Computational Model-Assisted Development of a Nonenzymatic Fluorescent Glucose-Sensing Assay

ACS Sens. 2024 Nov 22;9(11):6218-6227. doi: 10.1021/acssensors.4c02117. Epub 2024 Nov 13.

Abstract

Deep-red fluorescence was implemented in this fully injectable, nonenzymatic glucose biosensor design to allow for better light penetration through the skin, particularly for darker skin tones. In this work, a novel method was developed to synthesize Cy5.5 labeled mannose conjugates (Cy5.5-mannobiose, Cy5.5-mannotriose, and Cy5.5-mannotetraose) to act as the fluorescent competing ligand in a competitive binding assay with the protein Concanavalin A acting as the recognition molecule. Using fluorescence anisotropy (FA) data, a computational model was developed to determine optimal concentration ratios of the assay components to allow for sensitive glucose measurements within the physiological range. The model was experimentally validated by measuring the glucose response via FA of the three Cy5.5-labeled mannose conjugates synthesized with Cy5.5-mannotetraose demonstrating the most sensitive response to glucose across the physiological range. The developed method may be broadly applied to a vast range of commercially available fluorescent dyes and opens up opportunities for glucose measurements using nonenzymatic assays.

Keywords: biosensor; competitive binding; concanavalin A; fluorescence anisotropy; glucose sensing; mannose.

MeSH terms

  • Biosensing Techniques* / methods
  • Carbocyanines / chemistry
  • Computer Simulation
  • Concanavalin A* / chemistry
  • Fluorescence Polarization / methods
  • Fluorescent Dyes* / chemistry
  • Glucose* / analysis
  • Glucose* / chemistry
  • Mannose / chemistry

Substances

  • Fluorescent Dyes
  • Glucose
  • Concanavalin A
  • Mannose
  • Carbocyanines