| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T215 |
0-38 |
Sentence |
denotes |
Predicting cross reactivity to 1G4 TCR |
| T216 |
39-175 |
Sentence |
denotes |
To gauge the level of 1G4 TCR cross-reactivity to list of 2019-nCoV virus, we have leveraged the data from a recently published study 7. |
| T217 |
176-324 |
Sentence |
denotes |
1G4 or NY-ESO-1-specific TCR is a very well-studied and clinically efficacious TCR which recognize the peptide ‘SLLMWITQC’ presented by HLA-A*02:01. |
| T218 |
325-531 |
Sentence |
denotes |
Karapetyan et al. have recently provided data from three experimental assays reflecting Binding, Activating and Killing upon each mutation at each position of all possible 9-mers using these three datasets. |
| T219 |
532-687 |
Sentence |
denotes |
In a similar way to the original paper, we trained three Position Weight Matrices named B, A and K respectively from Binding, Activating and Killing assay. |
| T220 |
688-788 |
Sentence |
denotes |
We defined the cross-reactivity score of a given 9-mer sequence as the geometric mean of B, A and K. |
| T221 |
789-932 |
Sentence |
denotes |
We then scanned 2019-nCoV virus protein sequence with each of B, A and K PWMs and associated each of 9613 9-mers with a cross reactivity score. |
| T222 |
933-1021 |
Sentence |
denotes |
At the same we utilized NetMHCpan and associated each 9-mer with its presentation score. |
| T223 |
1022-1220 |
Sentence |
denotes |
Our final list of cross-reactive candidate peptides were those with a cross-reactivity sore >= 0.8 and reported as strong binders from NetMHCpan and have ‘L’ and ‘V’ amino acids at anchor positions. |
| T224 |
1221-1308 |
Sentence |
denotes |
The custom R codes are accessible from GitHub repository (see software availability 4). |
