Multiscale Coarse-Grained Approach to Investigate Self-Association of Antibodies

S Izadi and TW Patapoff and BT Walters, BIOPHYSICAL JOURNAL, 118, 2741-2754 (2020).

DOI: 10.1016/j.bpj.2020.04.022

Self-association of therapeutic monoclonal antibodies (mabs) are thought to modulate the undesirably high viscosity observed in their concentrated solutions. Computational prediction of such a self- association behavior is advantageous early during mab drug candidate selection when material availability is limited. Here, we present a coarse-grained (CG) simulation method that enables microsecond molecular dynamics simulations of full-length antibodies at high concentrations. The proposed approach differs from others in two ways: first, charges are assigned to CG beads in an effort to reproduce molecular multipole moments and charge asymmetry of full-length antibodies instead of only localized charges. This leads to great improvements in the agreement between CG and all-atom electrostatic fields. Second, the distinctive hydrophobic character of each antibody is incorporated through empirical adjustments to the short-range van der Waals terms dictated by cosolvent all-atom molecular dynamics simulations of antibody variable regions. CG simulations performed on a set of 15 different mabs reveal that diffusion coefficients in crowded environments are markedly impacted by intermolecular interactions. Diffusion coefficients computed from the simulations are in correlation with experimentally measured observables, including viscosities at a high concentration. Further, we show that the evaluation of electrostatic and hydrophobic characters of the mabs is useful in predicting the nonuniform effect of salt on the viscosity of mab solutions. This CG modeling approach is particularly applicable as a material-free screening tool for selecting antibody candidates with desirable viscosity properties. SIGNIFICANCE Early assessment of antibody drug developability characteristics can substantially reduce risks and costs associated with their product development and provides an opportunity for molecular redesign. One key aspect in the developability assessment is the prediction of the viscosity behavior. Subcutaneous delivery of antibodies requires highconcentration solutions to achieve a desired dose. At these high concentrations, antibody self- association can cause undesirably high viscosity, leading to significant challenges in manufacturing and administration. Presented here is a physics-based, coarse-grained scheme that enables early identification of the high viscosity of antibodies based solely on antibody structural attributes and dynamical properties from the simulations. The computational approaches like the one proposed greatly improve the successful progression of antibody drug candidates through clinical development, ultimately benefiting patients.

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