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Dynameric Frameworks with Aggregation-Induced Emission for Selective Detection of Adenosine Triphosphate
Yan Zhang1,2, Yuhao Li3, Chengyong Su3
1Institut Européen des Membranes, Adaptive Supramolecular Nanosystems Group, University of Montpellier, ENSCM, CNRS, Place Eugène Bataillon, CC 047, 34095, Montpellier, France.
Chempluschem
|January 18, 2020
Summary
Researchers observed a "dynameric effect" enhancing aggregation-induced emission (AIE) sensors for adenosine triphosphate (ATP). Dynameric networks showed superior ATP detection compared to molecular sensors, paving the way for adaptive biomimetic sensors.
Area of Science:
- Materials Science
- Supramolecular Chemistry
- Biomimetic Sensors
Background:
- Aggregation-induced emission (AIE) materials exhibit increased photoluminescence upon aggregation due to restricted intramolecular rotation.
- AIE sensors are valuable for detecting analytes, but enhancing their sensitivity and selectivity remains a challenge.
Purpose of the Study:
- To investigate the
- dynameric effect
- on AIE in molecular and dynameric sensors for adenosine triphosphate (ATP).
- To compare the performance of dynameric networks and molecular sensors in ATP detection.
Main Methods:
- Synthesis and characterization of molecular and dynameric AIE sensors.
- Fluorescence spectroscopy to evaluate AIE properties and ATP binding.
- Comparative analysis of sensor performance based on structural dynamics.
Main Results:
- The first experimental observation of a dynameric effect enhancing AIE was reported.
- Dynameric AIE sensors demonstrated enhanced, non-linear turn-on fluorescence switching upon ATP interaction.
- Multivalent dynameric networks showed superior ATP detection sensitivity compared to molecular sensors.
- Selective detection of ATP over other nucleotides (ADP, AMP, GTP, CTP) was achieved.
- The dynamic and reversible nature of imine linkages was crucial for enhanced AIE activity.
Conclusions:
- The dynameric effect significantly enhances AIE sensor performance for ATP detection.
- Dynameric frameworks offer a promising platform for developing highly sensitive and selective adaptive biomimetic sensors.
- This work provides a foundation for the rational design of advanced AIE-based sensing systems.
