Monoclonal Antibody Self-Association, Cluster Formation, and Rheology at High Concentrations

详细信息    查看全文

• 作者：Wayne G. Lilyestrom ; Sandeep Yadav ; Steven J. Shire ; Thomas M. Scherer
• 刊名：The Journal of Physical Chemistry B
• 出版年：2013
• 出版时间：May 30, 2013
• 年：2013
• 卷：117
• 期：21
• 页码：6373-6384
• 全文大小：563K
• 年卷期：v.117,no.21(May 30, 2013)
• ISSN：1520-5207

文摘

The rheological properties of macromolecular and colloidal suspensions are dependent on the thermodynamic and kinetic parameters that define viscous flow, and remain an active field of study with broad implications in cellular biophysics, soft-matter theory, and biopharmaceutical technology. Here we use static light scattering, small-angle X-ray scattering, and viscosity measurements as a function of protein concentration to semiquantitatively correlate the oligomeric state of an IgG1 antibody (mAb1) with its rheological behavior at solution pH 6.0 and varying ionic strength (modified by 0.01鈥?.1 M Na₂SO₄). Solution SAXS characterization of 100 mM Na₂SO₄ solutions confirmed that mAb1 forms reversible dimers with extended structures in dilute solutions. Light-scattering measurements over a wide range of concentrations (1鈥?75 mg/mL) provide detailed information on the equilibrium thermodynamic mAb1 interactions and their modulation by modest increases of Na₂SO₄. Through the use of interacting hard sphere models to fit light-scattering data, we establish that protein cluster formations consisting of 2鈥? mAb1 molecules also increase the viscosity of 175 mg/mL IgG solutions from 52 up to 450 cP. The analysis of dilute and semidilute mAb1 solution rheology correlates linearly with the thermodynamic equilibrium cluster size, consistent with the viscosity behavior of elongated oligomeric structures that are not significantly dendrimeric or in a state of globular collapse. Furthermore, SAXS- and rheology-based structural modeling illustrate that only a small set of anisotropic interactions between complementary surfaces are required to nucleate and propagate protein clusters.