Improved Peak Detection and Deconvolution of Native Electrospray Mass Spectra from Large Protein Complexes

Area of Science:

• Biochemistry
• Analytical Chemistry
• Structural Biology

Background:

• Native electrospray-ionization mass spectrometry (native MS) is crucial for analyzing large protein assemblies, preserving their structure.
• Native MS spectra often exhibit low signal-to-noise and broad peaks due to solvation and adduction, leading to peak overlap and complex charge envelopes.
• Accurate peak detection and charge state assignment are challenging in native MS, hindering the analysis of noncovalent assemblies.

Purpose of the Study:

• To develop a comprehensive algorithm, PeakSeeker, for improved peak detection, overlap resolution, and charge state assignment in native MS.
• To address the challenges posed by complex, heterogeneous, and noisy native mass spectra of large protein assemblies.

Main Methods:

• Developed PeakSeeker, an algorithm utilizing the second derivative of the mass spectrum for overlapped peak detection.
• Employed fitting linear combinations of charge envelopes to assign charge state distributions to molecular species.
• Validated the software on diverse datasets including synthetic mononucleosomes, RNA polymerase II/α-amanitin complex, and human TriC complex.

Main Results:

• PeakSeeker successfully deconvolutes heterogeneous, complex, and noisy native mass spectra.
• The algorithm accurately resolves severely overlapping peaks and interleaved ion signals.
• Demonstrated effective analysis of large protein assemblies with high background noise.

Conclusions:

• PeakSeeker provides a robust solution for analyzing challenging native MS data.
• The software enables more accurate mass determination and characterization of noncovalent biomolecular assemblies.
• This advancement facilitates deeper insights into the structure and function of protein complexes.