Improved Interpretation of Protein Conformational Differences and Ligand Occupancy in Large-Scale Cross-Link Data.

Chemical cross-linking of proteins in complex samples, cells, or even tissues is emerging to provide unique structural information on proteins and complexes that exist within native or nativelike environments. The public database XLinkDB automatically maps cross-links to available structures based on sequence homology. Structures most likely to reflect protein conformations in the cross-linked sample are routinely identified by having cross-linked residues separated by Euclidean distances within the maximum span of the applied cross-linker. Solvent accessible surface distance (SASD), which considers the accessibility of the cross-linked residues and the path connecting them, is a better predictor of consistency than the Euclidean distance. However, SASDs of structures are not publicly available, and their calculation is computationally intensive. Here, we describe in XLinkDB version 4.0 the automatic calculation of SASDs using Jwalk for all cross-links mapped to structures, both with and without regard to ligands, and derive empirical maximum SASD spans for BDP-NHP and DSSO cross-linkers of 51 and 43 Å, respectively. We document ligands proximal to cross-links in structures and demonstrate how SASDs can be used to help infer sample protein conformations and ligand occupancy, highlighting cross-links sensitive to ADP binding in mitochondria isolated from HEK293 cells.