Ask about this productRelated genes to: PYCRL antibody
- Gene:
- PYCR3 NIH gene
- Name:
- pyrroline-5-carboxylate reductase 3
- Previous symbol:
- PYCRL
- Synonyms:
- FLJ13852
- Chromosome:
- 8q24.3
- Locus Type:
- gene with protein product
- Date approved:
- 2004-03-19
- Date modifiied:
- 2017-03-22
Related products to: PYCRL antibody
Related articles to: PYCRL antibody
- Proline metabolism is selectively altered in cancer cells, providing ATP, redox balance, and proline for cell growth. The final enzyme of proline biosynthesis is Δ-pyrroline-5-carboxylate (P5C) reductase (PYCR), which catalyzes the NAD(P)H-dependent reduction of P5C to proline. Humans have three PYCR isoforms, PYCR1 and PYCR2 in the mitochondrion and PYCR3 in the cytosol. Interest in developing selective inhibitors of PYCR enzymes has significantly increased over the past decade. Orthosteric inhibitors of PYCR1 have been developed, but they may lack specificity given the near identity of the active sites of PYCR1 and PYCR2. Here, we explored a new strategy of targeting noncatalytic cysteines to gain isoform selectivity. Initial results with iodoacetamide showed higher inhibition of PYCR2 relative to PYCR1, a result that was further explored with the thiol-reactive compound ebselen. Ebselen treatment resulted in a complete loss of PYCR2 activity with an IC value of 22 nM, which is 10-fold more sensitive than with PYCR1. Results from protection assays with dithiothreitol, site-directed mutagenesis, and mass spectrometry implicate Cys232 in PYCR2 as the target of ebselen. A new crystal structure of PYCR2 shows that Cys232 is in the P5C-binding loop, whereas PYCR1 contains a serine at this position. Our study provides new insight into the structural and functional roles of unique cysteine residues in PYCR2. Further, our results demonstrate proof-of-concept for targeting a noncatalytic cysteine as a new approach for selectively inhibiting PYCR2 over PYCR1. - Source: PubMed
Publication date: 2026/04/21
Rossman Tyrell CMeeks Kaylen RPurohit GunjanNaldrett Michael JTanner John JBecker Donald F - Vitrification is a rapid-cooling cryopreservation technique for oocytes and a key method in assisted reproductive technology (ART). During vitrification, oocytes are exposed to high concentrations of cryoprotectants, leading to cryoinjury and osmotic stress that impair oocyte quality and subsequent developmental competence in mammals. However, the complex molecular stress responses evoked by vitrification remain poorly understood. - Source: PubMed
Publication date: 2025/12/16
Dilixiati AirixiatiZhao XiAihemaiti AikebaierLi WeijianFan ChenZhao GuodongWusiman AbuliziWang Xuguang - Changes in gene expression underlie most phenotypic differences among closely related species. While previous studies in model systems have identified conserved genes and pathways involved in craniofacial evolution, less is known about gene expression differences associated with craniofacial divergence in rapidly evolving species. Here, we investigate craniofacial-specific gene expression in a nascent adaptive radiation of Cyprinodon pupfishes endemic to San Salvador Island, Bahamas, which includes 3 trophic specialists with highly divergent craniofacial morphologies (two scale-eaters and a molluscivore) derived from an ancestral Caribbean-wide generalist. We compared gene expression in the most morphologically divergent craniofacial region with the relatively conserved caudal region across 5 Cyprinodon species and 9 populations. We focused on the hatchling stage, the earliest developmental stage at which craniofacial differences among species are evident. Our approach revealed a large proportion of differentially expressed genes (DEGs) found exclusively in the craniofacial region of the specialists only. By intersecting these specialist-specific craniofacial-exclusive genes with genomic regions harboring fixed single-nucleotide variants under selection in the specialists, we identified 14 candidate genes. We confirmed novel craniofacial expression for 2 of these candidates, pycr3 and atp8a1, genes not previously associated with craniofacial development or function, in hatchlings using in situ mRNA hybridization and observed species-specific differences in the pharyngeal arches and craniofacial muscles, respectively. Our findings demonstrate how an "evolutionary mutant" model can reveal novel gene expression patterns, highlighting the power of integrating tissue-species transcriptomics with speciation genomics to identify novel regulators of craniofacial evolution. - Source: PubMed
Palominos M FernandaMuhl VanessaMartin Christopher H - The human genome has a profound impact on human health and disease detection. Carcinoma (cancer) is one of the prominent diseases that majorly affect human health and requires the development of different treatment strategies and targeted therapies based on effective disease detection. Therefore, our research aims to identify biomarkers associated with distinct cancer types (gastric, lung, and breast) using machine learning. In the current study, we have analyzed the human genomic data of gastric cancer, breast cancer, and lung cancer patients using XGB-BIF (i.e., XGBoost-Driven Biomarker Identification Framework for detecting cancer). The proposed framework utilizes feature selection via XGBoost (eXtreme Gradient Boosting), which captures feature interactions efficiently and takes care of the non-linear effects in the genomic data. The research progressed by training XGBoost on the full dataset, ranking the features based on the Gain measure (importance), followed by the classification phase, which employed support vector machines (SVM), logistic regression (LR), and random forest (RF) models for classifying cancer-diseased and non-diseased states. To ensure interpretability and transparency, we also applied SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), enabling the identification of high-impact biomarkers contributing to risk stratification. Biomarker significance is discussed primarily via pathway enrichment and by studying survival analysis (Kaplan-Meier curves, Cox regression) for identified biomarkers to strengthen translational value. Our models achieved high predictive performance, with an accuracy of more than 90%, to classify and link genomic data into diseased (cancer) and non-diseased states. Furthermore, we evaluated the models using Cohen's Kappa statistic, which confirmed strong agreement between predicted and actual risk categories, with Kappa scores ranging from 0.80 to 0.99. Our proposed framework also achieved strong predictions on the METABRIC dataset during external validation, attaining an AUC-ROC of 93%, accuracy of 0.79%, and Kappa of 74%. Through extensive experimentation, XGB-BIF identified the top biomarker genes for different cancer datasets (gastric, lung, and breast). , , , , , , , and were identified as important biomarkers to identify diseased and non-diseased states of gastric cancer; , , , , and were identified as important biomarkers for breast cancer; and , , , , , and were identified as important biomarkers for lung cancer. XGB-BIF could be utilized for identifying biomarkers of different cancer types using genetic data, which can further help clinicians in developing targeted therapies for cancer patients. - Source: PubMed
Publication date: 2025/06/11
Ghuriani VeenaWassan Jyotsna TalrejaTripathi PriyalChauhan Anshika - The study aimed to explore the role of metabolism-related proteins and their correlation with clinical data in predicting the prognosis of polycystic ovary syndrome (PCOS). - Source: PubMed
Publication date: 2024/12/19
Ding NanWang RuifangWang PeiliWang Fang