Fig. 6: Application of Scout and MSAnnika to biological proteome-wide XL-MS datasets.
a, Entrapment database search on a published dataset of Azide-A-DSBSO cross-linked human mitochondria25. The data were searched against 2,000 random human mitochondria proteins sampled from a linear peptide search on the XL-MS data, supplemented with 2,000 random E. coli BL21 protein sequences. Interspecies cross-links and E. coli cross-links were considered false. Percentages indicate the resulting empirical FDR. b, Evaluation of PPIs identified from a HEK cell Azide-A-DSBSO XL-MS dataset. Brown, light blue and dark blue correspond to different STRING confidence score ranges. Yellow represents identifications that could not be found in STRING or that are considered impossible because they match to the Negatome database. In a and b, PPI-level results for Scout were either determined using the PPI-FDR filter (Scout) or by aggregation of ResPairs to unique protein pairs (Scout*). The second approach was also used for MSAnnika. c, ResPair interlinks per PPIs identified with MSAnnika and PPI-FDR-controlled Scout on the Azide-A-DSBSO HEK dataset. d,e, Cα–Cα distances of ResPair interlinks identified by Scout (blue) and MSAnnika (brown) when mapped on AlphaFold-Multimer models of their identified PPIs. For each PPI, the model with the highest cross-link satisfaction was used for analysis. Shown are all interlink Cα–Cα distances that can be mapped on AlphaFold-Multimer models with a model confidence of at least 0.5 (d), as well as the spread of interlink Cα–Cα distances for different ranges of AlphaFold-Multimer model confidence (e). In both cases, only interlinks between residues with a pLDDT score above 50 (indicating an ordered protein region) are considered. Boxes in e range from first to third quartile with the median indicated as a horizontal line. Whiskers represent 1.5 times the interquartile range. The violin plot shows that full data distribution, including minima and maxima.
