| Literature DB >> 32683296 |
Zahra Noorimotlagh1, Chiman Karami2, Seyyed Abbas Mirzaee1, Mohammadreza Kaffashian3, Sanaz Mami4, Mahdieh Azizi5.
Abstract
The beginning of 2020 was marked as the emergence of a COVID-19 outbreak caused by a new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, there is no vaccine or approved treatment for this infectious virus so the invention of an efficient vaccine is certainly a high priority. Some studies have employed several techniques to facilitate the combination of the immunoinformatics approach and comparative genomic approach in order to determine the potential peptides for designing the T-cell epitope-based peptide vaccine using the 2019-nCoV envelope protein as a target. Via screening the bioimmunoinformatic SARS-CoV2 derived B-cell and T-cell epitopes within the basic immunogenic of SARS-CoV2 proteins, we presented a set of inferred B-cell and T-cell epitopes from the spike (S) and nucleocapsid (N) proteins with high antigenicity and without allergenic property or toxic effects. Our findings provide a screened set of epitopes that can be introduced as potential targets for developing peptide vaccines against the SARS-CoV-2 virus.Entities:
Keywords: B-cell epitopes; Bioinformatics; COVID-19; SARS-CoV-2; T-cell epitopes
Mesh:
Substances:
Year: 2020 PMID: 32683296 PMCID: PMC7321027 DOI: 10.1016/j.intimp.2020.106738
Source DB: PubMed Journal: Int Immunopharmacol ISSN: 1567-5769 Impact factor: 4.932
Fig. 1Summary of a standard four-step protocol for literature review.
Summary of the main detailed of the included studies.
| Study ID | Type of Protein | B cell epitope | T cell epitope | Antigenicity | HLA Class I | HLA Class II | Threshold | Score | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| B cell | T cell | B cell | T cell | B cell | T cell | ||||||
| (Grifoni et al., 2020), USA | Surface glycoprotein | ✓ | ✓ | – | – | ✓ | – | ✓ | ✓ | – | ✓ |
| (Baruah and Bose, 2020), India | Surface glycoprotein | ✓ | ✓ | ✓ | ✓ | ✓ | – | ✓ | ✓ | – | ✓ |
| (Kumar et al., 2020), India | Spike protein | – | ✓ | – | ✓ | – | – | – | – | – | ✓ |
| (Ahmed et al., 2020), China | Surface glycoprotein | ✓ | ✓ | – | – | ✓ | ✓ | – | – | – | – |
| (Abdelmageed et al., 2020), Sudan | Envelope Protein | – | ✓ | – | ✓ | ✓ | ✓ | – | ✓ | – | – |
| (Sarkar et al., 2020), Bangladesh | Nucleocapsid phosphoprotein | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | – | – |
| (Li et al., 2020), China | Spike protein | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| (Saha and Prasad, 2020), India | Spike protein | – | ✓ | – | ✓ | ✓ | ✓ | – | ✓ | – | ✓ |
| (Ismail et al., 2020), Pakistan | Spike protein | ✓ | ✓ | – | ✓ | ✓ | ✓ | – | ✓ | ✓ | – |
| (Kalita et al., 2020), India | Nucleocapsid protein | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | – | ✓ | – |
| (Bhattacharya et al., 2020), Korea | spike protein | ✓ | ✓ | – | ✓ | ✓ | ✓ | – | ✓ | – | – |
| (Bojin et al., 2020), Romania | Spike protein | – | ✓ | – | – | ✓ | ✓ | – | – | – | ✓ |
| (Rehman et al., 2020), Pakistan | spike glycoprotein | ✓ | – | – | – | – | – | – | – | – | – |
Literature review of characteristics of B-cell epitopes identified in SARS-CoV-2.
| Study ID | linear B‐cell epitopes/ length | Antigenicity | Threshold | Score | Results |
|---|---|---|---|---|---|
| – | cutoff of 0.55 (corresponding to specificity greater than 0.81 and sensitivity below 0.3) | – | SARS-CoV epitopes in conjunction with bioinformatic predictions points to specific regions of SARS-CoV-2 that have a high likelihood of being recognized by human immune responses. The observation that many B and T cell epitopes are highly conserved between SARS-CoV-2 and SARS-CoV is important | ||
| 1.38 | 0.51 | IFN‐γ epitope | Three sequential B cell epitopes in the viral surface glycoprotein can be potential candidates for the development of 2019‐nCoV vaccines. | ||
| – | – | – | |||
| Antigenic (0.534) | Antigenicity | – | |||
| 1.2606 | 0.9 | 0.9 | The B- and T-cell epitopes identified here may assist the development of potent peptide-based vaccines to address the SARS-CoV-2 | ||
| – | – | Linear B cell epitopes were mapped using Bepipred Linear Epitope Prediction 2.0 and | |||
| – | 0.94 | A multi-epitope-based subunit vaccine was including highly antigenic epitopes from three virus proteins and had a good protective efficacy and safety against SARS-CoV-2 infection | |||
| – | – | – | |||
| – | – | – | Potential T-cells and B-cell epitopes (continuous) |
Literature review of characteristics of T-cell epitopes identified in SARS-CoV-2.
| Study ID | T cell epitope | MHC I & MHC II | Antigenicity | Threshold | Score | Results |
|---|---|---|---|---|---|---|
| – | HLA class II = . cutoff%20 | RF ≥ 0.3 | Virus Parallel | |||
| * (0.45)% | 0.5 | 0.83/0.64 | One overlapping CTL epitope between MERS‐CoV and 2019‐nCoV with one gap and one mismatch | |||
| *357 | – | scores > 1.25 = highest sensitivity | Spike glycoprotein sequences of 2019-nCoV and SARS-CoV exhibits 76.2% identity, 87.2% similarity and 2% Gaps | |||
| – | – | – | ||||
| 0.6025 | 0.4 | – | the following 10 peptide in MHC1 with the highest world population, coverage as a good candidate for vaccine, another 10 peptides in | |||
| 0.4 | – | potential subunit vaccines were designed against the SARS-CoV-2 using various methods of reverse vaccinology and immunoinformatics | ||||
| MHC-1 | MHC-1 | MHC-1 = 3 | ||||
| MHC-1 | 0.4 | score > 1 | 5 MHC I and 5 MHC II epitopes with high antigenic potential and strong binding affinity within the S protein of 2019- nCoV | |||
| 0.5 | – | SARS-CoV-2 spike glycoprotein for antigenic peptides and proposed a MEPVC by means of several computational immunological methods and biophysical calculations | ||||
| Nucleocapsi | – | – | Multi-epitope-based subunit vaccine has a probability to show good protective efficacy | |||
| 0.4 | – | pointed out 13 MHC‐I and 3 | ||||
| – | – | Candidate peptides could counteract the novel China coronavirus by eliciting both CD4 + and CD8 + T cell responses |