Electrostatically Mediated Protein-Protein Interactions for Monoclonal Antibodies: A Combined Experimental and Coarse-Grained Molecular Modeling Approach

Electrostatically mediated protein-protein interactions (PPI) can influence key product properties such as solubility, solution viscosity, and aggregation rates. Predictive models would allow for candidates/formulations to be screened with little or no protein material. Three monoclonal antibodies that display qualitatively different experimental PPI were evaluated at a range of pH and ionic strength conditions that are typical of product formulations. PPI parameters (k(D), B-22, and G(22)) were obtained from static and dynamic light scattering measurements and spanned from strongly repulsive to strongly attractive net interactions. Coarse-grained (CG) molecular simulations of PPI (specifically, B-22) were compared against experimental PPI parameters across multiple pH and salt conditions, using a CG model that treats each amino acid explicitly. Predicted B-22 values with default model parameters matched experimental B-22 values semiquantitatively for some cases; others required parameter tuning to account for effects such as ion binding. Experimental PPI values were also analyzed for each monoclonal antibody within the context of single-protein properties such as net charge, and domain-based and global dipole moments. The results show that PPI predicted qualitatively and semiquantitatively by CG molecular modeling of B-22 can be an effective computational tool for molecule and formulation assessment. (C) 2019 American Pharmacists Association (R). Published by Elsevier Inc. All rights reserved.