MedChemComm最新文献

Cancer cell proliferation and metastasis are known to be dependent on angiogenesis which is regulated by several parameters including copper availability. Tetradentate monoquinoline (TDMQ) ligands constitute a series of chelators tailored to regulate copper homeostasis due to their specificity for copper(II) with respect to Cu(I) or other biometals like iron or zinc. One of these chelators, TDMQ20 efficiently inhibits both proliferation and migration of several human cancer cell lines, better than the reference drug 5-fluorouracil, and with higher selectivity indexes with respect to non-cancer human cells. The biological activity of TDMQ20 may be driven by the coordination chemistry of copper, and the ability of this chelator to restore copper homeostasis and its subsequent redox properties. The anticancer mechanism of action of TDMQ20 involves intracellular production of reactive oxygen species, drastic mitochondrial damages and induction of tumor cell apoptosis. These data support the selection of TDMQ20 as drug-candidate against several human cancers.

The phosphoantigen (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMBPP) is an established activator of Vγ9/Vδ2 T cells and stimulates downstream effector functions including cytotoxicity and cytokine production. In order to improve its drug-like properties, we herein report the design, synthesis, serum stability, in vitro metabolism, and biological evaluation of a new class of symmetrical phosphonodiamidate prodrugs of methylene and difluoromethylene monophosphonate derivatives of HMBPP. These prodrugs, termed phosphonodiamidate ProPAgens, were synthesized in good yields, exhibited excellent serum stability (>7 h), and their in vitro metabolism was shown to be initiated by carboxypeptidase Y. These phosphonodiamidate ProPAgens triggered potent activation of Vγ9/Vδ2 T cells, which translated into efficient Vγ9/Vδ2 T cell-mediated eradication of bladder cancer cells in vitro. Together, these findings showcase the potential of these phosphonodiamidate ProPAgens as Vγ9/Vδ2 T cell modulators that could be further developed as novel cancer immunotherapeutic agents.

Molecular machine learning algorithms are becoming increasingly powerful at predicting the potency of potential drug candidates to guide molecular discovery, lead series prioritization, and structural optimization. However, a substantial amount of inhibition data is bounded and inaccessible to traditional regression algorithms. Here, we develop a novel molecular pairing approach to process this data. This creates a new classification task of predicting which one of two paired molecules is more potent. This novel classification task can be accurately solved by various, established molecular machine learning algorithms, including XGBoost and Chemprop. Across 230 ChEMBL IC₅₀ datasets, both tree-based and neural network-based “DeltaClassifiers” show improvements over traditional regression approaches in correctly classifying molecular potency improvements. The Chemprop-based deep DeltaClassifier outperformed all here evaluated regression approaches for paired molecules with shared and with distinct scaffolds, highlighting the promise of this approach for molecular optimization and scaffold-hopping.

To investigate atropisomers of non-steroidal glucocorticoid receptor modulator GSK866, a virtual library of substituted benzoic acid analogues was enumerated. Compounds from this library were subjected to a torsion angle scan using Spartan'20 to calculate the torsion rotation energy barrier which identified compounds predicted to be stable as atropisomers. After synthesis of the library, analysis showed that compounds 13 and 14 existed as stable atropisomers 13a, 13b, 14a and 14b, in agreement with the earlier calculations. Screening in a glucocorticoid receptor cellular assay showed that one compound from each atropisomer pair was significantly more potent than the other. Docking in a public structure of the glucocorticoid receptor (PBD code 3E7C) enabled the stereochemistry of the two most potent compounds 13a and 14b to be assigned as (R_a) and (S_a), respectively.

Computational algorithms and tools have retrenched the drug discovery and development timeline. The applicability of computational approaches has gained immense relevance owing to the dramatic surge in the structural information of biomacromolecules and their heteromolecular complexes. Computational methods are now extensively used in identifying new protein targets, druggability assessment, pharmacophore mapping, molecular docking, the virtual screening of lead molecules, bioactivity prediction, molecular dynamics of protein–ligand complexes, affinity prediction, and for designing better ligands. Herein, we provide an overview of salient components of recently reported computational drug-discovery workflows that includes algorithms, tools, and databases for protein target identification and optimized ligand selection.

As pregnant women and young children remain the first victims of malaria worldwide, the search for new antimalarials has been focusing on compounds with a high safety profile and extended efficacy. In a previous study, a rigid biphenyl PfDHFR inhibitor was developed by fragment-based screening, displaying sub nM enzyme inhibition but poor antiparasitic activity, presumably due to its low flexibility. Here, we report a new series of compounds that combines the biphenyl fragment with a flexible linker. Interestingly, their mode of binding differs from previously reported compounds, taking advantage of strong hydrophobic interaction. The new flexible biphenyl compounds show overall improved antiparasitic activity compared to rigid ones, with the best compound displaying a 2 nM antiplasmodial IC₅₀ and suitable drug-like properties. This confirms the importance of compound flexibility for antimalarial activity and opens the way to new opportunities for antimalarial drug design.

Oral cancer (OC) stands as a prominent cause of global mortality. Despite numerous efforts in recent decades, the efficacy of novel therapies to extend the lifespan of OC patients remains disappointingly low. Consequently, the demand for innovative therapeutic agents has become all the more pressing. In this context, we present our work on the design and synthesis of twenty-five novel quinoxaline-tethered imidazopyri(mi)dine derivatives. This was followed by comprehensive investigations into the impact of these molecules on the OC cell line. The in vitro cytotoxicity studies performed in CAL-27 and normal oral epithelial (NOE) cell lines revealed that some of the synthesized molecules like 12d have potent antiproliferative activity specifically towards OC cells with an IC₅₀ of 0.79 μM and show negligible cytotoxicity over NOE cells. Further, 12d arrested cell growth in the S phase of the cell cycle and induced cell death by early apoptosis. The in silico studies validated that 12d binds to the activator binding site on pyruvate kinase M2 (PKM2) overexpressed in OC while the lactate dehydrogenase (LDH)-coupled enzyme assay established 12d as a potent PKM2 activator with an AC₅₀ of 0.6 nM. Hence, this study provides fruitful evidence for the designed compounds as anticancer agents against OC.

Lysosomotropism is a phenomenon of diverse pharmaceutical interests because it is a property of compounds with diverse chemical structures and primary targets. While it is primarily reported to be caused by compounds having suitable lipophilicity and basicity values, not all compounds that fulfill such criteria are in fact lysosomotropic. Here, we use morphological profiling by means of the cell painting assay (CPA) as a reliable surrogate to identify lysosomotropism. We noticed that only 35% of the compound subset with matching physicochemical properties show the lysosomotropic phenotype. Based on a matched molecular pair analysis (MMPA), no key substructures driving lysosomotropism could be identified. However, using explainable machine learning (XML), we were able to highlight that higher lipophilicity, basicity, molecular weight, and lower topological polar surface area are among the important properties that induce lysosomotropism in the compounds of this subset.

Native mass spectrometry (nMS) is well established as a biophysical technique for characterising biomolecules and their interactions with endogenous or investigational small molecule ligands. The high sensitivity mass measurements make nMS particularly well suited for applications in fragment-based drug discovery (FBDD) screening campaigns where the detection of weakly binding ligands to a target biomolecule is crucial. We first reviewed the contributions of nMS to guiding FBDD hit identification in 2013, providing a comprehensive perspective on the early adoption of nMS for fragment screening. Here we update this initial progress with a focus on contributions of nMS that have guided FBDD for the period 2014 until end of 2023. We highlight the development of nMS adoption in FBDD in the context of other biophysical fragment screening techniques. We also discuss the roadmap for increased adoption of nMS for fragment screening beyond soluble proteins, including for guiding the discovery of fragments supporting advances in PROTAC discovery, RNA-binding small molecules and covalent therapeutic drug discovery.

Of the different modalities used to treat retinoblastoma, a chemothermotherapeutic regimen combining carboplatin and thermotherapy (also termed focal therapy), and the application of melphalan as a monotherapy, are particularly successful. Some studies indicate that melphalan shows potential when applied in combination with focal therapy, and yet is not applied in this combination. Here we describe a series of synthetically modified melphalan derivatives that display enhanced cytotoxicity relative to melphalan itself, with some displaying further enhancements in cytotoxicity when applied in combination with heat (used as a model for thermotherapy). The synthetic approach, which involves modifying melphalan with perfluorous chains of varying lengths via an ester linker, could lead to a more effective treatment option for retinoblastoma with reduced side-effects, which is a key limitation of melphalan.