Discovery of novel indole derivatives that inhibit NEDDylation and MAPK pathways against gastric cancer MGC803 cells

Fu, Dong-Jun; Cui, Xinxin; Zhu, Ting; Zhang, Yanbing; Hu, Yangyang; Zhang, Lirong; Wang, Shenghui; Zhang, Sai‐Yang

doi:10.1016/j.bioorg.2021.104634

Cited by 19 publications

(7 citation statements)

References 43 publications

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“…In our and others' previous study [25][26][27][28], Neddylation inhibitor MLN4924 has significant anti-tumor effect in both vitro and vivo. Through TCGA database and KEGG analysis, we found that NEED8, an important molecule in the Neddylation pathway, as well as the catalytic enzymes UBE2M and UBE2F, were all transcribed at higher levels in USML tissues than NL tissues (Fig.…”

Section: Correlation Between Hub Genes and Neddylation Pathwaymentioning

confidence: 62%

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

et al. 2021

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Background While large-scale genomic analyses symbolize a precious attempt to decipher the molecular foundation of uterine leiomyosarcoma (ULMS), bioinformatics results associated with the occurrence of ULMS based totally on WGCNA and CIBERSORT have not yet been reported. This study aimed to screen the hub genes and the immune cell infiltration pattern in ULMS by bioinformatics methods. Methods Firstly, the GSE67463 dataset, including 25 ULMS tissues and 29 normal myometrium (NL) tissues, was downloaded from the public database. The differentially expressed genes (DEGs) were screened by the ‘limma’ package and hub modules were identified by weighted gene co-expression network analysis (WGCNA). Subsequently, gene function annotations were performed to investigate the biological role of the genes from the intersection of two groups (hub module and DEGs). The above genes were calculated in the protein–protein interaction (PPI) network to select the hub genes further. The hub genes were validated using external data (GSE764 and GSE68295). In addition, the differential immune cell infiltration between UL and ULMS tissues was investigated using the CIBERSORT algorithm. Finally, we used western blot to preliminarily detect the hub genes in cell lines. Results WGCNA analysis revealed a green-yellow module possessed the highest correlation with ULMS, including 1063 genes. A total of 172 DEGs were selected by thresholds set in the ‘limma’ package. The above two groups of genes were intersected to obtain 72 genes for functional annotation analysis. Interestingly, it indicated that 72 genes were mainly involved in immune processes and the Neddylation pathway. We found a higher infiltration of five types of cells (memory B cells, M0-type macrophages, mast cells activated, M1-type macrophages, and T cells follicular helper) in ULMS tissues than NL tissues, while the infiltration of two types of cells (NK cells activated and mast cells resting) was lower than in NL tissues. In addition, a total of five genes (KDR, CCL21, SELP, DPT, and DCN) were identified as the hub genes. Internal and external validation demonstrated that the five genes were over-expressed in NL tissues compared with USML tissues. Finally, the correlation analysis results indicate that NK cells activated and mast cells activated positively correlated with the hub genes. However, M1-type macrophages had a negative correlation with the hub genes. Moreover, only the DCN may be associated with the Neddylation pathway. Conclusion A series of evidence confirm that the five hub genes and the infiltration of seven types of immune cells are related to USML occurrence. These hub genes may affect the occurrence of USML through immune-related and Neddylation pathways, providing molecular evidence for the treatment of USML in the future.

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Section: Correlation Between Hub Genes and Neddylation Pathwaymentioning

confidence: 62%

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

et al. 2021

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“…It is a three-step enzymatic cascade reaction by E1 NAE, NEDD8-conjugating enzymes E2 (Ubc12 or UBE2F), and NEDD8 E3 ligases 26 . To reveal the inhibitory effects of compound C11 on NEDDylation, a NEDDylation assay was performed according to our reported reference 27 . As shown in Figure 8 , there are no Ubc12-NEDD8 and Ubc12-(NEDD8) 2 bands without the treatment of ATP.…”

Section: Resultsmentioning

confidence: 99%

Discovery of dual tubulin-NEDDylation inhibitors with antiproliferative activity

Wang

2022

Journal of Enzyme Inhibition and Medicinal Chemistry

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Although various dual-target tubulin inhibitors have been designed and synthesised, no dual tubulin-NEDDylation inhibitors as antiproliferative agents were reported so far. In this work, a series of trimethoxyphenyl analogues as potential dual tubulin-NEDDylation inhibitors were synthesised and evaluated for their antiproliferative activity. Among them, compound C11 exhibited the most potent inhibitory activity with IC 50 values of 1.17, 2.48, and 1.47 μM against HepG2, PC3, and MCF7 cells, respectively. In addition, it displayed the potent inhibitory activity against tubulin with an IC 50 value of 2.40 μM and obviously inhibited tubulin polymerisation in HepG2 cells. Furthermore, C11 inhibited NEDDylation by a ATP-dependent manner. Molecular docking studies revealed that the methoxy group and dithiocarbamate group of C11 could form hydrogen bonds with residues of tubulin and E1 NEDD8-activating enzyme (NAE). These results suggested that compound C11 was a dual tubulin-NEDDylation inhibitor with antiproliferative activity.

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“…Besides, analogue 28 caused MGC803 cell G2/M phase arrest and induced apoptosis. Continually, Zhang's group synthesized a new array of indole-based compounds mainly through the modifications of rings A and B (Figure 14 C) 212 . Particularly, compound 29 exhibited the strongest biological activity toward MGC803, PC3, EC109 cells with the IC 50 values of 1.59, 3.56, 14.52 μM separately.…”

Section: Inhibitors Of Neddylation Enzymesmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Targeting cullin neddylation for cancer and fibrotic diseases

He,

Yang,

Zengyangzong

et al. 2023

Theranostics

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Protein neddylation is a post-translational modification, and its best recognized substrates are cullin family proteins, which are the core component of Cullin-RING ligases (CRLs). Given that most neddylation pathway proteins are overactivated in different cancers and fibrotic diseases, targeting neddylation becomes an emerging approach for the treatment of these diseases. To date, numerous neddylation inhibitors have been developed, of which MLN4924 has entered phase I/II/III clinical trials for cancer treatment, such as acute myeloid leukemia, melanoma, lymphoma and solid tumors. Here, we systematically describe the structures and biological functions of the critical enzymes in neddylation, highlight the medicinal chemistry advances in the development of neddylation inhibitors and propose the perspectives concerning targeting neddylation for cancer and fibrotic diseases.

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Discovery of novel indole derivatives that inhibit NEDDylation and MAPK pathways against gastric cancer MGC803 cells

Cited by 19 publications

References 43 publications

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

Discovery of dual tubulin-NEDDylation inhibitors with antiproliferative activity

Targeting cullin neddylation for cancer and fibrotic diseases

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