| Literature DB >> 33761582 |
Anusha Uttarilli1,2, Sridhar Amalakanti1, Phaneeswara-Rao Kommoju1, Srihari Sharma1, Pankaj Goyal3, Gowrang Kasaba Manjunath1, Vineet Upadhayay1, Alisha Parveen4, Ravi Tandon5, Kumar Suranjit Prasad6, Tikam Chand Dakal7, Izhar Ben Shlomo8, Malik Yousef9,10, Muniasamy Neerathilingam1,2, Abhishek Kumar1,2.
Abstract
The pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people and claimed thousands of lives. Starting in China, it is arguably the most precipitous global health calamity of modern times. The entire world has rocked back to fight against the disease and the COVID-19 vaccine is the prime weapon. Even though the conventional vaccine development pipeline usually takes more than a decade, the escalating daily death rates due to COVID-19 infections have resulted in the development of fast-track strategies to bring in the vaccine under a year's time. Governments, companies, and universities have networked to pool resources and have come up with a number of vaccine candidates. Also, international consortia have emerged to address the distribution of successful candidates. Herein, we summarize these unprecedented developments in vaccine science and discuss the types of COVID-19 vaccines, their developmental strategies, and their roles as well as their limitations.Entities:
Keywords: COVID-19; SARS-CoV-2; vaccine development
Mesh:
Substances:
Year: 2021 PMID: 33761582 PMCID: PMC8035961 DOI: 10.1515/jib-2021-0002
Source DB: PubMed Journal: J Integr Bioinform ISSN: 1613-4516
Figure 1:Stages of vaccine development. Vaccines requires largely five major steps, starting with preclinical tests in animal models, phase I involves limited number of human individuals and each of the next steps needs exponible increments of human individuals and it decreases change of success to reach to next levels and only limited numbers of vaccines are approved for public use by regulatory agencies of different countries.
Advantages and disadvantages of each vaccine strategy.
| Type of vaccine | Advantages | Disadvantages |
|---|---|---|
| Live attenuated | (i) Most immunogenic(ii) Confer long-term immunity after only one or two doses [ | (i) Antibody-dependent enhancement (ADE) of infection and disease [ |
| Whole inactivated | (i) High stability(ii) Can be given in immunocompromised people [ | (i) Weaker immune response than live-attenuated vaccines [ |
| Bacterial vector | Safer [ | Require multiple doses and adjuvants [ |
| Viral vector | Safe and potent at low doses [ | Transgene-specific response may be dampened by immune responses to antigenic targets within the vector itself [ |
| Protein subunits | (i) Low incidence of adverse reactions | May need adjuvants [ |
| (ii) Non-infectious [ | ||
| Nucleic acid based | (i) Mimics infection(ii) Easy manipulation of antigen(iii) Economical production [ | (i) Administered foreign DNA may persist for a long period(ii) Administered foreign DNA may interact with the host [ |
| Synthetic peptide | (i) Low incidence of reactions | May need adjuvants [ |
| (ii) Economical production | ||
| (iii) Non infectious |
Bioinformatics tools for COVID-19 vaccine development used in the computational analyses, reduced from focused reviews [19], [20].
| Number | Tool | Description |
|---|---|---|
| 1 | EpiMatrix | Maps T-cell epitopes across HLA class I and II |
| 2 | ClustiMer | Identifies promiscuous epitopes |
| 3 | Conservatrix | Identifies epitopes conserved across pathogen sequence variants |
| 4 | BlastiMer | Identifies epitopes with homology to autologous human proteins or to another organism of interest |
| 5 | EpiAssembler | Assembles overlapping epitopes to immunogenic consensus sequence |
| 6 | Optimatrix | Strategically alters peptides to optimize aggretope |
| 7 | Aggregatrix | Selects a set of peptides to maximize coverage of pathogen sequence variants |
| 8 | VaccineCAD | Minimizes “nonsense” immunogenicity at the junctions between epitopes in a string of beads construct |
| 9 | TepiTool | Provides some of the top MHC class I and class II binding prediction algorithms for number of species including humans, chimpanzees, bovines, gorillas, macaques, mice and pigs. The tool is designed as a user-friendly wizard with well-defined steps which helps the users to predict the best MHC binding peptides from their sequences of interest |
| 10 | PriSeT | Does computing of specific primers of SARS CoV2 for RT-PCR |
| 11 | CoVPipe | Helps in reproducible, reliable and fast analysis of NGS data |
| 12 | poreCov | It reduces the time-consuming bioinformatic bottlenecks in processing sequencing runs |
| 13 | VADR | It validates and annotates SARS CoV 2 |
| 14 | V-Pipe | Reproduces NGS-based, end-to-end analysis of genomic diversity in intra-host virus populations |
| 15 | Haploflow | It detects and also does full-length reconstruction of multi-strain infections |
| 16 | VIRify | Identifies viruses in clinical samples |
| 17 | VBRC genome analysis tools | Visualizes the differences between coronavirus sequences at different levels of resolution |
| 19 | VIRULIGN | Fast, codon-correct multiple sequence alignment and annotation of virus genomes |
| 20 | Rfam COVID-19 | It annotates structured RNAs in coronavirus sequences and predicts the secondary structures |
| 21 | UniProt COVID-19 | Provides the latest information on proteins and its relevance to the disease for virus and host |
| 22 | Pfam | It detects protein and annotates for outbreak tracking and studying evolution |
| 23 | BLAST | It helps in detection of homologous regions of a given motif of vaccine candidate |
Figure 2:Phases of vaccine production in the normal (non-pandemic) versus accelerated pandemic COVID-19 threat. (A) Normally, it takes approx. 10 years for the approval of a single vaccine. (B) In the COVID-19 pandemic situation, the time period has been shortened to 18–20 months for the approval.
Figure 3:Types of COVID-19 vaccines.