Towards predictable transmembrane transport: QSAR analysis of anion binding and transport

abstract

The transport of anions across biological membranes by small molecules is a growing research field due to the potential therapeutic benefits of these compounds. However, little is known about the exact mechanism by which these drug-like molecules work and which molecular features make a good transporter. An extended series of 1-hexyl-3-phenylthioureas were synthesized, fully characterized (NMR, mass spectrometry, IR and single crystal diffraction) and their anion binding and anion transport properties were assessed using H-1 NMR titration techniques and a variety of vesicle-based experiments. Quantitative structure-activity relationship (QSAR) analysis revealed that the anion binding abilities of the mono-thioureas are dominated by the (hydrogen bond) acidity of the thiourea NH function. Furthermore, mathematical models show that the experimental transmembrane anion transport ability is mainly dependent on the lipophilicity of the transporter (partitioning into the membrane), but smaller contributions of molecular size (diffusion) and hydrogen bond acidity (anion binding) were also present. Finally, we provide the first step towards predictable anion transport by employing the QSAR equations to estimate the transmembrane transport ability of four new compounds.

keywords

CHLORIDE TRANSPORT; MEMBRANE TRANSPORTERS; CELL-MEMBRANES; FLIP-FLOP; RECEPTORS; VESICLE; RECOGNITION; PRODIGIOSINS; COEFFICIENTS; PARAMETERS

subject category

Chemistry

authors

Busschaert, N; Bradberry, SJ; Wenzel, M; Haynes, CJE; Hiscock, JR; Kirby, IL; Karagiannidis, LE; Moore, SJ; Wells, NJ; Herniman, J; Langley, GJ; Horton, PN; Light, ME; Marques, I; Costa, PJ; Felix, V; Frey, JG; Gale, PA

our authors

acknowledgements

We thank the EPSRC for funding (MW, CJEH, LEK, SJM) and for access to the crystallographic facilities at the University of Southampton and Diamond Beamline I19. We thank the University of Southampton and A*STAR for a postgraduate scholarship (NB). IM thanks the FCT (Fundacao para a Ciencia e a Tecnologia) for the PhD scholarship SFRH/BD/87520/2012. PJC thanks FCT for the postdoctoral grant SFRH/BPD/27082/2006. VF acknowledges the funding from QREN-FEDER, through the Operational Program Competitiveness Factors - COMPETE and National Funds through the FCT under project PTDC/QUI-QUI/101022/2008. The authors would also like to thank Jonathan W. Essex (University of Southampton) and Russell Viner (Syngenta) for their help with calculating suitable log P values.

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