Evidence map›Paper›PMID 42575164›Full record

ArticleJournal of molecular biology2026

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 Shapiro and 2 more

Abstract read
In one paragraph

Article in Journal of molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Jared M SampsonDepartment of Biochemistry and Molecular Biophysics, Columbia University, United States; Department of Chemistry, Columbia University, United States; Life Sciences Software, Schrödinger, Inc, United States.
Alina P SergeevaDepartment of Biochemistry and Molecular Biophysics, Columbia University, United States; Department of Systems Biology, Columbia University, United States.
Tianyang GaoDepartment of Chemistry, Columbia University, United States.
Young Do KwonVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States.
Eswar ReddemZuckerman Mind Brain Behavior Institute, Columbia University, United States.
Fabiana A BahnaZuckerman Mind Brain Behavior Institute, Columbia University, United States.
Seetha M MannepalliZuckerman Mind Brain Behavior Institute, Columbia University, United States.
Baoshan ZhangVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States.
Peter D KwongDepartment of Biochemistry and Molecular Biophysics, Columbia University, United States; Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States; Aaron Diamond AIDS Research Center, Columbia University, United States; Department of Medicine, Columbia University, United States.
Lawrence ShapiroDepartment of Biochemistry and Molecular Biophysics, Columbia University, United States; Zuckerman Mind Brain Behavior Institute, Columbia University, United States; Aaron Diamond AIDS Research Center, Columbia University, United States.
Barry HonigDepartment of Biochemistry and Molecular Biophysics, Columbia University, United States; Department of Systems Biology, Columbia University, United States; Zuckerman Mind Brain Behavior Institute, Columbia University, United States. Electronic address: bh6@cumc.columbia.edu.
Richard A FriesnerDepartment of Chemistry, Columbia University, United States. Electronic address: raf8@columbia.edu.

Funding

Genome-wide structure-based analysis of protein-protein interactions and networksR35GM139585 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BARRY H HONIG · 2021 to 2026
$2.7M
NIGMS NIH HHS R35 GM139585
6 · The paper itself

Abstract

Accurate calculation of energy changes upon mutation is a key requirement for the effective use of computational methods in protein design. In this study, we applied free energy perturbation (FEP) calculations to predict the effects of mutations on the binding free energy between the immunoglobulin G (IgG) antibody fragment-crystallizable (Fc) region and the neonatal Fc receptor (FcRn), an interaction that is primarily responsible for antibody half-life. We assembled an extensive experimental dataset of Fc-FcRn binding affinities for wild-type (wt) and mutant complexes, including values from literature and from newly measured results. Starting from a crystal structure of the M252Y/S254T/T256E ("YTE") Fc variant bound to FcRn, we prepared all-atom models of human IgG1-subtype wt and YTE variant Fc-FcRn complexes, adding explicit hydrogens and assigning protonation states for key ionizable residues. Initial results using standard FEP protocols to compute relative binding free energies were promising but exhibited multiple outliers. By accounting for coupling effects for FEP mutations near key histidine residues, we improved the results for several outliers, suggesting such coupling as an important approach for pH-sensitive systems. Further, upon determining new crystal structures of wt Fc and three Fc variants at multiple pH values, we observed subtle conformational changes in unbound Fc; by accounting for these conformational changes in FEP calculations, we additionally improved agreement with experiment. The detailed structural and energetic analyses of the Fc-FcRn system we present here thus provide a practical energy-calculation framework to enable rational in silico design of novel Fc variants. SIGNIFICANCE: Antibody mutations that increase half-life are of high medical importance; unfortunately, these have been difficult to predict computationally. In this study of the Fc-FcRn complex, which controls antibody half-life via differential affinity at different pHs, we demonstrate a successful computational approach using free energy perturbation (FEP) calculations. Our prediction of accurate binding energies across a wide range of cases speaks to the power of the FEP methodology in navigating the free energy landscapes of dynamic molecular complexes. Furthermore, we show that accurate Fc-FcRn affinity calculations required careful consideration of conformational flexibility between bound and unbound states, contributing to our functional understanding of a system that will be important for future rational antibody-design efforts.

Indexed as

Histocompatibility Antigens Class IImmunoglobulin Fc FragmentsImmunoglobulin GReceptors, FcBinding SitesComputer SimulationHumansModels, MolecularMutationProtein BindingThermodynamicsFc receptor, neonatalHistocompatibility Antigens Class IImmunoglobulin Fc FragmentsImmunoglobulin GReceptors, Fcantibody-receptor interactionsbinding affinity predictionfree-energy methods

Identifiers

PMID42575164
PMCPMC13548062

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.