Flexible regions in the molecular architecture of Human fibrin clots structurally resolved by XL-MS and integrative structural modeling

Abstract

Upon activation, fibrinogen forms large fibrin biopolymers that coalesce into clots that assist in wound healing. Limited insights into their molecular architecture, due to the sheer size and insoluble character of fibrin clots, have however restricted our ability to develop novel treatments for clotting diseases. The so far resolved disparate structural details did provide insights into linear elongation; however, molecular details like the C-terminal domain of the α-chain, the heparin-binding domain on the β -chain, and others involved in lateral aggregation are lacking. To illuminate these dark areas, we applied crosslinking mass spectrometry (XL-MS) to obtain biochemical evidence in the form of over 300 distance constraints and combined this with structural modeling. These restraints additionally define the interaction network of the clots and e.g. provide molecular details for the interaction with Human Serum Albumin (HSA). We were able to construct the models of fibrinogen α(excluding two highly flexible regions) and β , confirm these models with known structural arrangements and map how the structure laterally aggregates to form intricate lattices together with fibrinogen γ. We validate the final model by mapping mutations leading to impaired clot formation. From a list of 22 mutations, we uncovered structural features for all, including a crucial role for β Arg'196 in lateral aggregation. The resulting model will be invaluable for research on dysfibrinogenemia and amyloidosis, as it provides insights into the molecular mechanisms of thrombosis and bleeding disorders related to fibrinogen variants. The structure is provided in the PDB-DEV repository.

A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes

“…Additionally, when using XlinkX for the analysis of data in which cleavable crosslinkers were used, the score cut-offs are important in filtering for high-quality data that more likely allow correct crosslink identification. One should be aware that while such cut-offs work well in this study and others 30,31 , they give no indication of the confidence in crosslink assignment. Judging by the data, different cut-off values could be optimised for different fragmentation techniques.…”

A synthetic peptide library for benchmarking crosslinking mass spectrometry search engines

“…Additionally, when using XlinkX for the analysis of data in which cleavable crosslinkers were used, the score cut-offs are important in filtering for high-quality data that more likely allow correct crosslink identification. One should be aware, that while such cut-offs work well in this study and others [30,31], they give no indication of the confidence in crosslink assignment.…”