Author

Andrew Reckers

Columbia UniversityORCID 0000-0002-7567-8540Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:protein folding & dynamics· 2 Assay:proteomics· 2 Organism:E. coli· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Anum Azam GlasgowiD· 2 shared Chenlin LuiD· 2 shared Savannah K. McBrideiD· 2 shared Kyle C. WeberiD· 1 shared Malcolm L. WellsiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 9 mutual co-author links

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2 shared papersBiophysics

Anum Azam GlasgowORCID

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2 papers

Recent·Most cited

A machine learning method for calculating highly localized protein stabilities

Chenlin Lu, Kyle C. Weber, Savannah K. McBride, Andrew Reckers, Anum Azam Glasgow

PFNet calculates residue-level free energy of opening from HX/MS data, enabling scalable and accessible protein stability analysis.

Nature Communications · Sep 1, 2026Peer-reviewedBiophysics

Site-resolved energetic information from HX/MS experiments

Chenlin Lu, Malcolm L. Wells, Andrew Reckers, Savannah K. McBride, Anum Azam Glasgow

This paper introduces PIGEON-FEATHER, a method to calculate free energies of protein conformational ensembles from HX/MS data, revealing evolutionary differences in enzyme inhibitors and ligand-induced reweighting in a protein-DNA complex.

Nature Chemical Biology · Oct 17, 2025Peer-reviewedBiophysics