5. Conclusions and Perspectives
Efforts to map a proteome-wide PPI network have made significant
contributions to our basic understanding of biological systems (Rual et
al., 2005). Scientists increasingly have deeper and comprehensive
insights into aberrant PPIs occurring in various pathological conditions
to strategically come up with effective therapeutic avenues (Ryan and
Matthews 2005). To this end, rational design of a potent modulator that
best counteracts abnormal PPIs would require detailed knowledge on a
binding interface of PPI with high fidelity comprising not only atomic
resolution but also “reality” existing in native environments. CLMS
and HDMS discussed herein are not competent enough for producing atomic
resolution of an interface comparable to that by X-ray crystallography
and EM. However, in terms of reality, they are especially useful in
extracting structural information in biological, native environment
including contact residues at interfaces, inter-residue distances,
peptide-level solvent accessibilities, and temporal dynamics of
interfacial areas, from which refined and near-physiological interfacial
landscape can be remodeled preferably using a preexisting structure as a
template. Exciting computational advances in data processing and
structural biology are greatly improving the fidelity of integration of
data obtained from both convention methods and CLMS/HDMS. High-fidelity
information of an interface thus acquired would serve as an excellent
cornerstone, increasing the likelihood of successful rational drug
discovery. Designer agonists or antagonists that recognize hot residues
in an interface responsible for a targeted PPI in a specific
pathological condition are expected to outperform conventional binders
with regard to both potency and efficacy.
Limitations of CLMS and HDMS remain to be overcome in future advances.
Specifically, CLMS users often suffer from excessive crosslinking
condition optimization and non-specific reactions that would compromise
precise measurement of spatial distances. Back exchange of deuterium in
HDMS hampers the reliable interpretation of solvent accessibility
dataset, necessitating effective sample treatment protocols by tricky
trial and error approach. Developments of new crosslinkers with
residue-specificity, bifunctionality, and/or reduced background mass
signals are expected to address the current challenges of CLMS (Ding et
al., 2016; Leitner et al., 2014; Lössl et al., 2014; Schneider et al.,
2018). Developments of improved workflows in HDMS should prove to be
innovative in the coming era (Hamuro and Zhang 2019; Lau et al., 2019;
Oganesyan et al., 2018). Together with novel MS instrumentation and
computational data processing techniques, all the efforts will continue
to advance CLMS and HDMS as excellent polishing tools for high-fidelity
structural determination of protein complexes and binding interfaces
thereof, thereby fueling the growth of structural proteomics and
biology, and, further, the advent of structure-based drug design regime
with exceptional reliability and probability (Figure 4).