Prediction of the Hydrogen Peroxide-Induced Methionine Oxidation Propensity in Monoclonal Antibodies

J Pharm Sci. 2018 May;107(5):1282-1289. doi: 10.1016/j.xphs.2018.01.002. Epub 2018 Jan 8.

Abstract

Methionine oxidation in therapeutic antibodies can impact the product's stability, clinical efficacy, and safety and hence it is desirable to address the methionine oxidation liability during antibody discovery and development phase. Although the current experimental approaches can identify the oxidation-labile methionine residues, their application is limited mostly to the development phase. We demonstrate an in silico method that can be used to predict oxidation-labile residues based solely on the antibody sequence and structure information. Since antibody sequence information is available in the discovery phase, the in silico method can be applied very early on to identify the oxidation-labile methionine residues and subsequently address the oxidation liability. We believe that the in silico method for methionine oxidation liability assessment can aid in antibody discovery and development phase to address the liability in a more rational way.

Keywords: biotechnology; in silico modeling; molecular modeling; monoclonal antibody; oxidation.

MeSH terms

  • Amino Acid Sequence
  • Antibodies, Monoclonal / chemistry*
  • Computer Simulation
  • Humans
  • Hydrogen Peroxide / chemistry*
  • Immunoglobulin Fc Fragments / chemistry
  • Immunoglobulin Variable Region / chemistry
  • Methionine / chemistry*
  • Models, Biological
  • Molecular Dynamics Simulation
  • Oxidation-Reduction
  • Protein Domains
  • Recombinant Proteins / chemistry

Substances

  • Antibodies, Monoclonal
  • Immunoglobulin Fc Fragments
  • Immunoglobulin Variable Region
  • Recombinant Proteins
  • Methionine
  • Hydrogen Peroxide