Related Experiment Video
Updated: Aug 12, 2025
10:50
Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System
Published on: May 1, 2019
14.7K
Characterizing Experimental Monoclonal Antibody Interactions and Clustering Using a Coarse-Grained Simulation Library
Amjad Chowdhury1, Neha Manohar1, Geetika Guruprasad1
1McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States.
The Journal of Physical Chemistry. B
|January 30, 2023
Summary
Protein-protein attractions in monoclonal antibody (mAb) solutions cause clustering and increase viscosity. A new model links viscosity to clustering, considering packing and fractal dimension, aiding characterization of mAb behavior.
Area of Science:
- Biophysics
- Materials Science
- Chemical Engineering
Background:
- Concentrated monoclonal antibody (mAb) solutions can exhibit increased viscosity due to protein-protein attractions forming clusters.
- Understanding these interactions is crucial for formulation development and predicting the physical behavior of therapeutic proteins.
Purpose of the Study:
- To develop an analytical model connecting mAb solution viscosity to protein clustering.
- To investigate the impact of short-range attractions and long-range repulsions on cluster properties.
- To provide a framework for characterizing mAb interactions and clustering under various conditions.
Main Methods:
- Development of an analytical model incorporating cluster packing and fractal dimension.
- Coarse-grained molecular dynamics simulations to analyze cluster characteristics (size distribution, fractal dimension, radial distribution, structure factors).
- Experimental validation using small-angle X-ray scattering (SAXS) and viscosity measurements.
Main Results:
- The model successfully relates mAb viscosity to clustering phenomena.
- Simulation library explored effects of charge and ionic strength on cluster properties.
- Experimental data fitted to the model framework, characterizing attraction, repulsion, and clustering across different pH and cosolute conditions.
Conclusions:
- The proposed model and simulation framework effectively characterize protein-protein interactions and clustering in mAb solutions.
- At low ionic strength, strong charges significantly influence cluster size, necessitating consideration of both viscosity and net charge (or structure factor and net charge) to differentiate attraction and repulsion effects.
