Calculation of therapeutic antibody viscosity with coarse-grained models, hydrodynamic calculations and machine learning-based parameters

Pin Kuang Lai, James W. Swan, Bernhardt L. Trout

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

High viscosity presents a challenge for manufacturing and drug delivery of therapeutic antibodies. The viscosity is determined by protein–protein interactions among many antibodies. Molecular simulation is a promising method to study protein–protein interactions; however, all-atom models do not allow the simulation of multiple molecules, which is necessary to compute viscosity directly. Coarse-grained models, on the other hand can do this. In this work, a 12-bead coarse-grained model based on Swan and coworkers (J. Phys. Chem. B 2018, 122, 2867–2880) was applied to study antibody interactions. Two adjustable parameters related to the short-range interactions on the variable and constant regions were determined by fitting experimental data of 20 IgG1 monoclonal antibodies at 150 mg/mL. The root-mean-square deviation improved from 1 to 0.68, and the correlation coefficient improved from 0.63 to 0.87 compared to that of a previous model that assumed the short-range interactions were the same for all the beads. Our model is also able to calculate the viscosity over a wide range of concentrations without additional parameters. A tabulated viscosity based on our model is provided to facilitate antibody screening in early-stage design.

Original languageEnglish
Article number1907882
JournalmAbs
Volume13
Issue number1
DOIs
StatePublished - 2021

Keywords

  • Antibody viscosity
  • coarse-grained models
  • hydrodynamic calculations
  • molecular dynamics simulations

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