Energy Resolved Mass Spectrometry Data from Surfaced Induced Dissociation Improves Prediction of Protein Complex Structure

Native Mass Spectrometry (nMS) is
a versatile technique
for elucidating
protein structure. Surface-Induced Dissociation (SID) is an activation
method in tandem MS predominantly employed for determining protein
complex stoichiometry alongside information about interface strengths.
SID-nMS data can be collected over a range of acceleration energies,
yielding Energy Resolved Mass Spectrometry (ERMS) data. Previous work
demonstrated that the onset and appearance energy from SID-nMS can
be used in integrative computational and experimental modeling to
guide multimeric structure determination in some cases. However, the
appearance energy is a single data point, while the ERMS data provide
a full pattern of interface breakage. We hypothesized that incorporation
of ERMS data into multimeric protein structure prediction would significantly
outperform appearance energy. To test this hypothesis, we generated
models of 20 protein complexes with RosettaDock using subunits generated
from AlphaFold2. We simulated the ERMS data for each predicted model
and rescored based on its agreement to experimental ERMS data. We
demonstrated that more accurately predicted models exhibited simulated
ERMS data in better agreement with the experimental data. As part
of our ERMS-based rescoring, we matched or improved the RMSD of the
best scoring model compared to Rosetta in 16 out of 20 cases, with
4 out of 20 cases improving to become a highly accurate (below 5 Å)
structure. Finally, we benchmarked our method against our previously
published appearance energy-based rescoring and showed improvement
in 14 out of 20 cases, with 6 out of 20 becoming a highly accurate
(below 5 Å) model. Our method is freely available through Rosetta
Commons, with a usage tutorial and test files provided in the Supporting
Information.