Enrico Luchinat

Phosphocoumarins and a first-in-class unsubstituted phosphoquinolinone are disclosed as previously unrecognized carbonic anhydrase (CA) inhibitors, displaying multimodal inhibition within a tunable coumarin-like scaffold. Acidic phosphocoumarins display inhibition of physiologically relevant human CAs, particularly tumor-associated isoforms IX and XII (K_Is: 0.08-0.28 μM) through a composite, two-step mechanism: the ligand first anchors the zinc-bound water molecule before displacing it to directly coordinate the catalytic zinc ion, without CA-mediated hydrolysis. Conversely, a methyl-ester phosphocoumarin functions as an isoform-selective prodrug, undergoing CA-mediated cyclic phosphoester hydrolysis to selectively generate a potent hCA IX/XII inhibitor (K_Is: 54-62 nM), whereas the phosphoquinolinone acts as a direct binder (K_Is: 0.18-0.29 μM vs hCA IX/XII). The complementary mechanisms are supported by QM/MM and long-time scale MD simulations, crystallographic studies, ³¹P NMR, HRMS, and MS/MS. Selected derivatives exhibit low-micromolar antiproliferative activity and induce apoptosis in cancer cells, fostering phosphorus-heterocycles as a mechanistically rich platform for isoform-selective CA inhibition and targeted drug design.

NMR spectroscopy is a powerful, noninvasive tool to analyze complex biological samples. In vitro, high-resolution, 1D NMR spectra of biofluids and cell extracts make it possible to classify biological samples based on their metabolic fingerprint. However, such analysis is currently not possible with live cells or tissues, or by spectroscopic imaging in vivo, due to the line broadening arising from the intrinsic inhomogeneity of such samples, causing severe signal overlap. Here, we show that machine learning approaches applied to poorly resolved NMR spectra of live, intact cells recorded at high fields allow for the classification of different physiopathologically relevant cell types cultured in vitro. We demonstrate the successful classification of neural progenitor cells, neurons, and astrocytes, as well as the classification of mixed cell type samples, and show that a classifier trained on high-field NMR spectra can discriminate cells analyzed at lower fields, approaching those of current MRI instruments. In the future, this approach could be further developed for MRSI data analysis applications, potentially offering a noninvasive diagnostic tool for lesions of the central nervous system and reducing the need for biopsies.

Drug development is a risky endeavour with a high failure rate, often caused by the limited ability to predict the efficacy and interactions of candidate drugs in a native cellular environment. In this context, in‐cell NMR spectroscopy is a promising tool for assessing drug‐target binding directly in living cells, thereby improving the screening and development of new molecules. In this study, we used real‐time in‐cell ¹⁹ F NMR spectroscopy in a flow bioreactor to observe competitive binding of fluorinated benzenesulfonamide derivatives to three cytosolic isoforms of carbonic anhydrase. Quantitative measurement of the dissociation constants relative to a spy ligand allowed an accurate ranking of the compounds based on their intracellular affinities for each isoform. The use of two fluorinated ligands allowed simultaneous observation of spy ligand displacement and test ligand binding, as well as estimation of the effective ratio of free ligand concentrations under poor solubility conditions. We also show that signal saturation caused by short repetition times, which can significantly impact the analysis, can be easily corrected a posteriori. Overall, we show that real‐time in‐cell ¹⁹ F NMR spectroscopy can reliably quantify drug–target binding in the cellular environment, paving the way for future applications in drug discovery.

One of the most important challenges of drug development is identifying whether a candidate molecule can efficiently reach and engage intracellular targets. Cell-based assays are usually employed to address this issue; nevertheless, many compounds that appear promising in vitro fail in cellular or in vivo contexts due to low intracellular activity or off-target effects. In this work, we employed ligand-based in-cell 19F NMR to characterize ligand–target interactions in the cellular environment. We investigated the binding of newly synthesized fluorinated sulfonamide derivatives to various cytosolic isoforms of carbonic anhydrase in living human cells. We assessed target engagement and membrane permeability of each ligand and provided a qualitative affinity ranking of the compounds toward each isoform. The fluorinated compounds characterized in this study are promising scaffolds for the development of isoform-selective inhibitors and may serve as chemical probes for future competitive screenings of nonfluorinated drug candidates in cells.

Most of our knowledge of protein structure and function originates from experiments performed with purified proteins resuspended in dilute, buffered solutions. However, most proteins function in crowded intracellular environments with complex compositions. Significant efforts have been made to develop tools to study proteins in their native cellular settings. Among these tools, in-cell NMR spectroscopy has been the sole technique for characterizing proteins in the intracellular space of living cells at atomic resolution and physiological temperature. Nevertheless, due to technological constraints, in-cell NMR studies have been limited to asynchronous single-cell suspensions, precluding obtaining information on protein behavior in different cellular states. In this study, we present a methodology that allows for obtaining an atomically resolved NMR readout of protein structure and interactions in living human cells synchronized in specific cell cycle phases and within 3D models of human tissue. The described approach opens avenues for investigating how protein structure or drug recognition responds to cell-cell communication or changes in intracellular space composition during transitions among cell cycle phases.

Combining multistep organic synthesis with mammalian cell based protein overexpression leads to isolated ¹³ C– ¹⁹ F spin systems in tryptophan side chains, which represent ideal sensors to probe protein interaction and dynamics using NMR spectroscopy.

Side chain isotope labelling is a powerful tool to study protein structure and interactions by NMR spectroscopy. ¹H,¹³C labelling of side-chain methyl groups in a deuterated background allows studying large molecules, while side-chain aromatic groups are highly sensitive to the interaction with ligands, drugs, and other proteins. In E. coli, side chain labelling is performed by substituting amino acids with isotope-labelled precursors. However, proteins that can only be produced in mammalian cells require expensive isotope-labelled amino acids. Here we provide a simple and cost-effective method to label side chains in mammalian cells, which exploits the reversible reaction catalyzed by endogenous transaminases to convert isotope-labelled α-ketoacid precursors. We show by in-cell and in-lysate NMR spectroscopy that replacing an amino acid in the medium with its cognate precursor is sufficient to achieve selective labelling without scrambling, and how this approach allows monitoring conformational changes such as those arising from ligand binding.

In-cell NMR spectroscopy is the sole technique for characterizing protein structure, dynamics, and interactions in living human cells at atomic resolution. However, its applications have been restricted to asynchronous single-cell suspensions. We developed a strategy based on target protein inducible overexpression in stably transfected cells, allowing the acquisition of high-resolution in-cell NMR spectra in physiologically defined cellular states and 3D tissue models.