Hydroxyeicosatetraenoic acids (HETEs) are metabolites of arachidonate acid (AA) oxidized by lipoxygenases or cytochrome P450 enzymes (CYP450). Since lipoxygenases and CYP450 enzymes widely exist in ...different organs and tissues, HETEs play significant roles in normal physiological and pathophysiological conditions. Mounting evidence has shown that HETEs play roles in modulation of inflammation during diabetes development. And accumulating evidence suggests that in prediabetic conditions, HETEs have already impacted on adipose tissue, kidney, heart, and islet. In the current review, we focused on the role of specific HETEs, namely 5-HETE, 12-HETE, 15-HETE and 20-HETE in diabetes, and highlighted their effects in the development of diabetes and diabetes-related complications. In conclusion, elucidation of HETEs’ impacts on different organs that contribute to the development of diabetes leads to identification of novel therapeutic modalities.
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•Provide information of hydroxyeicosatetraenoic acids in diabetes.•Summarize the different role of 5-HETE, 12-HETE, 15-HETE and 20-HETE in diabetes and obesity.•Discuss the potential impacts of HETEs in the prevention and treatment of diabetes.
Kaempferol, a representative flavonoid constituent of Sanguisorba officinalis, promotes melanogenesis, but the underlying mechanisms remain unknown. Here, we evaluated the effects of kaempferol on ...melanocytes morphology and behavior and determined the mechanisms regulating kaempferol-induced pigmentation. We observed that kaempferol increased melanin contents and dendritic length and stimulated melanocyte migration both in vitro and vivo. It significantly enhanced the expression of microphthalmia-associated transcription factor (MITF) and downstream enzymes of melanin biosynthesis—tyrosinase (TYR), tyrosinase-related protein (TRP-1), and dopachrome tautomerase (DCT). It also induced melanosome maturation (increased stage III and IV melanosomes) and melanin transfer to dendritic tips; this was evidenced as follows: kaempferol-treated melanocytes exhibited the perimembranous accumulation of HMB45-positive melanosomes and increased the expression of Rab27A, RhoA, and Cdc42, which improved melanosome transport to perimembranous actin filaments. These results jointly indicated that kaempferol promotes melanogenesis and melanocyte growth. Additionally, kaempferol stimulated the phosphorylation of P38/ERK MAPK and downregulated p-PI3K, p-AKT, and p-P70s6K expression. Pre-incubation with P38 (SB203580) and ERK (PD98059) signaling inhibitors reversed the melanogenic and dendritic effects and MITF expression. PI3K/AKT inhibitor augmented kaempferol-induced melanin content and dendrite length. In summary, kaempferol regulated melanocytes’ dendritic growth and melanosome quantity, maturation, and transport via P38/ERK MAPK and PI3K/AKT signaling pathways.
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A novel series of peptidomimetic aldehydes was designed and synthesized to target 3C protease (3Cpro) of enterovirus 71 (EV71). Most of the compounds exhibited high antiviral activity, and among ...them, compound 18p demonstrated potent enzyme inhibitory activity and broad-spectrum antiviral activity on a panel of enteroviruses and rhinoviruses. The crystal structure of EV71 3Cpro in complex with 18p determined at a resolution of 1.2 Å revealed that 18p covalently linked to the catalytic Cys147 with an aldehyde group. In addition, these compounds also exhibited good inhibitory activity against the 3CLpro and the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), especially compound 18p (IC50 = 0.034 μM, EC50 = 0.29 μM). According to our previous work, these compounds have no reasons for concern regarding acute toxicity. Compared with AG7088, compound 18p also exhibited good pharmacokinetic properties and more potent anticoronavirus activity, making it an excellent lead for further development.
We developed a simple and convenient copper-catalyzed method for the synthesis of quinoline-2-carboxylate derivatives through sequential intermolecular addition of alkynes onto imines and subsequent ...intramolecular ring closure by arylation. The efficiency of this system allowed the reactions to be carried out at room temperature.
Protein-protein interactions (PPIs) are central to most biological processes. Although efforts have been devoted to the development of methodology for predicting PPIs and protein interaction ...networks, the application of most existing methods is limited because they need information about protein homology or the interaction marks of the protein partners. In the present work, we propose a method for PPI prediction using only the information of protein sequences. This method was developed based on a learning algorithm-support vector machine combined with a kernel function and a conjoint triad feature for describing amino acids. More than 16,000 diverse PPI pairs were used to construct the universal model. The prediction ability of our approach is better than that of other sequence-based PPI prediction methods because it is able to predict PPI networks. Different types of PPI networks have been effectively mapped with our method, suggesting that, even with only sequence information, this method could be applied to the exploration of networks for any newly discovered protein with unknown biological relativity. In addition, such supplementary experimental information can enhance the prediction ability of the method.
Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a ...repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking) http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.
PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling) pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores.
PDTD serves as a comprehensive and unique repository of drug targets. Integrated with TarFisDock, PDTD is a useful resource to identify binding proteins for active compounds or existing drugs. Its potential applications include in silico drug target identification, virtual screening, and the discovery of the secondary effects of an old drug (i.e. new pharmacological usage) or an existing target (i.e. new pharmacological or toxic relevance), thus it may be a valuable platform for the pharmaceutical researchers. PDTD is available online at http://www.dddc.ac.cn/pdtd/.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The autophagic ubiquitin‐like protein LC3 functions through interactions with LC3‐interaction regions (LIRs) of other autophagy proteins, including autophagy receptors, which stands out as a ...promising protein–protein interaction (PPI) target for the intervention of autophagy. Post‐translational modifications like acetylation of Lys49 on the LIR‐interacting surface could disrupt the interaction, offering an opportunity to design covalent small molecules interfering with the interface. Through screening covalent compounds, we discovered a small molecule modulator of LC3A/B that covalently modifies LC3A/B protein at Lys49. Activity‐based protein profiling (ABPP) based evaluations reveal that a derivative molecule DC‐LC3in‐D5 exhibits a potent covalent reactivity and selectivity to LC3A/B in HeLa cells. DC‐LC3in‐D5 compromises LC3B lipidation in vitro and in HeLa cells, leading to deficiency in the formation of autophagic structures and autophagic substrate degradation. DC‐LC3in‐D5 could serve as a powerful tool for autophagy research as well as for therapeutic interventions.
A potent probe, DC‐LC3in‐D5, was discovered which demonstrates high selectivity to LC3A/B in the proteome. DC‐LC3in‐D5 inhibits autophagy by attenuating LC3B lipidation, which subsequently reduces the extent of autophagic structure formation and later substrate degradation.
Georgi is a traditional Chinese medicinal plant with broad pharmacological activities whose main active ingredient is the flavonoid baicalin. Given its medicinal value and increasing market demand, ...it is essential to improve the plant's baicalin content. Flavonoid biosynthesis is regulated by several phytohormones, primarily jasmonic acid (JA).
In this study, we conducted transcriptome deep sequencing analysis of
roots treated with methyl jasmonate for different durations (1, 3, or 7 hours). Leveraging weighted gene co-expression network analysis and transcriptome data, we identified candidate transcription factor genes involved in the regulation of baicalin biosynthesis. To validate the regulatory interactions, we performed functional assays such as yeast one-hybrid, electrophoretic mobility shift, and dual-luciferase assays.
Our findings demonstrated that SbWRKY75 directly regulates the expression of the flavonoid biosynthetic gene
, whereas SbWRKY41 directly regulates the expression of two other flavonoid biosynthetic genes,
and
, thus regulating baicalin biosynthesis. We also obtained transgenic
plants by somatic embryo induction and determined that overexpressing SbWRKY75 increased baicalin content by 14%, while RNAi reduced it by 22%. Notably, SbWRKY41 indirectly regulated baicalin biosynthesis by modulating the expression of
and
.
This study provides valuable insights into the molecular mechanisms underlying JA-mediated baicalin biosynthesis in
. Our results highlight the specific roles of transcription factors, namely SbWRKY75 and SbWRKY41, in the regulation of key biosynthetic genes. Understanding these regulatory mechanisms holds significant potential for developing targeted strategies to enhance baicalin content in
through genetic interventions.
Reliable uncertainty quantification for statistical models is crucial in various downstream applications, especially for drug design and discovery where mistakes may incur a large amount of cost. ...This topic has therefore absorbed much attention and a plethora of methods have been proposed over the past years. The approaches that have been reported so far can be mainly categorized into two classes: distance-based approaches and Bayesian approaches. Although these methods have been widely used in many scenarios and shown promising performance with their distinct superiorities, being overconfident on out-of-distribution examples still poses challenges for the deployment of these techniques in real-world applications. In this study we investigated a number of consensus strategies in order to combine both distance-based and Bayesian approaches together with post-hoc calibration for improved uncertainty quantification in QSAR (Quantitative Structure–Activity Relationship) regression modeling. We employed a set of criteria to quantitatively assess the ranking and calibration ability of these models. Experiments based on 24 bioactivity datasets were designed to make critical comparison between the model we proposed and other well-studied baseline models. Our findings indicate that the hybrid framework proposed by us can robustly enhance the model ability of ranking absolute errors. Together with post-hoc calibration on the validation set, we show that well-calibrated uncertainty quantification results can be obtained in domain shift settings. The complementarity between different methods is also conceptually analyzed.
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