Design, synthesis and application of carbazole macrocycles in anion sensors

Beilstein J Org Chem. 2020 Aug 4:16:1901-1914. doi: 10.3762/bjoc.16.157. eCollection 2020.

Abstract

Carboxylate sensing solid-contact ion-selective electrodes (ISEs) were created to provide a proof-of-concept ISE development process covering all aspects from in silico ionophore design to functional sensor characterization. The biscarbazolylurea moiety was used to synthesize methylene-bridged macrocycles of different ring size aiming to fine tune selectivity towards different carboxylates. Cyclization was achieved with two separate strategies, using either amide synthesis to access up to -[CH2]10- macrocycles or acyl halides to access up to -[CH2]14- macrocycles. Seventy-five receptor-anion complexes were modelled and studied with COSMO-RS, in addition to all free host molecules. In order to predict initial selectivity towards carboxylates, 1H NMR relative titrations were used to quantify binding in DMSO-d 6/H2O solvent systems of two proportions - 99.5%:0.5% m/m and 90.0%:10.0% m/m, suggesting initial selectivity towards acetate. Three ionophores were selected for successful sensor prototype development and characterization. The constructed ion-selective electrodes showed higher selectivity towards benzoate than acetate, i.e., the selectivity patterns of the final sensors deviated from that predicted by the classic titration experiments. While the binding constants obtained by NMR titration in DMSO-d 6/H2O solvent systems provided important guidance for sensor development, the results obtained in this work emphasize the importance of evaluating the binding behavior of receptors in real sensor membranes.

Keywords: anion sensors; carboxylates; ionophores; macrocycles; sensor prototype.

Grants and funding

This work was supported by the Estonian Research Council grant PRG690, by the EU through the European Regional Development Fund (TK141 “Advanced materials and high-technology devices for energy recuperation systems”) and by the EMPIR programme (project 17FUN09, UnipHied) co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme. JB gratefully acknowledges funding from the Academy of Finland (project no. 317829). VY gratefully acknowledges funding from the Magnus Ehrnrooth Foundation.