LAS0811: from combinatorial chemistry to activation of antioxidant response element

RiceProteomeDB (RPDB): a user-friendly database for proteomics data storage, retrieval, and analysis

Rice, feeding a significant portion of the world, poses unique proteomic challenges critical to agricultural research and global food security. The complexity of the rice proteome, influenced by various genetic and environmental factors, demands specialized analytical approaches for effective study. The central challenges in rice proteomics lie in developing custom methods suited to the unique aspects of rice biology. These include data preprocessing, method selection, and result validation, all of which are essential for advancing rice research. Our aim is to decode these proteomic intricacies to facilitate breakthroughs in strain improvement, disease resistance, and yield optimization, all vital for combating global food insecurity. To achieve this, we have created the RiceProteomeDB (RPDB), a React + Django database, offering a streamlined and comprehensive platform for the analysis of rice proteomics data. RiceProteomeDB (RPDB) simplifies proteomics data management and analysis. It offers features for data organization, preprocessing, method selection, result validation, and data sharing. Researchers can access processed rice proteomics data, conduct analyses, and explore experimental conditions. The user-friendly web interface enhances navigation and interaction. RPDB fosters collaboration by enabling data sharing and proper acknowledgment of sources, contributing to proteomics research and knowledge dissemination. Availability and implementation: Web application: http://riceproteome.plantprofile.net/ . The web application's source code, user's manual, and sample data: https://github.com/dongu7610/Riceproteome .

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Experimental Strategies to Explore Drug Action and Resistance in Kinetoplastid Parasites

Kinetoplastids are the causative agents of leishmaniasis, human African trypanosomiasis, and American trypanosomiasis. They are responsible for high mortality and morbidity in (sub)tropical regions. Adequate treatment options are limited and have several drawbacks, such as toxicity, need for parenteral administration, and occurrence of treatment failure and drug resistance. Therefore, there is an urgency for the development of new drugs. Phenotypic screening already allowed the identification of promising new chemical entities with anti-kinetoplastid activity potential, but knowledge on their mode-of-action (MoA) is lacking due to the generally applied whole-cell based approach. However, identification of the drug target is essential to steer further drug discovery and development. Multiple complementary techniques have indeed been used for MoA elucidation. In this review, the different 'omics' approaches employed to define the MoA or mode-of-resistance of current reference drugs and some new anti-kinetoplastid compounds are discussed.

Label-free quantitative proteomic analysis revealed a positive effect of ectopic over-expression of PeaT1 from Alternaria tenuissima on rice (Oryza sativa) response to drought

The protein elicitor PeaT1 was found in Alternaria tenuissima and exerted broad spectrum resistance in wheat, cotton, and rice. Recently, we found that overexpressing PeaT1 rice (OE) could enhance plant drought tolerance. Elucidating some elevated drought stress-related proteins and associated mechanisms is inevitable for improving drought tolerance in rice. In this study, combining a label-free quantitative proteomic method, multiple proteins were differentially accumulated in OE plants. Among these, a total of 57 significant changed proteins (including 32 up-regulated and 25 down-regulated) were mainly involved in metabolic, cellular, biological progress, and stress response. Using the RT-qPCR assay, 18 proteins' relative abundance was detected mostly consistent with the proteins abundance in proteomic data. Specially, proteins involved in abiotic stress, such as OsSKIPa and OsPP2C, which were significantly induced in early after dehydration treatment in transgenic rice, and the other stress response genes (prohibitin protein, PsbP protein, msrB Protein) also changed in PeaT1 OE lines. Taken together, these results suggested that these differential proteins would be helpful for understanding the functional molecular mechanism of PeaT1 in rice.

Antioxidant response elements: Discovery, classes, regulation and potential applications

Exposure to antioxidants and xenobiotics triggers the expression of a myriad of genes encoding antioxidant proteins, detoxifying enzymes, and xenobiotic transporters to offer protection against oxidative stress. This articulated universal mechanism is regulated through the cis-acting elements in an array of Nrf2 target genes called antioxidant response elements (AREs), which play a critical role in redox homeostasis. Though the Keap1/Nrf2/ARE system involves many players, AREs hold the key in transcriptional regulation of cytoprotective genes. ARE-mediated reporter constructs have been widely used, including xenobiotics profiling and Nrf2 activator screening. The complexity of AREs is brought by the presence of other regulatory elements within the AREs. The diversity in the ARE sequences not only bring regulatory selectivity of diverse transcription factors, but also confer functional complexity in the Keap1/Nrf2/ARE pathway. The different transcription factors either homodimerize or heterodimerize to bind the AREs. Depending on the nature of partners, they may activate or suppress the transcription. Attention is required for deeper mechanistic understanding of ARE-mediated gene regulation. The computational methods of identification and analysis of AREs are still in their infancy. Investigations are required to know whether epigenetics mechanism plays a role in the regulation of genes mediated through AREs. The polymorphisms in the AREs leading to oxidative stress related diseases are warranted. A thorough understanding of AREs will pave the way for the development of therapeutic agents against cancer, neurodegenerative, cardiovascular, metabolic and other diseases with oxidative stress.

Discovery of potent, novel Nrf2 inducers via quantum modeling, virtual screening, and in vitro experimental validation

Nuclear factor erythroid 2-related factor 2 (Nrf2) is the master transcription factor of the antioxidant response element pathway, coordinating the induction of detoxifying and antioxidant enzymes. Nrf2 is normally sequestered in the cytoplasm by Kelch-like ECH-associating protein 1 (Keap1). To identify novel small molecules that will disturb Nrf2-Keap1 binding and promote activation of the Nrf2- antioxidant response element pathway, we generated a quantum model based on the structures of known Nrf2- antioxidant response element activators. We used the quantum model to perform in silico screening on over 18 million commercially available chemicals to identify the structures predicted to activate the Nrf2- antioxidant response element pathway based on the quantum model. The top hits were tested in vitro, and half of the predicted hits activated the Nrf2-antioxidant response element pathway significantly in primary cell culture. In addition, we identified a new family of Nrf2-antioxidant response element-activating structures that all have comparable activity to tBHQ and protect against oxidative stress and dopaminergic toxins in vitro. The improved ability to identify potent activators of Nrf2 through the combination of in silico and in vitro screening described here improves the speed and cost associated with screening Nrf2-antioxidant response element -activating compounds for drug development.

Identification of UV-protective activators of nuclear factor erythroid-derived 2-related factor 2 (Nrf2) by combining a chemical library screen with computer-based virtual screening

Nuclear factor erythroid-derived 2-related factor 2 (Nrf2) is a master regulator of cellular antioxidant defense systems, and activation of this transcription factor is a promising strategy for protection of skin and other organs from environmental insults. To identify efficient Nrf2 activators in keratinocytes, we combined a chemical library screen with computer-based virtual screening. Among 14 novel Nrf2 activators, the most potent compound, a nitrophenyl derivative of 2-chloro-5-nitro-N-phenyl-benzamide, was characterized with regard to its molecular mechanism of action. This compound induced the expression of cytoprotective genes in keratinocytes isolated from wild-type but not from Nrf2-deficient mice. Most importantly, it showed low toxicity and protected primary human keratinocytes from UVB-induced cell death. Therefore, it represents a potential lead compound for the development of drugs for skin protection under stress conditions. Our study demonstrates that chemical library screening combined with advanced computational similarity searching is a powerful strategy for identification of bioactive compounds, and it points toward an innovative therapeutic approach against UVB-induced skin damage.

Histone deacetylase inhibition activates transcription factor Nrf2 and protects against cerebral ischemic damage

Interest in histone deacetylase (HDAC)-based therapeutics as a potential treatment for stroke has grown dramatically. The neuroprotection of HDAC inhibition may involve multiple mechanisms, including modulation of transcription factor acetylation independent of histones. The transcription factor Nrf2 has been shown to be protective in stroke as a key regulator of antioxidant-responsive genes. Here, we hypothesized that HDAC inhibition might provide neuroprotection against mouse cerebral ischemia by activating the Nrf2 pathway. We determined that the classic HDAC inhibitor trichostatin A increased neuronal cell viability after oxygen-glucose deprivation (from an OD value of 0.10±0.01 to 0.25±0.08) and reduced infarct volume in wild-type mice with stroke (from 49.1±3.8 to 21.3±4.6%). In vitro studies showed that HDAC inhibition reduced Nrf2 suppressor Keap1 expression, induced Keap1/Nrf2 dissociation, Nrf2 nuclear translocation, and Nrf2 binding to antioxidant response elements in heme oxygenase 1 (HO1), and caused HO1 transcription. Furthermore, we demonstrated that HDAC inhibition upregulated proteins downstream of Nrf2, including HO1, NAD(P)H:quinone oxidoreductase 1, and glutamate-cysteine ligase catalytic subunit in neuron cultures and brain tissue. Finally, unlike wild-type mice, Nrf2-deficient mice were not protected by pharmacologic inhibition of HDAC after cerebral ischemia. Our studies suggest that activation of Nrf2 might be an important mechanism by which HDAC inhibition provides neuroprotection.