Oligosaccharyltransferase inhibition induces senescence in RTK-driven tumor cells

Lopez-Sambrooks, Cecilia; Shrimal, Shiteshu; Khodier, Carol; Flaherty, Daniel P.; Rinis, Natalie; Charest, Jonathan; Gao, Ningguo; Zhao, Peng; Wells, Lance; Lewis, Timothy A.; Lehrman, Mark A.; Gilmore, Reid; Golden, Jennifer E.; Contessa, Joseph N.

doi:10.1038/nchembio.2194

Cited by 90 publications

(126 citation statements)

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“…To evaluate post-exposure antiviral activity, we treated cells 24 hours after infection and observed a ~80% decrease in DENV infection, which was somewhat lower compared to the immediate treatment (~99% decrease)(Figure S1A). As inhibition of the OST complex may cause cell cycle arrest and reduced proliferation (Lopez-Sambrooks et al, 2016), we determined the effects of increasing concentrations of NGI-1 on HEK293 proliferation. The half maximum cytotoxic concentration (CC 50 ) value in HEK293 cells was 34.9 μM and 33.1 μM using Cell Titer Glo (Figure 1F) and Trypan Blue exclusion assay (Figure S1B), respectively, confirming that the antiviral effects were not caused by reduced proliferation.…”

Section: Resultsmentioning

confidence: 99%

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A Small-Molecule Oligosaccharyltransferase Inhibitor with Pan-flaviviral Activity

et al. 2017

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Summary The mosquito-borne flaviviruses include important human pathogens such as dengue, Zika, West Nile and yellow fever virus, which pose a serious threat for global health. Recent genetic screens identified ER-membrane multiprotein complexes including the oligosaccharyltransferase (OST) complex as critical flavivirus host factors. Here, we show that a chemical modulator of the OST complex termed NGI-1 has promising antiviral activity against flavivirus infections. We demonstrate that NGI-1 blocks viral RNA replication, and that antiviral activity does not depend on inhibition of the N-glycosylation function of the OST. Viral mutants adapted to replicate in cells deficient of the OST complex showed resistance to NGI-1 treatment reinforcing the on-target activity of NGI-1. Lastly, we show that NGI-1 also has strong antiviral activity in primary and disease-relevant cell types. This study provides an example for advancing from the identification of genetic determinants of infection to a host-directed antiviral compound with broad activity against flaviviruses.

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Section: Resultsmentioning

confidence: 99%

“…Here, we used a recently developed, cell-permeable small molecule compound called NGI-1 that targets the OST complex (Lopez-Sambrooks et al, 2016). We show that NGI-1 exhibits pan-flaviviral activity by blocking the viral RNA synthesis.…”

Section: Introductionmentioning

confidence: 99%

A Small-Molecule Oligosaccharyltransferase Inhibitor with Pan-flaviviral Activity

et al. 2017

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“…In the area of drug discovery, active learning has been shown to efficiently derive high-performance prediction models based on small subsets of input data [32,34,39,46]. Furthermore, actively trained models not only reached significantly higher hit rates compared to experimental standards which frequently remain below 1 % in cases of unbiased chemical libraries [34,39,40,[47][48][49], but such models also contributed to successful identification of novel bioactive compounds [33,36,42] and cancer rescue mutants of p53 [31]. Overall, AL approaches bear the potential to improve drug discovery processes by increasing hit rates, reducing the amount of time-and cost-intensive experimentation, and accelerate hit-to-lead processes through integration into a feedback-driven experimentation workflow [33,36,42,43,50].…”

Section: Introductionmentioning

confidence: 99%

Small Random Forest Models for Effective Chemogenomic Active Learning

Rakers

Reker

Brown

2017

J. Comput. Aided Chem.

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The identification of new compound-protein interactions has long been the fundamental quest in the field of medicinal chemistry. With increasing amounts of biochemical data, advanced machine learning techniques such as active learning have been proven to be beneficial for building high-performance prediction models upon subsets of such complex data. In a recently published paper, chemogenomic active learning had been applied to the interaction spaces of kinases and G protein-coupled receptors featuring over 150,000 compound-protein interactions. Prediction models were actively trained based on random forest classification using 500 decision trees per experiment. In a new direction for chemogenomic active learning, we address the question of how forest size influences model evolution and performance. In addition to the original chemogenomic active learning findings that highly predictive models could be constructed from a small fraction of the available data, we find here that that model complexity as viewed by forest size can be reduced to one-fourth or one-fifth of the previously investigated forest size while still maintaining reliable prediction performance. Thus, chemogenomic active learning can yield predictive models with reduced complexity based on only a fraction of the data available for model construction.

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“…What's more, in multicellular eukaryotes, endoplasmic reticulum stress is induced by three upstream signaling proteins (IRE-1α, PERK and ATF6), and these three pathway co-formed the UPR. Under normal circumstances, IRE-1α, PERK and Bip/GRP78 combined into a complex in an inactive state [26], however, when a stress response occurs, unfolded proteins or misfolding proteins accumulated in the endoplasmic reticulum, and three transmembrane proteins were activated by separation of Bip/GRP78, so the rapid upregulation of GRP78 marked the beginning of ERS [27]. Some studies have…”

Section: Discussionmentioning

confidence: 99%

Effects of Endoplasmic Reticulum Stress on Pulmonary Hypertension in Rat Induced by Chronic Hypoxia and Hypercapnia

Zhang¹,

Zhang²,

Wu³

et al. 2018

JBM

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Objective: To observe the pulmonary vascular remodeling in rats with pulmonary hypertension induced by hypoxia and hypercapnia, and to explore the role of endoplasmic reticulum stress in pulmonary hypertension. Methods: 1) 40 SD rats were randomly divided into four groups: normoxic control group (N), hypoxia hypercapnia group (HH), endoplasmic reticulum stress (ERS) inhibitor 4-phenyl butyric acid group (4-PBA), ERS pathway agonist tunicamycin group (TM). 2) The mean pulmonary arterial pressure (mPAP) and the right ventricular hypertrophy index (RV/(LV + S)) were measured in each group. 3) Identification of pulmonary artery smooth muscle cells (PASMCs) in each group by immunofluorescence α-SMA. 4) Morphological changes of lung tissue and pulmonary artery were observed by electron microscope. 5) The apoptotic index of PASMCs in each group was detected by TUNEL. 6) Reverse transcription polymerase chain reaction (RT-PCR) and Western Blot (WB) were used to detect the expression of ERS related protein and mRNA (GRP78, CHOP, JNK, Caspase-12) in each group. Results: 1) Compared with the N group, the mPAP, RV/(LV + S) and vascular wall area (WA)/total area (TA) value of HH group, 4-PBA group and TM group were increased (P < 0.01), and the vascular lumen area (LA)/TA values, PASMCs apoptosis index were significantly decreased. GRP78, CHOP, JNK, Caspase-12 expression were increased, and the differences were statistically significant. 2) Compared with the HH group, the mPAP, RV/(LV + S) and WA/TA of 4-PBA group were decreased (P < 0.01); the LA/TA value and PASMCs apoptosis index were increased (P < 0.05); and the mRNA and protein expression of CHOP, JNK, Caspase-12 and GRP78 had a significant decrease (P < 0.05). 3) Compared with the HH, the mPAP, RV/(LV + S) and WA/TA of TM group were increased (P < 0.05, P < 0.01), while LA/TA were decreased (P < 0.01); and PASMCs apoptotic index was increased (P < 0.01). Meanwhile, the mRNA expression of Caspase-12, CHOP, JNK and GRP78 was increased to varying degrees (P < 0.05), and the protein expression of Caspase-12, CHOP and JNK was also increased significantly (P < 0.01). Conclusion: Hypoxia and hypercapnia induced pulmonary vascular remodeling may be related to the proliferation of PASMCs, and ERS related factors (JNK, Caspase12 and CHOP) are involved in the regulation of hypoxic hypercapnia.

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Oligosaccharyltransferase inhibition induces senescence in RTK-driven tumor cells

Cited by 90 publications

References 45 publications

A Small-Molecule Oligosaccharyltransferase Inhibitor with Pan-flaviviral Activity

A Small-Molecule Oligosaccharyltransferase Inhibitor with Pan-flaviviral Activity

Small Random Forest Models for Effective Chemogenomic Active Learning

Effects of Endoplasmic Reticulum Stress on Pulmonary Hypertension in Rat Induced by Chronic Hypoxia and Hypercapnia

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