In this PhD project, in-cell 19F NMR spectroscopy approaches were developed and applied to investigate target–ligand interactions directly in living human cells. Two complementary strategies were pursued: a target-based approach and a ligand-based approach. The target-based approach focused on expressing fluorinated proteins in HEK293T cells by controlling the incorporation of fluorinated aromatic amino acids. The study showed that fluorine incorporation occurs stochastically, resulting in a compromise between spectral sensitivity and sample homogeneity. High incorporation levels provide stronger 19F signals but result in heterogeneous protein populations, causing signal splitting in the NMR spectra, whereas low incorporation enhances spectral resolution and sample homogeneity but at the cost of lower sensitivity. These findings provide useful guidance for optimizing fluorinated protein expression in future drug-discovery applications, where target–ligand interactions could be monitored through chemical-shift perturbations. A 19F NMR ligand-based approach was implemented to investigate the intracellular binding of novel fluorinated benzenesulfonamides designed to target cytosolic carbonic anhydrase (CA) isoforms. 19F NMR enabled the direct observation of intracellular ligand–target complexes, revealing isoform-dependent affinities and also identifying off-target binding events for certain compounds. After selecting the most suitable compound as a “spy” ligand, real-time competitive binding experiments were performed in an NMR bioreactor, providing quantitative ratios of dissociation constants (Kd) for various compounds. The Kd values for each isoform were then estimated by comparing the spy ligand with a known reference compound. This approach could be expanded in the future to experiments capable of simultaneously monitoring multiple CA isoforms within the same cellular sample. Overall, this work expanded the applications of in-cell 19F NMR, showing that it is a powerful and physiologically relevant method for characterising drug–target interactions within living cells. The combination of silico predictions and in vitro assays with this strategy could provide a useful tool for the selection of more effective drug candidates at the preclinical stage of drug development.
19F in-cell NMR to investigate protein-ligand interactions in living human cells / azzurra costantino; lucia banci; Enrico Luchinat. - (2025).
19F in-cell NMR to investigate protein-ligand interactions in living human cells.
azzurra costantinoWriting – Original Draft Preparation
;lucia banciSupervision
;Enrico LuchinatSupervision
2025
Abstract
In this PhD project, in-cell 19F NMR spectroscopy approaches were developed and applied to investigate target–ligand interactions directly in living human cells. Two complementary strategies were pursued: a target-based approach and a ligand-based approach. The target-based approach focused on expressing fluorinated proteins in HEK293T cells by controlling the incorporation of fluorinated aromatic amino acids. The study showed that fluorine incorporation occurs stochastically, resulting in a compromise between spectral sensitivity and sample homogeneity. High incorporation levels provide stronger 19F signals but result in heterogeneous protein populations, causing signal splitting in the NMR spectra, whereas low incorporation enhances spectral resolution and sample homogeneity but at the cost of lower sensitivity. These findings provide useful guidance for optimizing fluorinated protein expression in future drug-discovery applications, where target–ligand interactions could be monitored through chemical-shift perturbations. A 19F NMR ligand-based approach was implemented to investigate the intracellular binding of novel fluorinated benzenesulfonamides designed to target cytosolic carbonic anhydrase (CA) isoforms. 19F NMR enabled the direct observation of intracellular ligand–target complexes, revealing isoform-dependent affinities and also identifying off-target binding events for certain compounds. After selecting the most suitable compound as a “spy” ligand, real-time competitive binding experiments were performed in an NMR bioreactor, providing quantitative ratios of dissociation constants (Kd) for various compounds. The Kd values for each isoform were then estimated by comparing the spy ligand with a known reference compound. This approach could be expanded in the future to experiments capable of simultaneously monitoring multiple CA isoforms within the same cellular sample. Overall, this work expanded the applications of in-cell 19F NMR, showing that it is a powerful and physiologically relevant method for characterising drug–target interactions within living cells. The combination of silico predictions and in vitro assays with this strategy could provide a useful tool for the selection of more effective drug candidates at the preclinical stage of drug development.| File | Dimensione | Formato | |
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PhD Thesis - Azzurra Costantino.pdf
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Descrizione: In this PhD project, in-cell 19F NMR spectroscopy approaches were developed and applied to investigate target–ligand interactions directly in living human cells. Two complementary strategies were pursued: a target-based approach and a ligand-based approach. The target-based approach focused on expressing fluorinated proteins in HEK293T cells by controlling the incorporation of fluorinated aromatic amino acids. The study showed that fluorine incorporation occurs stochastically, resulting in a compromise between spectral sensitivity and sample homogeneity. High incorporation levels provide stronger 19F signals but result in heterogeneous protein populations, causing signal splitting in the NMR spectra, whereas low incorporation enhances spectral resolution and sample homogeneity but at the cost of lower sensitivity. These findings provide useful guidance for optimizing fluorinated protein expression in future drug-discovery applications, where target–ligand interactions could be monitored through chemical-shift
Tipologia:
Tesi di dottorato
Licenza:
Open Access
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24.34 MB
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Adobe PDF
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24.34 MB | Adobe PDF |
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