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. 2015 May 12;112(19):5997-6002.
doi: 10.1073/pnas.1408766112. Epub 2015 Apr 27.

Charge-mediated influence of the antibody variable domain on FcRn-dependent pharmacokinetics

Angela Schoch  1 , Hubert Kettenberger  2 , Olaf Mundigl  3 , Gerhard Winter  4 , Julia Engert  4 , Julia Heinrich  1 , Thomas Emrich  5
Affiliations

Charge-mediated influence of the antibody variable domain on FcRn-dependent pharmacokinetics

Angela Schoch et al. Proc Natl Acad Sci U S A. .

Abstract

Here, we investigated the influence of the variable fragment (Fv) of IgG antibodies on the binding to the neonatal Fc receptor (FcRn) as well as on FcRn-dependent pharmacokinetics (PK). FcRn plays a key role in IgG homeostasis, and specific manipulation in the crystallizable fragment (Fc) is known to affect FcRn-dependent PK. Although the influence of the antigen-binding fragment (Fab) on FcRn interactions has been reported, the underlying mechanism is hitherto only poorly understood. Therefore, we analyzed the two IgG1 antibodies, briakinumab and ustekinumab, that have similar Fc parts but different terminal half-lives in human and systematically engineered variants of them with cross-over exchanges and varied charge distribution. Using FcRn affinity chromatography, molecular dynamics simulation, and in vivo PK studies in human FcRn transgenic mice, we provide evidence that the charge distribution on the Fv domain is involved in excessive FcRn binding. This excessive binding prevents efficient FcRn-IgG dissociation at physiological pH, thereby reducing FcRn-dependent terminal half-lives. Furthermore, we observed a linear correlation between FcRn column retention times of the antibody variants and the terminal half-lives in vivo. Taken together, our study contributes to a better understanding of the FcRn-IgG interaction, and it could also provide profound potential in FcRn-dependent antibody engineering of the variable Fab region.

Keywords: FcRn; antibody; charge; engineering; pharmacokinetics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Charge distribution and pH-dependent net charge. Isopotential surfaces of the proteins protonated at pH 7.4 and contoured at 2 kBT/e. Blue, positive; red, negative. (A) Briakinumab. The light chain is shown in yellow, and the heavy chain is shown in orange. Views of the Middle and Right images are related to the view in the Left panel by a rotation about a vertical and a horizontal axis, respectively. (B) Ustekinumab. Light and heavy chains are colored in light and dark green, respectively. The views are identical to A. (C) Homology model of briakinumab in complex with two human FcRn/β2 microglobulin (β2m) heterodimers, shown as molecular surface. The surface is colored according to its electrostatic potential (±1 kBT/e) calculated as above. A green circle marks the positive charge patch on FcRn deemed to interact with a negative patch on the Fab. Protein structures were prepared with DiscoveryStudio Pro. (D) Sequence-based calculated net charge vs. pH of briakinumab and ustekinumab.
Fig. 2.
Fig. 2.
pH-dependent FcRn–IgG interaction. FcRn affinity chromatograms of the 11 IgG variants were intensity-normalized for clarity. A molecular surface representation of the structural models, protonated at pH 7.4, was superimposed with isopotential surfaces contoured at 2 kBT/e. The view is identical to the Right panel in Fig. 1A and focuses on the CDR regions. A second horizontal axis indicates the elution pH, interpolated from offline pH measurements.
Fig. 3.
Fig. 3.
Correlation between in vivo PK parameters and FcRn column elution pHs. Antibodies were administered as a single i.v. bolus injection of 10 mg/kg to six animals per group. Data points represent the mean ± SD. (A) Blood level curves of briakinumab (orange), ustekinumab (green), mAb 8 (purple), and mAb 9 (blue). (B) Correlation between the terminal half-lives with the FcRn column elution pH.
Fig. 4.
Fig. 4.
Differential sorting of briakinumab and ustekinumab in FcRn-positive sorting endosomes. HUVECs were incubated together with 200 µg/mL both briakinumab (labeled with AlexaFluor594) and ustekinumab (labeled with AlexaFluor488) for 20 min at 37 °C, pH 7.3, followed by 20 min chase. At the end of the experiment, cells were fixed and counterstained with a monoclonal antibody directed against FcRn (DVN22) (44) detected by secondary antibodies labeled with AlexaFluor647.
Fig. 5.
Fig. 5.
Molecular dynamics simulation of FcRn–IgG models. (A) Conformation at the start of the simulation. The dashed line indicates the distance between two example amino acids in the Fv region and in the FcRn, which approach each other during the MD simulation as shown in D. The color code is identical to Fig. 1. (B) Conformation at the end of the simulation (t = 100 ns). The box indicates the part of the molecule shown in C. (C) Detailed view of the interaction between FcRn and the Fv domain of briakinumab. CDRs of the HC and the LC are colored in dark and light purple, respectively. (D) Distance between residues 192 (FcRn) and 57 (ustekinumab LC) and 58 (briakinumab LC), respectively, during the course of the simulation. Protein structures were prepared with PyMol (Schrodinger LLC).
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