| Literature DB >> 32864374 |
Abstract
PURPOSE: The aim of this research was to predict the epitope for coronavirus family spike protein. Coronavirus family is highly evolved viruses which cause several outbreaks in the past decades. Therefore, it is crucial to design a global vaccine candidate to prevent the coronavirus outbreak in the future.Entities:
Keywords: Coronavirus; Epitopes; Respiratory tract infections; Tools
Year: 2020 PMID: 32864374 PMCID: PMC7445319 DOI: 10.7774/cevr.2020.9.2.169
Source DB: PubMed Journal: Clin Exp Vaccine Res ISSN: 2287-3651
Coronavirus ID number
| No. | ID | Organism name |
|---|---|---|
| 1. | Q6Q1S2 | Human coronavirus NL63 (HCoV-NL63) |
| 2. | P36334 | Human coronavirus OC43 (HCoV-OC43) |
| 3. | P0DTC2 | Severe acute respiratory syndrome coronavirus 2 (2019-nCoV, SARS-CoV-2) |
| 4. | P59594 | Human SARS coronavirus (severe acute respiratory syndrome coronavirus, SARS-CoV) |
| 5. | P15423 | Human coronavirus 229E (HCoV-229E) |
| 6. | K9N5Q8 | Middle East respiratory syndrome-related coronavirus |
| 7. | Q0ZME7 | Human coronavirus HKU1 (isolate N5) (HCoV-HKU1) |
| 8. | Q5MQD0 | Human coronavirus HKU1 (isolate N1) (HCoV-HKU1) |
| 9. | Q14EB0 | Human coronavirus HKU1 (isolate N2) (HCoV-HKU1) |
Fig. 1Highly conserve region form coronavirus spike protein, amino acid number 945–1,100 was used to predict epitopes.
T cells epitopes prediction result
| No. | Start | Stop | Peptide | Methods | MHC class | Prediction based on | Tool | |||
|---|---|---|---|---|---|---|---|---|---|---|
| A | S | T | P | |||||||
| 1 | 1038 | 1046 | RVDFCGKGY | ANN | I | √ | √ | √ | √ | NetCTL |
| 2 | 1016 | 1024 | AEIRASANL | ANN | I | √ | IEDB-MHC I | |||
| 3 | 1015 | 1029 | AAEIRASANLAATKM | ANN | II | √ | IEDB-MHC II | |||
| 4 | 1038 | 1046 | RVDFCGKGY | SM | I and II | √ | MotifScan | |||
| 5 | 1041 | 1050 | FCGKGYHLM | QSAR | I and II | √ | MHCPred | |||
MHC, major histocompatibility complex; A, quantitative binding affinity; S, supertypes; T, TAP binding; P, proteasomal cleavage; ANN, artificial neural network; IEDB, Immune Epitope Database; SM, sequence motif; QSAR, quantitative structure-activity relationship model.
Linear B cells epitope predicted from highly conserved region
| No. | Start | Stop | Peptide | Tool | Method |
|---|---|---|---|---|---|
| 1. | 987 | 996 | EAEVQIDRL | Bepiprep | Machine learning-decision trees |
| 1034 | 1045 | LGQSKRVDFCGK | |||
| 2. | 1067 | 1075 | VPAQEKNFT | Emini Surface Accessibility Prediction | Propensity scale |
| 1085 | 1090 | GKAHFP | |||
| 3. | 1053 | 1059 | PQSAPHG | Chou and Fasman Beta-turn Prediction | Propensity scale |
| 4. | 960 | 966 | NTLVKQL | Kolaskar Tongaonkar Antigenicity | Propensity scale |
| 972 | 978 | ISSVLND | |||
| 1004 | 1011 | LQTYVTQQ | |||
| 1079 | 1084 | PAICHD | |||
| 5. | 1071 | 1147 | QEKNFTTAPAICHDGKAHFPREGVFVSNGTHWFVTQRNFYEPQIITT DNTFVSGNCDVVIGIVNNTVYDPLQPELDS | Ellipro |
Fig. 2Continuous B cells epitope predicted from highly conserved region and its residues (180 residues).
Fig. 3Selected highly conserved region for epitopes prediction is presented in yellow, T cell epitopes showed in underlined font, and B cell linear epitopes showed in red, numbers indicated the amino acid.