Calix[4]arene sulfonate hosts selectively modified on the upper rim: a study of nicotine binding strength and geometry

Warmerdam, Zoey; Kamba, Bianca; Shaurya, Alok; Sun, XuXin; Maguire, Mary K.; Hof, Fraser

doi:10.1080/10610278.2021.1873991

“…The existence of some disassembled DD1 at pH 2.2 leads to detectable fluorescence in the absence of nicotine, which signifies the presence of a mixture of species. At pH 12.1, nicotine is uncharged; the minimal response of DD1 absorbance and emission upon addition of nicotine (Figure S2) confirms that a cationic guest is required for significant binding to occur . This is verified by treatment of DD1 with the quaternary ammonium ion choline at pH 12.1, for which a fluorescence response occurs (inset Figure b).…”

mentioning

confidence: 71%

“…The current study focuses on the competing binding equilibria for the complexes of DimerDye1 (DD1) with the guest nicotine. Nicotine is a biologically relevant model analyte , that has multiple ionizable groups (p K a = 3.1 (pyridine) and 8.0 (pyrrolidine)), allowing us to probe the effect of charge on multiple binding equilibria. We first characterize the general assembly and photophysical properties of the system using absorbance and steady-state fluorescence.…”

mentioning

confidence: 99%

Mechanism of a Disassembly-Driven Sensing System Studied by Stopped-Flow Kinetics

Gallo

¹

,

Thomas

²

,

Selinger

³

et al. 2021

J. Org. Chem.

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We carried out steady-state and stopped-flow photophysical measurements to determine the kinetics of a discrete disassembly driven turn-on fluorescent system. On and off rates for both DimerDye1 assembly and nicotine binding were determined. Relative rates for these competing processes provide insight on how this system can be optimized for sensing applications. Kinetics studies in artificial saliva showed that moving to more complex media has minimal effects on the sensing ability of the system.

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“…The authors have cited additional references within the Supporting Information. [22][23][24][25][26][27][28][29][30][31][32][33]…”

Section: Supporting Informationmentioning

confidence: 99%

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

Selinger,

Hof

2023

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Molecular differentiation by supramolecular sensors is typically achieved through sensor arrays, relying on the pattern recognition responses of large panels of isolated sensing elements. Here we report a new one‐pot systems chemistry approach to differential sensing in biological solutions. We constructed an adaptive network of three cross‐assembling sensor elements with diverse analyte‐binding and photophysical properties. This robust sensing approach exploits complex interconnected sensor‐sensor and sensor‐analyte equilibria, producing emergent supramolecular and photophysical responses unique to each analyte. We characterize the basic mechanisms by which an adaptive network responds to analytes. The inherently data‐rich responses of an adaptive network discriminate among very closely related proteins and protein mixtures without relying on designed protein recognition elements. We show that a single adaptive sensing solution provides better analyte discrimination using fewer response observations than a sensor array built from the same components. We also show the network's ability to adapt and respond to changing biological solutions over time.

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Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

Selinger,

Hof

2023

Angewandte Chemie

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Molecular differentiation by supramolecular sensors is typically achieved through sensor arrays, relying on the pattern recognition responses of large panels of isolated sensing elements. Here we report a new one‐pot systems chemistry approach to differential sensing in biological solutions. We constructed an adaptive network of three cross‐assembling sensor elements with diverse analyte‐binding and photophysical properties. This robust sensing approach exploits complex interconnected sensor‐sensor and sensor‐analyte equilibria, producing emergent supramolecular and photophysical responses unique to each analyte. We characterize the basic mechanisms by which an adaptive network responds to analytes. The inherently data‐rich responses of an adaptive network discriminate among very closely related proteins and protein mixtures without relying on designed protein recognition elements. We show that a single adaptive sensing solution provides better analyte discrimination using fewer response observations than a sensor array built from the same components. We also show the network's ability to adapt and respond to changing biological solutions over time.

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Calix[4]arene sulfonate hosts selectively modified on the upper rim: a study of nicotine binding strength and geometry

Cited by 5 publications

References 41 publications

Mechanism of a Disassembly-Driven Sensing System Studied by Stopped-Flow Kinetics

Mechanism of a Disassembly-Driven Sensing System Studied by Stopped-Flow Kinetics

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

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