Structure and Relaxation in Solutions of Monoclonal Antibodies

Abstract

Reversible self-association of therapeutic antibodies is a key factor in high protein solution viscosities. In the present work, a coarse-grained computational model accounting for electrostatic, dispersion, and long-ranged hydrodynamic interactions of two model monoclonal antibodies is applied to understand the nature of self-association, predicting the solution microstructure and resulting transport properties of the solution. For the proteins investigated, the structure factor across a range of solution conditions shows quantitative agreement with neutron-scattering experiments. We observe a homogeneous, dynamical association of the antibodies with no evidence of phase separation. Calculations of self-diffusivity and viscosity from coarse-grained dynamic simulations show the appropriate trends with concentration but, respectively, over- and under-predict the experimentally measured values. By adding constraints to the self-associated clusters that rigidify them under flow, prediction of the transport properties is significantly improved with respect to experimental measurements. We hypothesize that these rigidity constraints are associated with missing degrees of freedom in the coarse-grained model resulting from patchy and heterogeneous interactions among coarse-grained domains. These results demonstrate how structural anisotropy and anisotropy of interactions generated by features at the 2-5 nm length scale in antibodies are sufficient to recover the dynamics and rheological properties of these important macromolecular solutions.

Surface heterogeneity affects percolation and gelation of colloids: dynamic simulations with random patchy spheres

“…They greatly affect the dynamics of colloidal dispersions, and including them in computational models is crucial to accurately explain kinetic phenomena such as gelation, 13,14 and quantify transport properties such as diffusivity and viscosity. 36,45 The hydrodynamic force F H and torque T H in the over-damped regime are linear in the particles' translational velocity U and angular velocity X: 46…”

“…3 shows a schematic plot of this system of linear equations as we apply them to random patchy particles. Our previous works 36,45 efficiently evaluated the dynamics of such assemblies by describing bead-bead hydrodynamic interactions with the Rotne-Prager-Yamakawa (RPY) mobility tensor 47 M RPY ab , which is a far-field approximation for velocityforce couplings between spherical beads:…”

“…15,24,33 Protein surface functionalities significantly impact the solution micro-structure and viscosity, 23,34 which is a phenomenology that is not explained by isotropic liquid theories 22,35 based on spherically averaged attractions and lumped charges. Our recent work 36 has shown that constraint on relative motion between nearly touching proteins explains the high viscosity observed in concentrated solutions of monoclonal antibodies.…”

Enhanced diffusion and magnetophoresis of paramagnetic colloidal particles in rotating magnetic fields

“…If an aggregate is treated as a rigid collection of particles constrained to move together, which may be appropriate given the strong interparticle forces, the rigidity constraints significantly increase the drag, so the drag reduction may not be quite so dramatic. 81,82 Such a refined hydrodynamic model was not implemented here. If the particles form platelets and sheets (d E 2) or crystals (d E 3), the mobility decreases even faster as the aggregates break up, with the rate increasing the larger the fractal dimension.…”

“…A modification to our hydrodynamic model is needed to ensure the particles composing the cage remain rigidly constrained, which is discussed in detail elsewhere. 81,82,86 Like our previous bulk calculations, we computed the long-time self diffusivity from the mean-squared displacement (15) and the low-gradient magnetophoretic mobility from eqn (16), both shown in Fig. 9.…”