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

Abstract

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.