Modeling and mitigation of high-concentration antibody viscosity through structure-based computer-aided protein design

PLoS One. 2020 May 7;15(5):e0232713. doi: 10.1371/journal.pone.0232713. eCollection 2020.

Abstract

For an antibody to be a successful therapeutic many competing factors require optimization, including binding affinity, biophysical characteristics, and immunogenicity risk. Additional constraints may arise from the need to formulate antibodies at high concentrations (>150 mg/ml) to enable subcutaneous dosing with reasonable volume (ideally <1.0 mL). Unfortunately, antibodies at high concentrations may exhibit high viscosities that place impractical constraints (such as multiple injections or large needle diameters) on delivery and impede efficient manufacturing. Here we describe the optimization of an anti-PDGF-BB antibody to reduce viscosity, enabling an increase in the formulated concentration from 80 mg/ml to greater than 160 mg/ml, while maintaining the binding affinity. We performed two rounds of structure guided rational design to optimize the surface electrostatic properties. Analysis of this set demonstrated that a net-positive charge change, and disruption of negative charge patches were associated with decreased viscosity, but the effect was greatly dependent on the local surface environment. Our work here provides a comprehensive study exploring a wide sampling of charge-changes in the Fv and CDR regions along with targeting multiple negative charge patches. In total, we generated viscosity measurements for 40 unique antibody variants with full sequence information which provides a significantly larger and more complete dataset than has previously been reported.

MeSH terms

  • Antibodies, Monoclonal / chemistry*
  • Antibodies, Monoclonal / genetics
  • Antibodies, Monoclonal / immunology
  • Becaplermin / immunology
  • Computer-Aided Design
  • Humans
  • Immunoglobulin G / chemistry*
  • Immunoglobulin G / genetics
  • Immunoglobulin G / immunology
  • Models, Molecular
  • Mutation
  • Protein Conformation
  • Surface Properties
  • Viscosity

Substances

  • Antibodies, Monoclonal
  • Immunoglobulin G
  • Becaplermin

Grants and funding

Pfizer provided support for this research in the form of research materials and salaries for authors JA, AT, RS, SM, AK, HY, KK, DM, AD, GY, XZ, LR, WM, DF, GC, EB and LL. However, Pfizer did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.