Schema for IEDB Predictions - IEDB-Predicted Epitopes from Grifoni et al 2020
  Database: wuhCor1    Primary Table: cd4Epitopes Data last updated: 2020-03-24
Big Bed File Download: /gbdb/wuhCor1/epitopes/cd4Epitopes.bb
Item Count: 241
The data is stored in the binary BigBed format.

Format description: Browser extensible data, with extended fields for detail page
fieldexampledescription
chromNC_045512v2Reference sequence chromosome or scaffold
chromStart19870Start position in chromosome
chromEnd19915End position in chromosome
nameVIWDYKRDAPAHISTShort Name of item
score555Score from 0-1000
strand++ or -
thickStart19870Start of where display should be thick (start codon)
thickEnd19915End of where display should be thick (stop codon)
reserved233,212,201Used as itemRgb as of 2004-11-22
scoreValue12.0Epitope score
id184Link to source
descriptionorf1ab polyprotein_VIWDYKRDAPAHISTDescription

Sample Rows
 
chromchromStartchromEndnamescorestrandthickStartthickEndreservedscoreValueiddescription
NC_045512v21987019915VIWDYKRDAPAHIST555+1987019915233,212,20112.0184orf1ab polyprotein_VIWDYKRDAPAHIST
NC_045512v22000520050GQVDLFRNARNGVLI388+2000520050188,209,2469.0185orf1ab polyprotein_GQVDLFRNARNGVLI
NC_045512v22035020395QLGGLHLLIGLAKRF944+2035020395201,59,5519.0186orf1ab polyprotein_QLGGLHLLIGLAKRF
NC_045512v22041020455ELEDFIPMDSTVKNY1000+2041020455179,3,3820.0187orf1ab polyprotein_ELEDFIPMDSTVKNY
NC_045512v22053020575EIIKSQDLSVVSKVV888+2053020575218,90,7218.0188orf1ab polyprotein_EIIKSQDLSVVSKVV
NC_045512v22077020815KGIMMNVAKYTQLCQ1000+2077020815179,3,3820.0189orf1ab polyprotein_KGIMMNVAKYTQLCQ
NC_045512v22080020845TQLCQYLNTLTLAVP722+2080020845246,164,13415.0190orf1ab polyprotein_TQLCQYLNTLTLAVP
NC_045512v22081520860YLNTLTLAVPYNMRV1000+2081520860179,3,3820.0191orf1ab polyprotein_YLNTLTLAVPYNMRV
NC_045512v22131021355QIDGYVMHANYIFWR261+2131021355144,178,2546.7192orf1ab polyprotein_QIDGYVMHANYIFWR
NC_045512v22135521400NTNPIQLSSYSLFDM888+2135521400218,90,7218.0193orf1ab polyprotein_NTNPIQLSSYSLFDM

IEDB Predictions (epitopes) Track Description
 

Description

This composite track indicates the immune epitope predictions for B cells, CD4 T-cells and CD8 T-cells, using these software packages: B cells = BebiPred 2.0, CD4 = IEDB Tepitool, CD8 = NetMHCpan4.0EL

The color range for the markers is from dark blue (strong prediction) to dark red (weak prediction). Black is used for markers with no calculated prediction.

From the publication: Candidate targets for immune responses to 2019-Novel Coronavirus (nCoV): sequence homology- and bioinformatic-based predictions, full reference below.

The prediction of epitopes for CD8 T-cells was run for the following HLA alleles, as they have a worldwide population frequency > 6%

HLA allelesFrequency in worldwide population
HLA-A*01:0116.2
HLA-A*02:0125.2
HLA-A*03:0115.4
HLA-A*11:0112.9
HLA-A*23:016.4
HLA-A*24:0216.8
HLA-B*07:0213.3
HLA-B*08:0111.5
HLA-B*35:016.5
HLA-B*40:0110.3
HLA-B*44:029.2
HLA-B*44:037.6

Summary

We identified potential targets for immune responses to 2019-nCoV and provide essential information for understanding human immune responses to this virus and evaluation of diagnostic and vaccine candidates.

Abstract

Effective countermeasures against the recent emergence and rapid expansion of the 2019-Novel Coronavirus (2019-nCoV) require the development of data and tools to understand and monitor viral spread and immune responses. However, little information about the targets of immune responses to 2019-nCoV is available. We used the Immune Epitope Database and Analysis Resource (IEDB) resource to catalog available data related to other coronaviruses, including SARS-CoV, which has high sequence similarity to 2019-nCoV, and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in 2019-nCoV that have high homology to SARS virus. Parallel bionformatic predictions identified a priori potential B and T cell epitopes for 2019-nCoV. The independent identification of the same regions using two approaches reflects the high probability that these regions are targets for immune recognition of 2019-nCoV.

Credits

Data collected by Arkal Arjun Rao for the Sgourakis Research Group, U.C. Santa Cruz

References

Grifoni A, Sidney J, Zhang Y, Scheuermann RH, Peters B, Sette A. Candidate targets for immune responses to 2019-Novel Coronavirus (nCoV): sequence homology- and bioinformatic-based predictions, BioRxiv 2020 (doi: https://doi.org/10.1101/2020.02.12.946087)