subsequently be translated into structural restraints, which are then
used by a modeling workflow to generate 3D models of protein
assemblies. Moreover, several computational methods and tools
have been developed to assist the structural interpretation of
CX-MS [4, 6, 31]. Another MS-based labeling strategy that can
be used for modeling protein complexes includes covalent labeling
(CL)-MS. Covalent labeling is a chemical modification technique
that allows the mapping of residue-level surface accessibility. It
relies on the notion that exposed amino acid residues accessible to
the labeling reagents will readily react, while protected (buried)
residues respond to a lesser extent [32]. These differences in reactivity can be associated with conformational changes of proteins
and therefore be used to infer information regarding protein–protein or protein–ligand interactions [33].
1.4 Hydrogen–
Deuterium
Exchange MS
HDX-MS has recently gained interest for studying protein conformational dynamics and their associations with ligands [15, 34–
36]. HDX-MS can report on change in the structure and dynamics
of proteins, through monitoring the exchange of protein backbone
amide hydrogens for deuterium in the surrounding labeling buffer.
The exchange rate is dependent on both hydrogen bonding and
solvent accessibility [37–39]. HDX-MS tolerates a broad range of
sample environments and can be used to capture conformational
changes of proteins at peptide-level resolution. Data from two
protein states (e.g., apo and holo) can be compared in a differential
manner, allowing relative changes in protein structure and dynamics to be determined. The resulting significant differences (ΔHDX)
between the two states can in turn be mapped onto 3D models of
proteins to inform on conformational changes [37] (Fig. 1).
Recently HDX-MS has been applied to a range of membrane
proteins and their interactions with lipids [36, 40, 41]. Moreover,
attempts to model data derived from HDX-MS have utilized protection factors, which can be used as restraints to build model
structures directly from ΔHDX [42].
1.5 Integrating
with Other Structural
Approaches
While MS-based approaches offer a wide range of techniques capable of generating diverse structural information, their integration
with other powerful structural methods is often desirable. The
most commonly used methods to integrate MS data are X-ray
crystallography and cryo-EM. Traditionally, crystallographic information has been the gold standard to either validate the ability of a
computational strategy to build accurate models (benchmarking)
or be used in conjunction with other methods to refine its conformation. The recent resolution revolution of cryo-EM has yield a
game-changing effect in structural biology through its ability to
provide atomic-level resolution of proteins previously thought to
be insuperable (such as dynamic and membrane proteins), thus
significantly expanding the potential number of biological
Mass Spectrometry-Based Protein Modelling
223
used by a modeling workflow to generate 3D models of protein
assemblies. Moreover, several computational methods and tools
have been developed to assist the structural interpretation of
CX-MS [4, 6, 31]. Another MS-based labeling strategy that can
be used for modeling protein complexes includes covalent labeling
(CL)-MS. Covalent labeling is a chemical modification technique
that allows the mapping of residue-level surface accessibility. It
relies on the notion that exposed amino acid residues accessible to
the labeling reagents will readily react, while protected (buried)
residues respond to a lesser extent [32]. These differences in reactivity can be associated with conformational changes of proteins
and therefore be used to infer information regarding protein–protein or protein–ligand interactions [33].
1.4 Hydrogen–
Deuterium
Exchange MS
HDX-MS has recently gained interest for studying protein conformational dynamics and their associations with ligands [15, 34–
36]. HDX-MS can report on change in the structure and dynamics
of proteins, through monitoring the exchange of protein backbone
amide hydrogens for deuterium in the surrounding labeling buffer.
The exchange rate is dependent on both hydrogen bonding and
solvent accessibility [37–39]. HDX-MS tolerates a broad range of
sample environments and can be used to capture conformational
changes of proteins at peptide-level resolution. Data from two
protein states (e.g., apo and holo) can be compared in a differential
manner, allowing relative changes in protein structure and dynamics to be determined. The resulting significant differences (ΔHDX)
between the two states can in turn be mapped onto 3D models of
proteins to inform on conformational changes [37] (Fig. 1).
Recently HDX-MS has been applied to a range of membrane
proteins and their interactions with lipids [36, 40, 41]. Moreover,
attempts to model data derived from HDX-MS have utilized protection factors, which can be used as restraints to build model
structures directly from ΔHDX [42].
1.5 Integrating
with Other Structural
Approaches
While MS-based approaches offer a wide range of techniques capable of generating diverse structural information, their integration
with other powerful structural methods is often desirable. The
most commonly used methods to integrate MS data are X-ray
crystallography and cryo-EM. Traditionally, crystallographic information has been the gold standard to either validate the ability of a
computational strategy to build accurate models (benchmarking)
or be used in conjunction with other methods to refine its conformation. The recent resolution revolution of cryo-EM has yield a
game-changing effect in structural biology through its ability to
provide atomic-level resolution of proteins previously thought to
be insuperable (such as dynamic and membrane proteins), thus
significantly expanding the potential number of biological
Mass Spectrometry-Based Protein Modelling
223