Characterizing Protein Solvent Accessible Surface Area in Solution by Dual Polarity Native Mass Spectrometry

Native mass spectrometry (nMS) is rapidly emerging as a pivotal technique for exploring protein conformations and protein-ligand interactions. Pioneering research has demonstrated that the charge state distribution (CSD) of proteins in native mass spectra can be indicative of their solvent accessible surface area (SASA). Moreover, beyond SASA, it is postulated that the abundance of acidic and basic amino acids on the protein surface may also impact the CSD. Specifically, basic amino acids tend to acquire positive charges during electrospray ionization (ESI), whereas acidic amino acids are prone to adopting negative charges. Consequently, this study investigates the CSDs of globular proteins in both positive and negative ion modes to provide a comprehensive characterization of protein SASA. Experiments were conducted under both native ESI and native nano-ESI conditions. By harnessing the average charges observed across dual polarity nMS data, we achieved significantly enhanced log linear correlations between protein SASA and its CSDs. The coefficient of determination (<i>R</i><sup>2</sup>) improved from 0.9866 to 0.9888 under ESI conditions and from 0.9677 to 0.9902 under nano-ESI conditions when compared to models utilizing only positive ion mode data. These findings suggest that the SASA of globular proteins can be effectively characterized through the CSDs derived from dual polarity nMS analysis.

Authors

Institutions

Publication Details

Journal
Journal of the American Society for Mass Spectrometry
Published
2025-04-01
DOI
https://doi.org/10.1021/jasms.4c00465
Citations
3
Primary Topic
Mass Spectrometry Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.27

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterizing Protein Solvent Accessible Surface Area in Solution by Dual Polarity Native Mass Spectrometry

Yi Zhao, Lei Yang, Wei Liang Xu, Wenjing Zhang et al.
3 citations
Journal of the American Society for Mass Spectrometry
Mass Spectrometry Techniques and Applications
2.27
article

Characterizing Protein Solvent Accessible Surface Area in Solution by Dual Polarity Native Mass Spectrometry

Yi Zhao, Lei Yang, Wei Liang Xu, Wenjing Zhang, Xinyan Fu
article en
3 citations

Abstract

Native mass spectrometry (nMS) is rapidly emerging as a pivotal technique for exploring protein conformations and protein-ligand interactions. Pioneering research has demonstrated that the charge state distribution (CSD) of proteins in native mass spectra can be indicative of their solvent accessible surface area (SASA). Moreover, beyond SASA, it is postulated that the abundance of acidic and basic amino acids on the protein surface may also impact the CSD. Specifically, basic amino acids tend to acquire positive charges during electrospray ionization (ESI), whereas acidic amino acids are prone to adopting negative charges. Consequently, this study investigates the CSDs of globular proteins in both positive and negative ion modes to provide a comprehensive characterization of protein SASA. Experiments were conducted under both native ESI and native nano-ESI conditions. By harnessing the average charges observed across dual polarity nMS data, we achieved significantly enhanced log linear correlations between protein SASA and its CSDs. The coefficient of determination (<i>R</i><sup>2</sup>) improved from 0.9866 to 0.9888 under ESI conditions and from 0.9677 to 0.9902 under nano-ESI conditions when compared to models utilizing only positive ion mode data. These findings suggest that the SASA of globular proteins can be effectively characterized through the CSDs derived from dual polarity nMS analysis.

Journal of the American Society for Mass SpectrometryVol. 36(5)
Beijing Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Mass Spectrometry Techniques and Applications
2.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.