Author

Richard A. Friesner

Columbia UniversityORCID 0000-0002-1708-9342Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:protein structure· 3 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Research Focus:protein folding & dynamics· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Alina P. SergeevaiD· 2 shared Barry H. HonigiD· 2 shared Fabiana A. Bahna· 2 shared Jared M. SampsoniD· 2 shared Lawrence S. ShapiroiD· 2 shared Seetha M. Mannepalli· 2 shared Allan HaldaneiD· 1 shared Andrew G. BuchananiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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2 shared papersBiophysics

Alina P. SergeevaORCID

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Author profile →

3 papers

Recent·Most cited

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, Young Do Kwon, Eswar Reddem, Fabiana A. Bahna, Seetha M. Mannepalli, Baoshan Zhang, Peter D. Kwong, Lawrence S. Shapiro, Barry H. Honig, 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.

Journal of Molecular Biology · Aug 10, 2026Peer-reviewedBiophysics

Results of a large scale study of the binding of 50 type IIinhibitors to 348 kinases: The role of protein reorganization

Vardan H. Vardanyan, Allan Haldane, Howook Hwang, Dilek Coskun, Muyun Lihan, Edward B. Miller, Richard A. Friesner, Ronald M. Levy

This paper analyzes the binding of 50 type II inhibitors to 348 kinases, showing that protein reorganization significantly contributes to inhibitor selectivity with an AUC of ~0.8.

Journal of Medicinal Chemistry · Apr 9, 2026Peer-reviewedBiophysics

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

Jared M. Sampson, Daniel A. Cannon, Jianxin Duan, J. C. K. Epstein, Alina P. Sergeeva, Phinikoula S. Katsamba, Seetha M. Mannepalli, Fabiana A. Bahna, Hélène Adihou, Stéphanie M. Guéret, Ranganath Gopalakrishnan, Stefan Geschwindner, D. Gareth Rees, Anna Sigurdardottir, Trevor C. I. Wilkinson, , 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.

Journal of Molecular Biology · Apr 24, 2024Peer-reviewedBiophysics