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Porphyrin-GO Nanocomposites Based NIR Fluorescent Sensor Array for Heparin Sensing and Quality Control
Zhiyu Yang1, Liangfei Fan1, Xia Fan2
1Jiangsu Key Laboratory of Pesticide Science, Department of Chemistry, College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu 210095, People's Republic of China.
Analytical Chemistry
|April 9, 2020
Summary
A novel sensor array using porphyrin-graphene (PP-GO) nanocomposites effectively distinguishes heparin from similar glycosaminoglycans (GAGs). This technology ensures heparin safety by detecting trace GAG contaminants, crucial for clinical anticoagulant drug use.
Area of Science:
- Biomaterials Science
- Analytical Chemistry
- Nanotechnology
Background:
- Heparin (Hep) is a vital anticoagulant with high heterogeneity, posing challenges in distinguishing it from glycosaminoglycan (GAG) analogues.
- Ensuring the purity of clinical heparin is critical for patient safety due to potential GAG contaminants.
Purpose of the Study:
- To develop a reliable method for discriminating heparin from its GAG analogues.
- To create a sensor for detecting trace GAG contaminants in heparin preparations.
Main Methods:
- Synthesis of five porphyrin-graphene (PP-GO) nanocomposites with varying porphyrin substitutions.
- Construction of a near-infrared (NIR) sensor array (PP-GO) for GAG discrimination.
- Utilizing pattern-based recognition with Hierarchical Component Analysis (HCA) and Linear Discriminant Analysis (LDA).
Main Results:
- The PP-GO sensor array demonstrated cross-reactivity towards heparin and three other GAGs (Chs, HA, DS).
- Effective discrimination of heparin and its GAG analogues was achieved in both PBS and 10% serum media.
- The sensor array successfully identified trace GAG contaminants in heparin with 100% accuracy.
Conclusions:
- The developed PP-GO sensor array offers a powerful tool for GAG discrimination and heparin quality control.
- This technology enhances the safe clinical application of heparin by ensuring its purity.
- The sensor array shows significant potential for real-world applications in pharmaceutical analysis.
