Fig. 4: Evaluation of the effects of the Thunder isolation polygon and DDA-PASEF optimization on HLAIp identification from samples with distinct peptide HLA-binding motifs. | Nature Communications

Fig. 4: Evaluation of the effects of the Thunder isolation polygon and DDA-PASEF optimization on HLAIp identification from samples with distinct peptide HLA-binding motifs.

From: Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model

Fig. 4

a All peptides (top) and predicted HLA binders (HLAIps, bottom) identified across the 1/K0 vs m/z dimensions; the left panels show all the peptides identified without polygon for all samples, and the right panels all the peptides identified with the Thunder polygon; the dotted lines delimit the perimeter of the Thunder isolation polygon. b Total peptides identified from two injection replicates in each method. c Total HLAIps identified from two injection replicates in each method. d Proportion of peptides (considering modifications) identified in function of their charge state. e Proportion of peptides with 8–13 AAS (8-13-mers). f Proportion of 8-13-mers predicted to bind each of the HLA alleles of the sample, or none of them (non-binder, NB). g Total HLAIps in the whole dataset obtained from the four samples and four methods in function of the HLA allele with the highest binding affinity.

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