods that are generally used to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines has proved to be a promising immunization strategy against viruses and pathogens, thus inducing more comprehensive protective immunity. The current study demonstrated a comprehensive in silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in silico cloning in a known pET28a vector system also estimated the possibility of MVC expression inEscherichia coli. Despite that this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can be present as a better prophylactic solution against COVID-19.
| Item Type: | Article |
|---|---|
| Funders: | Institute of Biochemistry and Biotechnology, University of the Punjab, Deanship of Scientific Research, King Faisal University (Grant No. 2/49/40) |
| Uncontrolled Keywords: | COVID-19; SARS-CoV-2; spike protein; multiepitope vaccine; molecular modeling |
| Subjects: | R Medicine |
| Divisions: | Faculty of Science > Department of Chemistry |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 30 Dec 2023 02:15 |
| Last Modified: | 30 Dec 2023 02:15 |
| URI: | http://eprints.um.edu.my/id/eprint/36455 |
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