Interfacial recognition of human prostate-specific antigen by immobilized monoclonal antibody: Effects of solution conditions and surface chemistry

  • Zhao X
  • Pan F
  • Garcia-Gancedo L
 et al. 
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Abstract

The specific recognition between monoclonal antibody (anti-human prostate-specific antigen, anti-hPSA) and its antigen (human prostate-specific antigen, hPSA) has promising applications in prostate cancer diagnostics and other biosensor applications. However, because of steric constraints associated with interfacial packing and molecular orientations, the binding efficiency is often very low. In this study, spectroscopic ellipsometry and neutron reflection have been used to investigate how solution pH, salt concentration and surface chemistry affect antibody adsorption and subsequent antigen binding. The adsorbed amount of antibody was found to vary with pH and the maximum adsorption occurred between pH 5 and 6, close to the isoelectric point of the antibody. By contrast, the highest antigen binding efficiency occurred close to the neutral pH. Increasing the ionic strength reduced antibody adsorbed amount at the silica-water interface but had little effect on antigen binding. Further studies of antibody adsorption on hydrophobic C8 (octyltrimethoxysilane) surface and chemical attachment of antibody on (3-mercaptopropyl)trimethoxysilane/4-maleimidobutyric acid N-hydroxysuccinimide ester-modified surface have also been undertaken. It was found that on all surfaces studied, the antibody predominantly adopted the 'flat on' orientation, and antigen-binding capabilities were comparable. The results indicate that antibody immobilization via appropriate physical adsorption can replace elaborate interfacial molecular engineering involving complex covalent attachments.

Author-supplied keywords

  • Antibody binding
  • Antibody conformation
  • Antigen recognition
  • Biointerface
  • Interfacial binding
  • Neutron reflection

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Authors

  • Xiubo Zhao

  • Fang Pan

  • Luis Garcia-Gancedo

  • Andrew J. Flewitt

  • Gregory M. Ashley

  • Jikui Luo

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