Polo like kinase 1 (PLK1) is a serine/threonine kinase that plays an important role in multiple phases of the cell cycle, inhibiting its activity has been considered an effective treatment for acute myeloid leukemia (AML). Here, we reported a series of highly potent PLK1 inhibitors. Among them, compound WD6 was identified as the most promising PLK1 inhibitor, with an IC value of 0.27 nM and greatly reduced hERG affinity, with 12.78 % inhibition at 10 μM. Compound WD6 displayed significant anti-proliferative activities against MV4-11 (IC = 23.3 nM), excellent pharmacokinetic properties (t = 7.59 h, AUC = 29300 ng h mL and F = 35.1 %), good PPB and low risk of drug-drug interactions. In vivo, oral administration of compound WD6 at a dose of 20 mg/kg effectively suppressed the tumor growth in the MV4-11 xenograft mouse model. Further research indicated that WD6 exhibited excellent kinase selectivity, arresting MV4-11 cells at G2 phase, inducing apoptosis in a dose-dependent manner and down-regulating the transcription of the proliferation-related oncogene c-MYC. These results showed that compound WD6 has the potential to be a promising drug candidate for treating AML.
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http://dx.doi.org/10.1016/j.ejmech.2025.117480 | DOI Listing |
Eur J Med Chem
March 2025
Department of Biomedical and Chemical Engineering, Liaoning Institute of Science and Technolgy, Benxi, 117004, China. Electronic address:
Polo like kinase 1 (PLK1) is a serine/threonine kinase that plays an important role in multiple phases of the cell cycle, inhibiting its activity has been considered an effective treatment for acute myeloid leukemia (AML). Here, we reported a series of highly potent PLK1 inhibitors. Among them, compound WD6 was identified as the most promising PLK1 inhibitor, with an IC value of 0.
View Article and Find Full Text PDFPharmaceuticals (Basel)
December 2023
Department of Life Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy.
J Chem Inf Model
September 2023
Molecular Discovery, Kinetic Business Centre, Theobald Street, Elstree, Borehamwood, Hertfordshire WD6 4PJ, United Kingdom.
Deep Learning approaches are able to automatically extract relevant features from the input data and capture nonlinear relationships between the input and output. In this work, we present the GRID-derived AI (GrAId) descriptors, a simple modification to GRID MIFs that facilitate their use in combination with Convolutional Neural Networks (CNNs) to build Deep Learning models in a rotationally, conformationally, and alignment-independent approach we are calling DeepGRID. To our knowledge, this is the first time that GRID MIFs have been combined with CNNs in a Deep Learning approach.
View Article and Find Full Text PDFInt J Mol Sci
November 2022
Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto, 8, 06132 Perugia, Italy.
The field of targeted protein degradation, through the control of the ubiquitin-proteasome system (UPS), is progressing considerably; to exploit this new therapeutic modality, the proteolysis targeting chimera (PROTAC) technology was born. The opportunity to use PROTACs engaging of new E3 ligases that can hijack and control the UPS system could greatly extend the applicability of degrading molecules. To this end, here we show a potential application of the ELIOT (E3 LIgase pocketOme navigaTor) platform, previously published by this group, for a scaffold-repurposing strategy to identify new ligands for a novel E3 ligase, such as TRIM33.
View Article and Find Full Text PDFJ Chem Inf Model
March 2022
Laboratory for Chemoinformatics and Molecular Modelling, Department of Chemistry, Biology and Biotechnology, University of Perugia, via Elce di Sotto 8, Perugia 06123, Italy.
Understanding which chemical modifications can be made to known ligands is a key aspect of structure-based drug design and one that was pioneered by the software GRID. We developed FragExplorer with the explicit aim of showing GRID users which fragments would best match the GRID molecular interaction fields in a protein binding site, given a bound ligand as a starting point. Users can grow ligands or replace existing moieties; the R-Group Exploration mode identifies all potential R-Groups and searches for replacements automatically; the Scaffold Exploration mode does the same for all potential scaffolds.
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