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Mechanistic deconvolution of autoreduction in tetrazolium-based cell viability assays

Tran et al. | Jul 12, 2024

Mechanistic deconvolution of autoreduction in tetrazolium-based cell viability assays

Optical reporters like tetrazolium dyes, exemplified by 5-diphenyl tetrazolium bromide (MTT), are effective tools for quantifying cellular responses under experimental conditions. These dyes assess cell viability by producing brightly-colored formazan dyes when reduced inside active cells. However, certain small molecules, including reducing agents like ascorbic acid, cysteine, and glutathione (GSH), can interfere with MTT assays, potentially compromising accuracy.

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Computational development of aryl sulfone compounds as potential NNRTIs

Zhang et al. | Oct 12, 2022

Computational development of aryl sulfone compounds as potential NNRTIs

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors that bind to the HIV reverse transcriptase and prevent replication. Indolyl aryl sulfones (IAS) and IAS derivatives have been found to be highly effective against mutant strains of HIV-1 reverse transcriptase. Here, we analyzed molecules designed using aryl sulfone scaffolds paired to cyclic compounds as potential NNRTIs through the computational design and docking of 100 novel NNRTI candidates. Moreover, we explored the specific combinations of functional groups and aryl sulfones that resulted in the NNRTI candidates with the strongest binding affinity while testing all compounds for carcinogenicity. We hypothesized that the combination of an IAS scaffold and pyrimidine would produce the compounds with the best binding affinity. Our hypothesis was correct as the series of molecules with an IAS scaffold and pyrimidine exhibited the best average binding affinity. Additionally, this study found 32 molecules designed in this procedure with higher or equal binding affinities to the previously successful IAS derivative 5-bromo-3-[(3,5-dimethylphenyl)sulfonyl]indole-2-carboxyamide when docked to HIV-1 reverse transcriptase.

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High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

Shern et al. | Jan 20, 2021

High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

As cancer continues to take millions of lives worldwide, the need to create effective therapeutics for the disease persists. The kinesin Eg5 assembly motor protein is a promising target for cancer therapeutics as inhibition of this protein leads to cell cycle arrest. Monastrol, a small dihydropyrimidine-based molecule capable of inhibiting the kinesin Eg5 function, has attracted the attention of medicinal chemists with its potency, affinity, and specificity to the highly targeted loop5/α2/α3 allosteric binding pocket. In this work, we employed high-throughput virtual screening (HTVS) to identify potential small molecule Eg5 inhibitors from a designed set of novel dihydropyrimidine analogs structurally similar to monastrol.

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Evaluation of Tea Extract as an Inhibitor of Oxidative Stress in Prostate Cells

Zhang et al. | Jan 22, 2019

Evaluation of Tea Extract as an Inhibitor of Oxidative Stress in Prostate Cells

One important factor that contributes to human cancers is accumulated damage to cells' DNA due to the oxidative stress caused by free radicals. In this study, the authors investigate the effects of several different tea leaf extracts on oxidative stress in cultured human prostate cells to see if antioxidants in the tea leaves could help protect cells from this type of DNA damage. They found that all four types of tea extract (as well as direct application of the antioxidant EGCG) improved the outcomes for the cultured cells, with white tea extract having the strongest effect. This research suggests that tea extracts and the antioxidants that they contain may have applications in the treatment of the many diseases associated with cellular DNA damage, including cancer.

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Down-regulation of CD44 inhibits Wnt/β-catenin mediated cancer cell migration and invasion in gastric cancer

Baek et al. | May 10, 2021

Down-regulation of CD44 inhibits Wnt/β-catenin mediated cancer cell migration and invasion  in gastric cancer

In this study, we aimed to characterize CD44-mediated regulation of the Wnt/β-catenin signaling pathway, which promotes cancer invasion and metastasis. We hypothesized that CD44 down-regulation will inhibit gastric cancer cell migration and invasion by leading to down-regulation of Wnt/β-catenin signaling. We found that CD44 up-regulation was significantly related to poor prognosis in gastric cancer patients. We demonstrated the CD44 down-regulation decreased β-catenin protein expression level. Our results suggest that CD44 down-regulation inhibits cell migration and invasion by down-regulating β-catenin expression level.

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Efficacy of electrolytic treatment on degrading microplastics in tap water

Schroder et al. | Apr 23, 2023

Efficacy of electrolytic treatment on degrading microplastics in tap water
Image credit: Imani

Here seeking to identify a method to remove harmful microplastics from water, the authors investigated the viability of using electrolysis to degrade microplastics in tap water. Compared to control samples, they found electrolysis treatment to significantly the number of net microplastics, suggesting that this treatment could potentially implemented into homes or drinking water treatment facilities.

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Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation

Gupta et al. | Jan 31, 2023

 Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation
Image credit: Markus Spiske

Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.

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