Correction to Efficient Targeted Degradation via Reversible and Irreversible Covalent PROTACs.
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ABSTRACT:
SUBMITTER: Gabizon R
PROVIDER: S-EPMC8506570 | biostudies-literature |
REPOSITORIES: biostudies-literature
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2015-09-03 | E-GEOD-60988 | biostudies-arrayexpress
Project description:Transcription factors (TFs) represent a major class of therapeutic targets for the treatment of human diseases including cancer. Although the biological functions and even crystal structures of many TFs have been clearly elucidated, there is still no viable approach to target the majority of TFs, thus rendering them undruggable for decades. PROTACs (proteolysis targeting chimeras) emerge as a powerful class of therapeutic modalities, which rely on induced protein-protein interactions between the proteins of interest (POIs) and E3 ubiquitin ligases to aid the degradation of POIs by the ubiquitin-proteasome system (UPS). Here, we report the development of a platform termed TF-PROTAC, which links an DNA oligonucleotide to an E3 ligase ligand via a click reaction, to selectively degrade the TF of interest. The selectivity of these TF-PROTACs depends on the DNA oligonucleotides utilized that can be specific to the TFs of interest. We have developed two series of VHL-based TF-PROTACs, NF-κB-PROTAC (dNF-κB) and E2F-PROTAC (dE2F), which effectively degrade endogenous p65 and E2F1 proteins in cells, respectively, and subsequently display superior antiproliferative effects in cells. Collectively, our results suggest that TF-PROTACs provide a generalizable platform to achieve selective degradation of TFs and a universal strategy for targeting most "undruggable" TFs.
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Project description:KRAS is mutated in ?20% of human cancers and is one of the most sought-after targets for pharmacological modulation, despite having historically been considered "undruggable." The discovery of potent covalent inhibitors of the KRASG12C mutant in recent years has sparked a new wave of interest in small molecules targeting KRAS. While these inhibitors have shown promise in the clinic, we wanted to explore PROTAC-mediated degradation as a complementary strategy to modulate mutant KRAS. Herein, we report the development of LC-2, the first PROTAC capable of degrading endogenous KRASG12C. LC-2 covalently binds KRASG12C with a MRTX849 warhead and recruits the E3 ligase VHL, inducing rapid and sustained KRASG12C degradation leading to suppression of MAPK signaling in both homozygous and heterozygous KRASG12C cell lines. LC-2 demonstrates that PROTAC-mediated degradation is a viable option for attenuating oncogenic KRAS levels and downstream signaling in cancer cells.
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Project description:Targeted protein degradation (TPD) is emerging as a strategy to overcome the limitations of traditional small-molecule inhibitors. Proteolysis-targeting chimera (PROTAC) technology can be used to target proteins by hijacking the ubiquitin-proteasome system. Conceptually, PROTAC aims to target the "undruggable" majority of proteins in the human proteome. Through constant exploration and optimization of PROTACs and the exploitation of other TPD strategies over two decades, TPD has expanded from theoretical studies to clinical strategies, with practical applications in oncological, immunological, and other diseases. In this review, we introduce the mechanisms, features, and molecular targets of orthodox PROTACs and summarize the PROTAC drugs under study as cancer therapeutics in clinical trials. We also discuss PROTAC derivatives and other TPD strategies, such as lysosome-targeting chimeras, autophagy-targeting chimeras, and molecular glue strategies. Collectively, the studies summarized herein support the full potential of TPD in the biomedical industry.
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2015-09-03 | GSE60988 | GEO
Project description:Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that have emerged as a therapeutic modality to induce targeted protein degradation (TPD) by harnessing cellular proteolytic degradation machinery. PROTACs which ligand the E3 ligase in a covalent manner have attracted intense interest; however, covalent PROTACs with a broad protein of interest (POI) scope have proven challenging to discover by design. Here, we report the structure-guided design and optimization of Von Hippel-Lindau (VHL) protein-targeted sulfonyl fluorides which covalently bind Ser110 in the HIF1α binding site. We demonstrate that their incorporation in bifunctional degraders induces targeted protein degradation of BRD4 or the androgen receptor without further linker optimization. Our study discloses the first covalent VHL ligands which can be implemented directly in bifunctional degrader design, expanding the substrate scope of covalent E3 ligase PROTACs.
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Project description:Potent covalent inhibitors of Bruton's tyrosine kinase (BTK) based on an aminopyrazole carboxamide scaffold have been identified. Compared to acrylamide-based covalent reactive groups leading to irreversible protein adducts, cyanamide-based reversible-covalent inhibitors provided the highest combined BTK potency and EGFR selectivity. The cyanamide covalent mechanism with BTK was confirmed through enzyme kinetic, NMR, MS, and X-ray crystallographic studies. The lead cyanamide-based inhibitors demonstrated excellent kinome selectivity and rat pharmacokinetic properties.
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Project description:The rational design of PROTACs is difficult due to their obscure structure-activity relationship. This study introduces a deep neural network model - DeepPROTACs to help design potent PROTACs molecules. It can predict the degradation capacity of a proposed PROTAC molecule based on structures of given target protein and E3 ligase. The experimental dataset is mainly collected from PROTAC-DB and appropriately labeled according to the DC50 and Dmax values. In the model of DeepPROTACs, the ligands as well as the ligand binding pockets are generated and represented with graphs and fed into Graph Convolutional Networks for feature extraction. While SMILES representations of linkers are fed into a Bidirectional Long Short-Term Memory layer to generate the features. Experiments show that DeepPROTACs model achieves 77.95% average prediction accuracy and 0.8470 area under receiver operating characteristic curve on the test set. DeepPROTACs is available online at a web server ( https://bailab.siais.shanghaitech.edu.cn/services/deepprotacs/ ) and at github ( https://github.com/fenglei104/DeepPROTACs ).
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