P07-24

Correlation Analysis of Excipient Modulated Viscosity of Monoclonal Antibody and Molecular Surface Patch Properties

Yoshirou KIMURA *

Life Science Dept., MOLSIS Inc.
( * E-mail: kimura.yoshirou@molsis.co.jp )

When an antibody drug is administered by injection, a high-concentration solution of 100 mg/mL or more is required because of the limited amount administered at one time. However, the formulations with such high concentrations can result in a high viscosity. Subcutaneous injection typically requires viscosities below 15–20 cP. Various excipient molecules, such as saccharides and amino acids, are used to adjust the viscosity. This experimental process is expensive and time-consuming, so in silico techniques are expected to improve efficiency.
The molecular surface patch analysis functionality implemented in MOE[1], which is the molecular modeling and simulation software, has been reported to be useful for protein-protein interaction analysis[2] and estimating physical properties such as protein retention times in hydrophobic interaction chromatography[3][4]. The patch analysis has also been used in studies of antibody viscosity [5], but to our knowledge no studies considering excipients have been done to date. Therefore, we decided to perform molecular surface patch analysis on a system including an antibody and its interacted excipient molecules and investigate the correlation between various physical properties obtained by this and viscosity. If they are correlated, it will be possible to predict viscosity, screen excipients, and analyze the factors behind the increase in viscosity.
We investigated the correlation between the experimental viscosity of an antibody with some excipients and various physical properties obtained by molecular surface patch analysis and found that the surface area of the positive and negative charge patches was highly correlated with the viscosity. In this presentation, we will introduce the details of the calculation method and the comparison with the experiment.

[1] Molecular Operating Environment (MOE), 2022.02; Chemical Computing Group ULC, 1010 Sherbrooke St. West, Suite #910, Montreal, QC, Canada, H3A 2R7, 2022.
[2] Depetris, R. S.; et al. Proteins: Struct., Funct., Bioinf. 2022, 90 (4), 919–935.
[3] Thorsteinson, N.; et al., mAbs, 2021, 13 (1), 1981805.
[4] Jetha, A.; et al., mAbs, 2018, 10 (6), 890-900.
[5] Armstrong, G. B.; et al., Comput. Struct. Biotechnol. J., 2024, 23, 2345-2357.