Author

Jared M. Sampson

Columbia UniversityORCID 0000-0001-6441-1579Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein folding & dynamics· 2 Assay:protein structure· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Alina P. SergeevaiD· 2 shared Barry H. HonigiD· 2 shared Fabiana A. Bahna· 2 shared Lawrence S. ShapiroiD· 2 shared Richard A. FriesneriD· 2 shared Seetha M. Mannepalli· 2 shared Andrew G. BuchananiD· 1 shared Anna SigurdardottiriD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

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2 shared papersBiophysics

Alina P. SergeevaORCID

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2 papers

Recent·Most cited

BiophysicsJournal of Molecular BiologyPeer-reviewedAug 10, 2026

A functional investigation of antibody Fc-FcRn variant binding guided by in silico free energy perturbation methods

Jared M. Sampson, Alina P. Sergeeva, Tianyang Gao…·Richard A. Friesner

This paper uses free energy perturbation (FEP) calculations to predict and improve the accuracy of Fc-FcRn binding energy changes due to mutations, incorporating conformational changes and coupling effects.

DOI 10.1016/j.jmb.2026.169982

humanprotein structure

𝕏 PostBluesky

BiophysicsJournal of Molecular BiologyPeer-reviewedApr 24, 2024

Robust prediction of relative binding energies for protein-protein complex mutations using free energy perturbation calculations

Jared M. Sampson, Daniel A. Cannon, Jianxin Duan…·Lingle Wang

The paper benchmarks free energy perturbation calculations for predicting mutation effects on protein-protein binding affinity and introduces an automated method to improve accuracy.

24 citations

protein structuredeep learning