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Structural insights into neonatal Fc receptor-based recycling mechanisms.

ABSTRACT: We report the three-dimensional structure of human neonatal Fc receptor (FcRn) bound concurrently to its two known ligands. More particularly, we solved the crystal structure of the complex between human FcRn, wild-type human serum albumin (HSA), and a human Fc engineered for improved pharmacokinetics properties (Fc-YTE). The crystal structure of human FcRn bound to wild-type HSA alone is also presented. HSA domain III exhibits an extensive interface of contact with FcRn, whereas domain I plays a lesser role. A molecular explanation for the HSA recycling mechanism is provided with the identification of FcRn His(161) as the only potential direct contributor to the corresponding pH-dependent process. At last, this study also allows an accurate structural definition of residues considered for decades as important to the human IgG/FcRn interaction and reveals Fc His(310) as a significant contributor to pH-dependent binding. Finally, we explain various structural mechanisms by which several Fc mutations (including YTE) result in increased human IgG binding to FcRn. Our study provides an unprecedented relevant understanding of the molecular basis of human Fc interaction with human FcRn.

SUBMITTER: Oganesyan V

PROVIDER: S-EPMC3953293 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Structural insights into neonatal Fc receptor-based recycling mechanisms.

Oganesyan Vaheh V Damschroder Melissa M MM Cook Kimberly E KE Li Qing Q Gao Changshou C Wu Herren H Dall'Acqua William F WF

The Journal of biological chemistry 20140127 11

We report the three-dimensional structure of human neonatal Fc receptor (FcRn) bound concurrently to its two known ligands. More particularly, we solved the crystal structure of the complex between human FcRn, wild-type human serum albumin (HSA), and a human Fc engineered for improved pharmacokinetics properties (Fc-YTE). The crystal structure of human FcRn bound to wild-type HSA alone is also presented. HSA domain III exhibits an extensive interface of contact with FcRn, whereas domain I plays ...[more]

PMID: 24469444

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Project description:Salvage of endogenous immunoglobulin G (IgG) by the neonatal Fc receptor (FcRn) is implicated in many clinical areas, including therapeutic monoclonal antibody kinetics, patient monitoring in IgG multiple myeloma, and antibody-mediated transplant rejection. There is a clear clinical need for a fully parameterized model of FcRn-mediated recycling of endogenous IgG to allow for predictive modeling, with the potential for optimizing therapeutic regimens for better patient outcomes. In this paper we study a mechanism-based model incorporating nonlinear FcRn-IgG binding kinetics. The aim of this study is to determine whether parameter values can be estimated using the limited in vivo human data, available in the literature, from studies of the kinetics of radiolabeled IgG in humans. We derive mathematical descriptions of the experimental observations-timecourse data and fractional catabolic rate (FCR) data-based on the underlying physiological model. Structural identifiability analyses are performed to determine which, if any, of the parameters are unique with respect to the observations. Structurally identifiable parameters are then estimated from the data. It is found that parameter values estimated from timecourse data are not robust, suggesting that the model complexity is not supported by the available data. Based upon the structural identifiability analyses, a new expression for the FCR is derived. This expression is fitted to the FCR data to estimate unknown parameter values. Using these parameter estimates, the plasma IgG response is simulated under clinical conditions. Finally a suggestion is made for a reduced-order model based upon the newly derived expression for the FCR. The reduced-order model is used to predict the plasma IgG response, which is compared with the original four-compartment model, showing good agreement. This paper shows how techniques for compartmental model analysis-structural identifiability analysis, linearization, and reparameterization-can be used to ensure robust parameter identification.

Dataset Information

Structural insights into neonatal Fc receptor-based recycling mechanisms.

Publications

Structural insights into neonatal Fc receptor-based recycling mechanisms.

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