Optimization of permeability in a series of pyrrolotriazine inhibitors of IRAK4

Degorce, Sébastien L.; Anjum, Rana; Dillman, Keith; Drew, Lisa; Groombridge, Sam D.; Halsall, Christopher T.; Lenz, Eva M.; Lindsay, Nicola; Mayo, Michele; Pink, Jennifer H.; Robb, Graeme R.; Scott, James S.; Stokes, Stephen; Xue, Yafeng

doi:10.1016/j.bmc.2018.01.008

Cited by 14 publications

(19 citation statements)

References 16 publications

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“…Intriguingly, its far less toxic β-glucuronidase-responsive albumin-binding prodrug could bind covalently to albumin and subsequently release 17 when exposed to the β-glucuronidase . The imidazopyridazine derivative 18 (IC 50 = 28 nM, Figure C) and pyrrolotriazine derivative 19 (IC 50 = 39 nM, Figure C) showed significant activity of CLK2 inhibition. , …”

Section: Disclosed Clk2 Inhibitorsmentioning

confidence: 85%

“…107 The imidazopyridazine derivative 18 (IC 50 = 28 nM, Figure 5C) and pyrrolotriazine derivative 19 (IC 50 = 39 nM, Figure 5C) showed significant activity of CLK2 inhibition. 108,109 Quinoline/Quinazoline Derivatives. In collaboration with SGC, Chaikuad et al published the first crystal structure of CLK2 in the complex of the quinoline derivative 20 (NR9, Figure 6A), which showed moderate enzymatic activity (CLK2 IC 50 = 553 nM).…”

Section: ■ Disclosed Clk2 Inhibitorsmentioning

confidence: 99%

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Development of Cdc2-like Kinase 2 Inhibitors: Achievements and Future Directions

Qin

Feng

et al. 2021

J. Med. Chem.

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Cdc2-like kinases (CLKs; CLK1–4) are associated with various neurodegenerative disorders, metabolic regulation, and viral infection and have been recognized as potential drug targets. Human CLK2 has received increasing attention as a regulator that phosphorylates serine- and arginine-rich (SR) proteins and subsequently modulates the alternative splicing of precursor mRNA (pre-mRNA), which is an attractive target for degenerative disease and cancer. Numerous CLK2 inhibitors have been identified, with several molecules currently in clinical development. The first CLK2 inhibitor Lorecivivint (compound 1) has recently entered phase 3 clinical trials. However, highly selective CLK2 inhibitors are rarely reported. This Perspective summarizes the biological roles and therapeutic potential of CLK2 along with progress on the development of CLK2 inhibitors and discusses the achievements and future prospects of CLK2 inhibitors for therapeutic applications.

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Section: Disclosed Clk2 Inhibitorsmentioning

confidence: 85%

Section: ■ Disclosed Clk2 Inhibitorsmentioning

confidence: 99%

Development of Cdc2-like Kinase 2 Inhibitors: Achievements and Future Directions

Qin

Feng

et al. 2021

J. Med. Chem.

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“…Degorce and co-workers discovered compounds 49 (IRAK4 IC 50 = 0.022 µM) and 50 (IRAK4 IC 50 = 0.094 µM) as potent IRAK4 inhibitors using a scaffold hopping strategy (Fig. 21 ) [ 138 ]. Both compounds displayed good selectivity over a panel of 126 kinases at 1 µM concentration.…”

Section: Serine/threonine Kinase Inhibitorsmentioning

confidence: 99%

Pyrrolo[2,1-f][1,2,4]triazine: a promising fused heterocycle to target kinases in cancer therapy

2021

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“…Recent publications deal with the impact of hydrogen bond acceptor (HBA) strengths on p‐glycoprotein and permeability, or the correlation of HBA strengths of a (hetero‐) aromatic group to the inhibitory activity for their target phosphodiesterase 10 A . Similar investigations have also been performed on multiple kinase projects . The HBA strengths of phosphine oxides are also mentioned in the article describing the discovery of Brigatinib .…”

Section: Introductionmentioning

confidence: 99%

Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths

Bauer

Schneider

Göller

2018

Molecular Informatics

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We present two approaches for the computation of hydrogen bond acceptor strengths, one by machinelearning and one by a composite quantum-mechanical protocol, both based on the well-established pK BHX scale and dataset. The QM calculations after a necessary linear fit reproduce the complexation free energies in solution with an RMSE of 2.6 kJ mol À1 , not far off the expected error of 2 kJ mol À1 obtained from the comparison of experimental data from two different sources. The second approach is by Gaussian Process Regression (GPR) machine-learning. We describe the hydrogen bond acceptor atoms by a radial atomic reactivity descriptor that encodes their electronic and steric environment. The performance of the GPR model on an external test set corresponds to 3.3 kJ mol À1 , which is also close to the experimental error. We apply the GPR model built on experimental data to model the hydrogen bond acceptor strengths of a series of hydrogen bond acceptor sites of 10 phosphodiesterase 10 A inhibitors. The predicted values correlate well with the experimentally measured IC 50 values.Keywords: hydrogen bonds · structure-property relation · machine learning · computational chemistry · density functional theory[a] C.

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Optimization of permeability in a series of pyrrolotriazine inhibitors of IRAK4

Cited by 14 publications

References 16 publications

Development of Cdc2-like Kinase 2 Inhibitors: Achievements and Future Directions

Development of Cdc2-like Kinase 2 Inhibitors: Achievements and Future Directions

Pyrrolo[2,1-f][1,2,4]triazine: a promising fused heterocycle to target kinases in cancer therapy

Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths

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