InCl3 mediated heteroarylation of indoles and their derivatization via C H activation strategy: Discovery of 2-(1H-indol-3-yl)-quinoxaline derivatives as a new class of PDE4B selective inhibitors for arthritis and/or multiple sclerosis

Sunke, Rajnikanth; Bankala, Ramudu; Thirupataiah, B.; Ramarao, E. V. Venkat Shivaji; Kumar, J.S. Dileep; Doss, Hari Maduri; Medishetti, Raghavender; Kulkarni, Pushkar; Kapavarapu, Ravikumar; Rasool, Mahaboobkhan; Mudgal, Jayesh; Mathew, Jessy Elizabeth; Shenoy, Gautham G.; Parsa, Kishore V. L.; Pal, Manojit

doi:10.1016/j.ejmech.2019.04.020

Cited by 28 publications

(7 citation statements)

References 45 publications

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“…Zebrafish have delivered popular models for demonstrating, or investigating mechanisms of, the hepatotoxicity from traditional medicines − and environmental contaminants, including those of pharmaceutical − and of other industrial origin. − In addition to these applications, zebrafish hepatotoxicity assays are being directly employed in early drug discovery toxicology. Evidence for this can be found in recent reports on studies designed to discover liver-protective compounds against known hepatotoxins, improve formulations or therapeutic indices for promising chemotherapies, , and demonstrate novel compound efficacy in a zebrafish autoimmune disease model, which was coupled with an assessment of hepatotoxicity …”

Section: Intestine Pancreas and Hepatobiliary Toxicitymentioning

confidence: 99%

“…Evidence for this can be found in recent reports on studies designed to discover liverprotective compounds against known hepatotoxins, 179 improve formulations or therapeutic indices for promising chemotherapies, 180,181 and demonstrate novel compound efficacy in a zebrafish autoimmune disease model, which was coupled with an assessment of hepatotoxicity. 182 Gall Bladder. Lipophilic dyes can be used to visualize both lipid metabolism and transport in vivo in larval zebrafish.…”

Section: Chemical Research In Toxicologymentioning

confidence: 99%

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Use of Zebrafish in Drug Discovery Toxicology

Cassar

Adatto

Freeman

et al. 2019

Chem. Res. Toxicol.

384

277

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Unpredicted human safety events in clinical trials for new drugs are costly in terms of human health and money. The drug discovery industry attempts to minimize those events with diligent preclinical safety testing. Current standard practices are good at preventing toxic compounds from being tested in the clinic; however, false negative preclinical toxicity results are still a reality. Continual improvement must be pursued in the preclinical realm. Higher-quality therapies can be brought forward with more information about potential toxicities and associated mechanisms. The zebrafish model is a bridge between in vitro assays and mammalian in vivo studies. This model is powerful in its breadth of application and tractability for research. In the past two decades, our understanding of disease biology and drug toxicity has grown significantly owing to thousands of studies on this tiny vertebrate. This Review summarizes challenges and strengths of the model, discusses the 3Rs value that it can deliver, highlights translatable and untranslatable biology, and brings together reports from recent studies with zebrafish focusing on new drug discovery toxicology. ■ CONTENTS 107Biographies 107 References 108

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Section: Intestine Pancreas and Hepatobiliary Toxicitymentioning

confidence: 99%

Section: Chemical Research In Toxicologymentioning

confidence: 99%

Use of Zebrafish in Drug Discovery Toxicology

Cassar

Adatto

Freeman

et al. 2019

Chem. Res. Toxicol.

384

277

View full text Add to dashboard Cite

show abstract

“…GFAP, CD11b, Iba1, Cox2) following spinal cord injury (Myers et al, 2019;Avila et al, 2017). Furthermore, intraperitoneal administration of the PDE4B inhibitor 2-(1H-indol-3-yl)-quinoxaline (derivative 3b) halted MS disease progression in the EAE zebrafish model starting from a 3 mg/kg dose (Myers et al, 2019;Sunke et al, 2019).…”

Section: Fig 4 (Continued)mentioning

confidence: 99%

Selective PDE4 subtype inhibition provides new opportunities to intervene in neuroinflammatory versus myelin damaging hallmarks of multiple sclerosis

Schepers

Paes

Tiane

et al. 2023

Brain, Behavior, and Immunity

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“…The majority of csDMPs were in CD8+ T cells ( n = 48), a handful of which mapped to genes shown to be differentially expressed in animal models of neurodegenerative diseases (e.g. Dynactin Subunit 5[ 36 ], Isopentenyl-Diphosphate Delta Isomerase 1 [ 37 ], SLIT-ROBO Rho GTPase Activating Protein 1 [ 38 ] and Phosphodiesterase 4D [ 39 ]). Given the absence of DMRs in CD8+ T cells, and low number of csDMPs in other immune cell types, these results serve to guide future cell-type-targeted studies of disease severity, rather than demonstrating a mechanistic role for individual cell-type methylation in determining clinical outcomes.…”

Section: Discussionmentioning

confidence: 99%

Whole-blood methylation signatures are associated with and accurately classify multiple sclerosis disease severity

et al. 2022

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Background The variation in multiple sclerosis (MS) disease severity is incompletely explained by genetics, suggesting genetic and environmental interactions are involved. Moreover, the lack of prognostic biomarkers makes it difficult for clinicians to optimise care. DNA methylation is one epigenetic mechanism by which gene–environment interactions can be assessed. Here, we aimed to identify DNA methylation patterns associated with mild and severe relapse-onset MS (RMS) and to test the utility of methylation as a predictive biomarker. Methods We conducted an epigenome-wide association study between 235 females with mild (n = 119) or severe (n = 116) with RMS. Methylation was measured with the Illumina methylationEPIC array and analysed using logistic regression. To generate hypotheses about the functional consequence of differential methylation, we conducted gene set enrichment analysis using ToppGene. We compared the accuracy of three machine learning models in classifying disease severity: (1) clinical data available at baseline (age at onset and first symptoms) built using elastic net (EN) regression, (2) methylation data using EN regression and (3) a weighted methylation risk score of differentially methylated positions (DMPs) from the main analysis using logistic regression. We used a conservative 70:30 test:train split for classification modelling. A false discovery rate threshold of 0.05 was used to assess statistical significance. Results Females with mild or severe RMS had 1472 DMPs in whole blood (839 hypermethylated, 633 hypomethylated in the severe group). Differential methylation was enriched in genes related to neuronal cellular compartments and processes, and B-cell receptor signalling. Whole-blood methylation levels at 1708 correlated CpG sites classified disease severity more accurately (machine learning model 2, AUC = 0.91) than clinical data (model 1, AUC = 0.74) or the wMRS (model 3, AUC = 0.77). Of the 1708 selected CpGs, 100 overlapped with DMPs from the main analysis at the gene level. These overlapping genes were enriched in neuron projection and dendrite extension, lending support to our finding that neuronal processes, rather than immune processes, are implicated in disease severity. Conclusion RMS disease severity is associated with whole-blood methylation at genes related to neuronal structure and function. Moreover, correlated whole-blood methylation patterns can assign disease severity in females with RMS more accurately than clinical data available at diagnosis.

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InCl3 mediated heteroarylation of indoles and their derivatization via C H activation strategy: Discovery of 2-(1H-indol-3-yl)-quinoxaline derivatives as a new class of PDE4B selective inhibitors for arthritis and/or multiple sclerosis

Cited by 28 publications

References 45 publications

Use of Zebrafish in Drug Discovery Toxicology

Use of Zebrafish in Drug Discovery Toxicology

Selective PDE4 subtype inhibition provides new opportunities to intervene in neuroinflammatory versus myelin damaging hallmarks of multiple sclerosis

Whole-blood methylation signatures are associated with and accurately classify multiple sclerosis disease severity

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