Novel STAT3 small-molecule inhibitors identified by structure-based virtual ligand screening incorporating SH2 domain flexibility

Identification and mechanistic exploration of key anti-inflammatory molecules in American ginseng: Impacts on signal transducer and activator of transcription 3 STAT3 phosphorylation and macrophage polarization

American ginseng (AG) has been reported to have anti-inflammatory effects in many diseases, but the key molecules and mechanisms are unclear. This study aims to evaluate the anti-inflammatory mechanism of AG and identify the key molecules by in vivo and in vitro models. Zebrafish was employed to assess the anti-inflammatory properties of AG and the compounds. Metabolomics was utilized to identify potential anti-inflammatory molecules in AG, while molecular dynamics simulations were conducted to forecast the interaction capabilities of these compounds with inflammatory targets. Additionally, macrophage cell was employed to investigate the anti-inflammatory mechanisms of the key molecules in AG by enzyme-linked immunosorbent assay and western blotting. Seven potential anti-inflammatory molecules were discovered in AG, with ginsenoside Rg1, ginsenoside Rs3 (G-Rs3), and oleanolic acid exhibiting the strongest affinity for signal transducer and activator of transcription 3. These compounds demonstrated inhibitory effects on macrophage migration in zebrafish models and the ability to regulate ROS levels in both zebrafish and macrophages. The cell experiments found that ginsenoside Rg1, ginsenoside Rs3, and oleanolic acid could promote macrophage M2/M1 polarization ratio and inhibit phosphorylation overexpression of signal transducer and activator of transcription 3. This study revealed the key anti-inflammatory molecules and mechanisms of AG, and provided new evidence of anti-inflammatory for the scientific use of AG.

Enhancing cancer therapy: The role of drug delivery systems in STAT3 inhibitor efficacy and safety

The signal transducer and activator of transcription 3 (STAT3), a member of the STAT family, resides in the nucleus to regulate genes essential for vital cellular functions, including survival, proliferation, self-renewal, angiogenesis, and immune response. However, continuous STAT3 activation in tumor cells promotes their initiation, progression, and metastasis, rendering STAT3 pathway inhibitors a promising avenue for cancer therapy. Nonetheless, these inhibitors frequently encounter challenges such as cytotoxicity and suboptimal biocompatibility in clinical trials. A viable strategy to mitigate these issues involves delivering STAT3 inhibitors via drug delivery systems (DDSs). This review delineates the regulatory mechanisms of the STAT3 signaling pathway and its association with cancer. It offers a comprehensive overview of the current application of DDSs for anti-STAT3 inhibitors and investigates the role of DDSs in cancer treatment. The conclusion posits that DDSs for anti-STAT3 inhibitors exhibit enhanced efficacy and reduced adverse effects in tumor therapy compared to anti-STAT3 inhibitors alone. This paper aims to provide an outline of the ongoing research and future prospects of DDSs for STAT3 inhibitors. Additionally, it presents our insights on the merits and future outlook of DDSs in cancer treatment.

Identification of SH2 domain-containing proteins and motifs prediction by a deep learning method

The Src Homology 2 (SH2) domain plays an important role in the signal transmission mechanism in organisms. It mediates the protein-protein interactions based on the combination between phosphotyrosine and motifs in SH2 domain. In this study, we designed a method to identify SH2 domain-containing proteins and non-SH2 domain-containing proteins through deep learning technology. Firstly, we collected SH2 and non-SH2 domain-containing protein sequences including multiple species. We built six deep learning models through DeepBIO after data preprocessing and compared their performance. Secondly, we selected the model with the strongest comprehensive ability to conduct training and test separately again, and analyze the results visually. It was found that 288-dimensional (288D) feature could effectively identify two types of proteins. Finally, motifs analysis discovered the specific motif YKIR and revealed its function in signal transduction. In summary, we successfully identified SH2 domain and non-SH2 domain proteins through deep learning method, and obtained 288D features that perform best. In addition, we found a new motif YKIR in SH2 domain, and analyzed its function which helps to further understand the signaling mechanisms within the organism.

Lung cancer treatment potential and limits associated with the STAT family of transcription factors

Lung cancer is one of the mortal cancers and the leading cause of cancer-related mortality, with a cancer survival rate of fewer than 5% in developing nations. This low survival rate can be linked to things like late-stage detection, quick postoperative recurrences in patients receiving therapy, and chemoresistance developing against various lung cancer treatments. Signal transducer and activator of transcription (STAT) family of transcription factors are involved in lung cancer cell proliferation, metastasis, immunological control, and treatment resistance. By interacting with specific DNA sequences, STAT proteins trigger the production of particular genes, which in turn result in adaptive and incredibly specific biological responses. In the human genome, seven STAT proteins have been discovered (STAT1 to STAT6, including STAT5a and STAT5b). Many external signaling proteins can activate unphosphorylated STATs (uSTATs), which are found inactively in the cytoplasm. When STAT proteins are activated, they can increase the transcription of several target genes, which leads to unchecked cellular proliferation, anti-apoptotic reactions, and angiogenesis. The effects of STAT transcription factors on lung cancer are variable; some are either pro- or anti-tumorigenic, while others maintain dual, context-dependent activities. Here, we give a succinct summary of the various functions that each member of the STAT family plays in lung cancer and go into more detail about the advantages and disadvantages of pharmacologically targeting STAT proteins and their upstream activators in the context of lung cancer treatment.

Aucubin as a natural potential anti-acute hepatitis candidate: Inhibitory potency and hepatoprotective mechanism

BACKGROUND

Hepatic inflammation can substantially impact the development of acute hepatitis. It is a pressing need to identify and exploit novel therapeutic targets as well as effective drug therapies against acute hepatitis. Aucubin (AU) is one of the main active components extracted from the leaves of Eucommia ulmoides and possesses significant anti-inflammatory and antioxidant activities. However, the protective effect and mechanism of AU on acute hepatitis have not been reported yet.

PURPOSE

This study aims to investigate the protective effect of AU on LPS-induced acute hepatitis and the mechanism of action.

METHODS

The limma package was used to analyze differentially expressed genes (DEGs) between LPS-induced acute hepatitis and normal groups based on Gene Expression Omnibus (GEO) microarray data. Network pharmacology predicted targets for AU therapy against acute hepatitis, and Gene Ontology (GO) enrichment analysis of the biological processes involved in these targets. The key pathways were analyzed by protein-protein interaction, KEGG (Kyoto Encyclopedia of Genes and Genomes), and GSEA (Gene Set Enrichment Analysis) enrichment. The important interaction targets between AU and key pathways were evaluated by molecular simulation. The in silico predicted mechanism was verified based on in vitro and in vivo experiments.

RESULTS

A total of 116 intersection targets between AU prediction targets and differentially expressed genes were identified. They were functionally involved in the imbalance of "inflammation-anti-inflammation" and "oxidation-antioxidation" systems in the process of LPS-induced cases. In vitro experiments revealed that AU reduced inflammation in LPS-induced HepG2 cells by reducing the inflammatory cytokines TNF-α, IL-6, as well as iNOS enzyme activity levels. In addition, LPS-induced oxidative stress can be alleviated by AU via adjusting the levels of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), Malone dialdehyde (MDA) and reactive oxygen species (ROS). Protein-protein interaction and GSEA results showed that AU might exert anti-inflammatory effects mainly through the STAT3/NF-κB signal pathway. Molecular dynamics simulation as well as in vivo tests further demonstrated AU restrained nuclear transfer of NF-κB (P65), probably through reducing phosphorylation of STAT3. In addition, AU appears to reduce oxidative stress by upregulating NRF2/HO-1.

CONCLUSION

We explored potential targets and signal pathways of AU in inhibiting acute hepatitis. AU exerted anti-inflammatory and antioxidant activities and may be a useful candidate drug for the treatment of acute hepatitis.