Crosslinking mass spectrometry captures protein structures in solution. The crosslinks reveal spatial proximities as distance restraints, but do not easily reveal which of these restraints derive from the same protein conformation. This superposition can be reduced by photo-crosslinking, and adding information from protein structure models, or quantitative crosslinking reveals conformation-specific crosslinks. As a consequence, crosslinking MS has proven useful already in the context of multiple dynamic protein systems. We foresee a breakthrough in the resolution and scale of studying protein dynamics when crosslinks are used to guide deep-learning-based protein modelling. Advances in crosslinking MS, such as photoactivatable crosslinking and in-situ crosslinking, will then reveal protein conformation dynamics in the cellular context, at a pseudo-atomic resolution, and plausibly in a time-resolved manner.
Section snippetsIntroduction to crosslinking MSCrosslinking mass spectrometry (MS) captures the 3D structure of proteins by covalently connecting residues that are close in space. These links are then revealed using mass spectrometry and database searching, reminiscent of how proteins are identified in proteomics. However, several important alterations have been made to the standard proteomics workflow resulting from the fact that two linked peptides must be identified. In a typical crosslinking MS experiment, proteins are crosslinked in
Crosslinking MS and protein conformationsCrosslinking proteins sub-stoichiometrically aims at producing only a handful of crosslinks per protein molecule. Crosslinks formed in different molecules are then aggregated into a snapshot of residue proximities in the native structure of the investigated protein. This data aggregation has direct consequences when the protein populates multiple conformation states: crosslink data provides an aggregated image of these states. If high-resolution protein structure models exist, either
Quantitative crosslinking MSConformation-specific crosslinks can also be revealed independent of high-resolution structure models using quantitative crosslinking MS (QCLMS). When different protein conformations can be separated before or after crosslinking, they can be compared directly. A protein changing its conformation will also change which residue pairs can be crosslinked or the yield by which they may be crosslinked. The changes may result from altered residue proximity, solvent accessibility or steric
Photoactivated crosslinking of conformation dynamicsIn earlier applications, homo-bifunctional crosslinkers comprising NHS ester (and derivatives) have been the predominant choice [22,25]. In recent years, an increasing number of studies [17,20,21,26, 27, 28, 29, 30, 31] have applied photoactivated crosslinking (Box 2) to characterise protein conformational dynamics.
An NHS ester-based crosslinking reaction is typically incubated for tens of minutes to yield sufficient crosslinking products. After reacting with an amino acid on one end, a
Modelling protein conformation states using crosslink dataBiological systems can be understood better using crosslinking data if the crosslinks can be embedded in the context of atomic or pseudo-atomic models. As already pointed out above, dissonances between crosslinks and the model point towards alternative conformation states. In fact, crosslinks can even serve as starting points for generating structural models of alternative conformations. This is further facilitated when different conformation states can be enriched experimentally and then
OutlookSo far, detailed characterisation of protein conformational dynamics has been mainly carried out in isolated protein systems. Although challenging, it is conceivable to probe protein conformation states and their dynamics at the level of the proteome and in the cellular context. The first challenge is to identify sufficient crosslinks that can represent conformation states for a wide range of proteins in situ. These crosslinks not only have to be detected in mass spectrometry against the
Declaration of competing interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
AcknowledgementsThis work received funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2008/1 – 390540038. The Wellcome Centre for Cell Biology is supported by core funding from the Wellcome Trust (203149). For the purpose of open access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
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