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Updated: Aug 26, 2025
Sedimentation Equilibrium of a Small Oligomer-forming Membrane Protein: Effect of Histidine Protonation on Pentameric Stability
Published on: April 2, 2015
Predicting Experimental B22 Values and the Effects of Histidine Charge States for Monoclonal Antibodies Using
Hassan Shahfar1, Christopher J O'Brien1, Ivan L Budyak2
1Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware19716, United States.
Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B22) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B22 values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B22 calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B22 values at pH conditions near the pKa of titratable residues.
Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B22) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B22 values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B22 calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B22 values at pH conditions near the pKa of titratable residues.
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