Fabricating a super stable luminescent chemosensor with multi-stimuli-response to metal ions and small organic molecules through turn-on and turn-off effects

2017 ◽  
Vol 5 (18) ◽  
pp. 4511-4519 ◽  
Author(s):  
Yan Yang ◽  
Lian Chen ◽  
Feilong Jiang ◽  
Xiuyan Wan ◽  
Muxin Yu ◽  
...  

A multi-stimuli-responsive luminescent Ln-MOF (1), with a combination of exceptionally high thermal, air and chemical stabilities, as a turn-on/turn-off chemosensor for metal ions and small organic molecules is reported.

2016 ◽  
Vol 55 (5) ◽  
pp. 2261-2273 ◽  
Author(s):  
Si-Si Zhao ◽  
Jin Yang ◽  
Ying-Ying Liu ◽  
Jian-Fang Ma

2020 ◽  
Vol 16 (6) ◽  
pp. 738-743 ◽  
Author(s):  
Poonam Rani ◽  
Kashmiri Lal ◽  
Vikas D. Ghule ◽  
Rahul Shrivastava

Background: The synthesis of small organic molecules based Hg2+ ions receptors have gained considerable attention because it is one of the most prevalent toxic metals which is continuously discharged into the environment by different natural and industrial activities. 1,4-Disubstituted 1,2,3-triazoles have been reported as good chemosensors for the detection of various metal ions including Hg2+ ions. Methods: The synthesis of 1,2,3-triazoles (4a-4c) was achieved by Cu(I)-catalyzed azide-alkyne cycloaddition, and their binding affinity towards various metal ions and anions were studied by UVVisible titration experiments. The perchlorate salts of metal ions and tetrabutylammonium salts of anions were utilized for the UV-Visible experiments. DFT studies were performed to understand the binding and mechanism on the sensing of 4a toward Hg2+ using the B3LYP/6-311G(d,p) method for 4a and B3LYP/LANL2DZ for 4a-Hg2+ species on the Gaussian 09W program. Results: The UV-visible experiments indicated that the compounds 4a-4c show a selective response towards Hg2+ ion in UV-Visible spectra, while other ions did not display such changes in the absorption spectra. The binding stoichiometry was evaluated by Job’s plot which indicated the 1:1 binding stoichiometry between receptors (4a-4c) and Hg2+ ion. The detection limit of 4a, 4b and 4c for the Hg2+ ions was found to be 29.1 nM, 3.5 μM and 1.34 μM, respectively. Conclusion: Some 1,2,3-triazole derivatives were synthesized (4a-4c) exhibiting high selectively and sensitivity towards Hg2+ ions in preference to other ions. Compound 4a has a low detection limit of 29.1 nM and the binding constant of 2.3×106 M-1. Similarly, 4b and 4c also showed selective sensing towards Hg2+ ions in the μM range. The observed experimental results were corroborated by density functional theory (DFT) calculations.


2021 ◽  
Author(s):  
Yue Zhang ◽  
Daowen Zhang ◽  
Jin-Tao Wang ◽  
Xiaojie Zhang ◽  
Yongfang Yang

Stimuli-responsive nanogels were fabricated by reaction of proteins and polymers without using small-organic-molecules. Once the nanogels dissociated, the proteins were released with functional groups, secondary structures, and activities maintained.


Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>


Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>


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