![]() ![]() It is promising to combat the COVID-19 by inducing the B-cells and T-cells that can perform immune responses against the SARS-CoV-2 spike protein. Proteolytic activation of spike protein by host cell proteases is also a critical determinant 21. Previous studies reveal that the spike protein of the SARS-CoV-2 plays a decisive role during the infection. ![]() The spike protein of the SARS-CoV-2 can latch onto cells and force the virus through the cell membrane, which enables the virus entry. Coronavirus is studded on its exterior with spike proteins, which are key components to infect and attack human cells 20. The genome sequencing of the SARS-CoV-2 is completed 8 and researchers have studied the details in the SARS-CoV-2 proteins 19. Multi-epitope vaccines can be powerful for fighting viral infections, providing excellent vaccine candidates for clinical trials. They contain the vital part of the virus to elicit either a cellular or a humoral immune response and they reduce unwanted components that can trigger adverse effects 18. Multi-epitope vaccines are constructed by multiple virus protein fragments rich in overlapping epitopes. Recently, researchers have worked on constructing multi-epitope vaccines by in silico methods based on immunoinformatics without the need to grow pathogens to accelerate the vaccine design process 15, 16, 17. Such process usually takes more than a year to result in efficacious vaccines and hence contributes very little to avoid the current spread of the disease 13, 14. Traditional process of vaccine design is based on growing pathogens, which represents a very time-consuming process of isolating, inactivating and injecting the virus that causes the disease 11, 12. Researchers have proposed several approaches to develop vaccines for the SARS-CoV-2 10. The main clinical features of the COVID-19 are fever, cough and myalgia or fatigue 6 the virus has caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and is associated with ICU (Intensive Care Unit) admission and high mortality rates 7.Ĭurrently, without a single specific antiviral therapy for SARS-CoV-2, the control methods of the COVID-19 are early diagnosis, reporting, isolation, supportive treatments, and timely publishing epidemic information with only limited impact on the coronavirus 8, 9. Efficacious vaccines are therefore desperately needed 5. First detected in December 2019 in Wuhan, the virus has spread globally, with basic reproduction number (R0) reaching 5.7 3, millions of deaths, and unprecedented financial, social and political impacts all over the world 4. Moreover, we trace the RNA mutations of the SARS-CoV-2 and ensure that the designed vaccine can tackle the recent RNA mutations of the virus.Ĭoronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 1, 2. ![]() ![]() In conclusion, this proposed artificial intelligence (AI) based vaccine discovery framework accelerates the vaccine design process and constructs a 694aa multi-epitope vaccine containing 16 B-cell epitopes, 82 CTL epitopes and 89 HTL epitopes, which is promising to fight the SARS-CoV-2 viral infection and can be further evaluated in clinical studies. Finally, we optimize and insert the codon sequence into a plasmid to ensure the cloning and expression efficiency. The 3D structure of the designed vaccine is predicted, refined and validated by in silico tools. The human population coverage, antigenicity, allergenicity, toxicity, physicochemical properties and secondary structure of the designed vaccine are evaluated via state-of-the-art bioinformatic approaches, showing good quality of the designed vaccine. We further use in silico methods to investigate the linear B-cell epitopes, Cytotoxic T Lymphocytes (CTL) epitopes, Helper T Lymphocytes (HTL) epitopes in the 26 subunit candidates and identify the best 11 of them to construct a multi-epitope vaccine for SARS-CoV-2 virus. By combining the in silico immunoinformatics and deep neural network strategies, the DeepVacPred computational framework directly predicts 26 potential vaccine subunits from the available SARS-CoV-2 spike protein sequence. In this study, we propose an in silico deep learning approach for prediction and design of a multi-epitope vaccine (DeepVacPred). Without an existing effective medical therapy, vaccines are urgently needed to avoid the spread of this disease. The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the social, financial and political entities around the world. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |