A machine learning method for calculating highly localized protein stabilities

Abstract The residue-level free energy of opening (∆G op ) is the thermodynamic descriptor of localized protein stability, providing valuable information about the protein ensemble at physiologically relevant timescales and conditions. PFNet instantly determines ∆G op for arbitrarily large proteins and complexes from conventional peptide-level hydrogen exchange-mass spectrometry (HX-MS) datasets. It unlocks the full potential of HX-MS, democratizing the method and establishing quantitative, scalable and accessible analysis.

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Publication Details

Journal
Nature Communications
Published
2026-09-01
DOI
https://doi.org/10.1038/s41467-026-75590-9
Citations
1
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
2.94

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article

A machine learning method for calculating highly localized protein stabilities

Kyle C. Weber, Chenlin Lu, Andrew Reckers, Savannah K. McBride et al.
1 citations
Nature Communications
Protein Structure and Dynamics
2.94
article

A machine learning method for calculating highly localized protein stabilities

Kyle C. Weber, Chenlin Lu, Andrew Reckers, Savannah K. McBride, Anum Glasgow
article en
1 citations

Abstract

Abstract The residue-level free energy of opening (∆G op ) is the thermodynamic descriptor of localized protein stability, providing valuable information about the protein ensemble at physiologically relevant timescales and conditions. PFNet instantly determines ∆G op for arbitrarily large proteins and complexes from conventional peptide-level hydrogen exchange-mass spectrometry (HX-MS) datasets. It unlocks the full potential of HX-MS, democratizing the method and establishing quantitative, scalable and accessible analysis.

Nature Communications
Columbia University (US)
National Science Foundation, National Institutes of Health, National Institute of General Medical Sciences, National Institute of Biomedical Imaging and Bioengineering
Openalex Percentile: Top 17%
Protein Structure and Dynamics
2.94
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A machine learning method for calculating highly localized protein stabilities — Kyle C. Weber, Chenlin Lu, et al. · Nature Communications (2026) | TGRS Research Map | TGRS