Molecular Computations of Preferential Interaction Coefficients of IgG1 Monoclonal Antibodies with Sorbitol, Sucrose, and Trehalose and the Impact of These Excipients on Aggregation and Viscosity

Abstract

Preferential interactions of formulation excipients govern their overall interactions with protein molecules, and molecular dynamics simulations allow for the examination of the interactions at the molecular level. We used molecular dynamics simulations to examine the interactions of sorbitol, sucrose, and trehalose with three different IgG1 antibodies to gain insight into how these excipients impact aggregation and viscosity. We found that sucrose and trehalose reduce aggregation more than sorbitol because of their larger size and their stronger interactions with high-spatial aggregation propensity residues compared to sorbitol. Two of the antibodies had high viscosity in sodium acetate buffer, and for these, we found that sucrose and trehalose tended to have opposite effects on viscosity. The data presented here provide further insight into the mechanisms of interactions of these three carbohydrate excipients with the antibody surface and thus their impact on excipient stabilization of antibody formulations.

Engineering Stability, Viscosity, and Immunogenicity of Antibodies by Computational Design

“…To gain insights into how formulation excipients of protein therapeutics affect aggregation and viscosity, Trout and coworkers conducted MD simulations using 3 different IgG1 and several carbohydrates. 135 They found that sucrose and trehalose reduced antibody aggregation more than sorbitol because of their larger size and stronger interactions with high-SAP regions of the antibodies.…”

Molecular computations of preferential interactions of proline, arginine.HCl, and NaCl with IgG1 antibodies and their impact on aggregation and viscosity

“…The pIs of mAbs A, B, and C are 9.1, 9.0, and 7.2, respectively. 11 Another study indicated that proline is a desirable excipient under stressful conditions, such as low pH, because it reduces aggregation. 39 Thus, proline's impact on conformational and colloidal stability might be dependent on formulation pH and mAb pI.…”

“…10 One type of experimental data that can be used to validate force field parameters involving proteinexcipient-water mixtures is the preferential interaction coefficient (Γ 23 Þ. 11 Timasheff and others have studied the preferential interactions of certain sugars and polyols with small proteins using preferential interaction theory. [12][13][14] It is hypothesized that the exclusion of these osmolytes from the protein surface favors the native, folded state to minimize the exposed surface area.…”

“…The preferential interaction coefficient of antibodyexcipient mixtures can be measured experimentally via vapor pressure osmometry, 15 and is also accessible via simulation. 11 Numerous experimental [16][17][18][19] and simulation 6,7,[20][21][22][23] studies have been performed on the effects of amino acid and ionic excipients on proteins. However, many of the studies that have been performed focus on how excipients interact with only one or two proteins.…”

“…Here, we use simulations and experiments to investigate the mechanisms by which three common amino acid and ionic excipients (proline, Arg.HCl, and NaCl) affect the aggregation and viscosity of three antibodies studied previously. 11,15,28 By examining multiple antibodies, we can assess how the excipients interact with different antibody surfaces to identify molecular mechanisms underlying the behavior.…”