AKR1C3 _ DDH3
- Known as:
- AKR1C3 _ DDH3
- Catalog number:
- MC983
- Product Quantity:
- 0.1 ml
- Category:
- -
- Supplier:
- ACR
- Gene target:
- AKR1C3 _ DDH3
Related genes to: AKR1C3 _ DDH3
- Gene:
- AKR1C3 NIH gene
- Name:
- aldo-keto reductase family 1 member C3
- Previous symbol:
- HSD17B5
- Synonyms:
- KIAA0119, DDX, HAKRB, PGFS
- Chromosome:
- 10p15.1
- Locus Type:
- gene with protein product
- Date approved:
- 1998-09-29
- Date modifiied:
- 2016-10-05
Related products to: AKR1C3 _ DDH3
Related articles to: AKR1C3 _ DDH3
- Amomum tsao-ko is a medicinal spice whose organic acids determine flavor and bioactivity, yet systematic profiling is lacking. We performed metabolomics across three accessions and two processing states, network pharmacology on differential metabolites, and transcriptomics on fresh fruits of three accessions. Metabolomics resolved accession-specific and drying-responsive profiles. Network pharmacology identified core targets converging on steroid hormone biosynthesis and inflammatory pathways, and molecular docking prioritized three organic acids, including jasmonic acid, abscisic acid, and 1-(2-amino-3-methylpentanoyl)pyrrolidine-2-carboxylic acid, with strong binding to PTGS2, AKR1C3, and CYP19A1. Transcriptomics revealed that key biosynthetic genes for jasmonic acid and abscisic acid, including LOX2S, AOS, NCED, and ABA2, were differentially expressed across accessions in patterns consistent with the corresponding metabolite accumulation levels. These cross-validated findings link organic acid composition to genotype and processing, highlight candidate bioactives for inflammation and endocrine modulation, and provide a foundation for germplasm evaluation and medicinal development of A. tsao-ko. - Source: PubMed
Publication date: 2026/09/20
Fu HongboGuo JinmingXiong LinaLi YanMa MengliLu Bingyue - A library of 24 structurally diverse bile-acid derivatives, comprising 11 new derivatives and 13 previously reported analogues, was prepared. Twenty selected compounds were evaluated against six cancer cell lines and MRC-5 fibroblasts. Lactams 14, 15 and 17 and oxime 10 produced the strongest cell-line-dependent antiproliferative activities, with IC₅₀ values below 10 µM in selected cancer-cell models and MRC-5 IC₅₀ values above 100 µM. Interactions with the ligand-binding domains (LBDs) of estrogen receptor α (ERα), estrogen receptor β (ERβ), androgen receptor (AR) and glucocorticoid receptor (GR) were evaluated using yeast-based fluorescent biosensors. Compound 27 showed the highest affinity for ERβ-LBD, whereas compound 24 exhibited weak affinity for ERα-LBD. No detectable binding to AR-LBD was observed for the tested derivatives, while compounds 10 and 30 showed the highest affinity for GR-LBD. Preliminary screening identified several potent AKR1C3 and AKR1C4 inhibitors, while concentration-dependent assays confirmed the inhibitory activity of compounds 23 and 30 against AKR1C3, with IC₅₀ values of 23.22 and 24.61 μM, respectively. Molecular docking generated plausible binding models for selected compounds within the AKR1C3 and GR ligand-binding sites. Matched-series analysis did not reveal a universally favourable chemotype or a simple relationship between cLogP, TPSA and biological activity. Instead, activity depended on the position of modification and the underlying bile-acid scaffold. These findings highlight the bile-acid framework as a versatile and tunable scaffold for anticancer drug discovery, in which variation of functional group identity and position can generate distinct biological profiles and provide different starting points for further optimization. - Source: PubMed
Publication date: 2026/09/15
Bekić SofijaMarinović MajaJakimov DimitarNikolić AndreaBjedov SrdjanPavlović Ksenija - Parkinson's disease (PD) is a complex neurodegenerative disorder in which environmental toxins play a critical etiological role. Rotenone, a classical mitochondrial complex I inhibitor used to model PD, exerts its neurotoxicity through incompletely defined downstream molecular networks. Here, we integrated multiple PD transcriptomic datasets from GEO with predicted rotenone targets, applied machine learning to screen core candidate genes, and analyzed their cellular localization using single-cell transcriptomics. Molecular docking was performed to assess target-rotenone binding, and functional validation was carried out in primary dopaminergic neurons via lentivirus-mediated gene manipulation, Western blotting, qRT-PCR, and mitochondrial function assays. This approach identified and validated a six-gene core network (AKR1C2, AKR1C3, CES1, CTSS, DRD2, HSPA1A), several of which were predicted to directly bind rotenone. Single-cell analysis confirmed their enrichment in PD dopaminergic neurons, and immunofluorescence validated their co-localization with the dopaminergic marker TH. In rotenone-treated neurons, all six genes except DRD2, as well as KRT8, were significantly upregulated at both the mRNA and protein levels; rotenone also impaired mitochondrial Complex I activity and ATP production, and increased α-synuclein expression. In silico knockout revealed that AKR1C2-perturbed genes were enriched in keratinization pathways. Functional experiments demonstrated that AKR1C2 positively regulates KRT8. Notably, AKR1C2 knockdown not only reduced KRT8 levels but also rescued mitochondrial function, neuronal viability, and rotenone-impaired action potential firing, whereas AKR1C2 overexpression exacerbated these deficits. Critically, KRT8 re‑expression reversed the protective effects of AKR1C2 knockdown, while KRT8 knockdown reversed AKR1C2 overexpression‑induced impairments, collectively confirming the causal role of the AKR1C2-KRT8 axis. Collectively, these findings delineate a multi-node molecular network downstream of rotenone and provide the first experimental validation of a novel AKR1C2-KRT8 regulatory axis in dopaminergic neuron injury. - Source: PubMed
Publication date: 2026/09/01
Lin JianheHe LianyuWang JinglingYang CuiyuLiang ShushuHuang JinshanLi SijunZheng DengxingLiang Mei - Ochratoxin A (OTA), a food-borne mycotoxin, has been implicated in hepatotoxicity and potential carcinogenic processes, yet the molecular links between OTA exposure and hepatocellular carcinoma (HCC) remain incompletely understood. This study used an integrated computational workflow to prioritize candidate targets and pathways potentially linking OTA exposure with HCC. OTA-related and HCC-related targets were collected from public databases, intersected, and subjected to functional enrichment analysis. Transcriptomic data from the GSE36376 discovery dataset were analyzed to identify differentially expressed genes, followed by LASSO and SVM-RFE feature selection, immune-cell deconvolution, molecular docking, and molecular dynamics simulation. A total of 214 overlapping OTA-HCC-associated targets were identified and were enriched in pathways related to signal transduction, apoptosis, metabolism, and immune regulation. In GSE36376, 443 differentially expressed genes were identified using p < 0.05 and |log2 fold change| > 1, and overlap analysis yielded 13 shared target genes. Five candidate targets, CYP3A4, KIFC1, AKR1C3, CA2, and TTR, were further prioritized. KIFC1 and AKR1C3 were upregulated in HCC samples, whereas CYP3A4, CA2, and TTR were downregulated. These genes showed apparent discriminatory ability within the discovery dataset, with AUC values ranging from 0.866 to 0.958. Molecular docking predicted favorable OTA-target interactions, with docking energies ranging from -7.4 to -10.8 kcal/mol. CYP3A4 showed the lowest predicted docking energy (-10.8 kcal/mol) and was further evaluated by molecular dynamics simulation, with a protein-fitted OTA RMSD of 1.435 ± 0.097 nm and complex Rg of 2.308 ± 0.010 nm during the equilibrated 20-100 ns trajectory. Overall, this study provides a reproducible hypothesis-generating framework for exploring potential metabolic, genomic-instability-related, and immune-microenvironment links between OTA exposure and HCC. Future validation in independent datasets and experimental models will be important to further assess the biological relevance of these candidate targets and pathways. - Source: PubMed
Publication date: 2026/08/31
Yang ShiliLiu HuaiquanKou HaiyangLai LingyanZhang XinyanXu YunlingSun YuChen Bo - Triphala is a traditional three-fruit formulation with potential anticancer activity, but its ferroptosis-related mechanisms in oral cancer remain unclear. We integrated network pharmacology, transcriptomic analyses, prognostic modeling, Mendelian randomization, immune and drug-response analyses, molecular docking, and in vitro validation to investigate the Triphala-ferroptosis-oral cancer axis. Fifty-eight candidate functional genes were identified, and an eight-gene signature comprising AKR1C3, CA9, EGFR, GSTA1, MAPK8, MGST1, PPARG, and RB1 showed prognostic value across multiple cohorts. Mendelian randomization supported causal associations of MAPK8, MGST1, and PPARG with oral cancer risk. Seven Triphala-derived compounds, including epigallocatechin gallate, quercetin, kaempferol, luteolin, ellagic acid, gallic acid, and quinine, displayed favorable predicted interactions with key targets. In CAL-27 cells, Triphala altered the expression of signature genes, reduced GPX4 and SLC7A11 protein levels, increased Feand malondialdehyde, depleted glutathione and glutathione peroxidase activity, and enhanced lipid peroxidation; these effects were partially modulated by ferrostatin-1. This study advances the field by linking Triphala to a ferroptosis-based prognostic framework and experimentally demonstrating its regulation of the SLC7A11-GSH-GPX4 axis in oral cancer. - Source: PubMed
Zhao YiweiLi SiminJiang LinxinKreher DeborahSchmalz GerhardFichter AndreasHu Xianda