Akt1,2,3 monocl (clone 5C10)
- Known as:
- Akt1,2,3 monocl (clonality 5C10)
- Catalog number:
- ASA905-661
- Product Quantity:
- 100 µg
- Category:
- -
- Supplier:
- Other suppliers
- Gene target:
- Akt1 2 3 monocl (clone 5C10)
Related genes to: Akt1,2,3 monocl (clone 5C10)
- Gene:
- AKT1 NIH gene
- Name:
- AKT serine/threonine kinase 1
- Previous symbol:
- -
- Synonyms:
- RAC, PKB, PRKBA, AKT
- Chromosome:
- 14q32.33
- Locus Type:
- gene with protein product
- Date approved:
- 1986-01-01
- Date modifiied:
- 2019-04-23
Related products to: Akt1,2,3 monocl (clone 5C10)
Related articles to: Akt1,2,3 monocl (clone 5C10)
- Potassium (K) is an essential macronutrient for plant growth, yet Camellia oleifera is often cultivated in red soils severely deficient in available K. Such nutrient limitation has become a major constraint on its growth and productivity, while the physiological and molecular mechanisms underlying K deficiency responses in this woody species remain unclear. In this study, tissue-cultured seedlings of the C. oleifera cultivar 'Cenruan 3' were employed to examine growth and physiological traits under K deficiency and to elucidate the underlying transcriptional regulation. Potassium deprivation markedly reduced biomass accumulation, chlorophyll content, photosynthetic capacity, and primary root elongation. Root fresh and dry weights decreased, whereas root Ca and Mg concentrations increased. Stem lignification was accelerated, and reactive oxygen species (ROS) accumulated in leaves. Transcriptome analysis revealed activation of the Ca-dependent CBL-CIPK signaling module, which likely modulates K transport systems such as AKT1 and HAK5 to enhance K uptake and redistribution. Crosstalk among ROS, ethylene, and auxin signaling appears to contribute to adaptive adjustments of root architecture under ionic stress. Moreover, the phenylpropanoid pathway was significantly upregulated, together with increased expression of lignin biosynthesis-related genes, indicating enhanced structural reinforcement. Overall, C. oleifera adapts to K limitation through coordinated regulation of ion sensing, signal transduction, and metabolic and structural remodeling. A core Ca-CBL-CIPK regulatory network integrates K acquisition with hormonal and ROS signals. These findings improve our understanding of potassium utilization in woody plants and provide valuable references for developing C. oleifera cultivars with enhanced tolerance to low-K conditions. - Source: PubMed
Publication date: 2026/06/26
Yin RuoyongLu ShuaijieZhang BaojinTao JialuLiu XiaodiXi RuchunDeng Xiaomei - The increasing availability of large chemical libraries and bioactivity datasets has created a growing need for cheminformatics tools capable of extracting interpretable structure-activity relationship (SAR) information across structurally diverse chemical series. However, many existing approaches rely on rigid scaffold definitions, descriptor-based clustering, or manually curated groupings, often limiting the identification of SAR trends spanning partially overlapping chemotypes. Here, we present SARgate, an open-source cheminformatics platform designed to organize chemical libraries into structurally coherent subsets and facilitate multi-level SAR exploration within a unified graphical environment. Starting from Bemis-Murcko scaffolds, SARgate applies automated aggregation procedures to derive generalized cores based on minimal shared substructures, enabling flexible R-group decomposition and improved recognition of chemically related series. Developed in Python using RDKit as the core cheminformatics engine, SARgate integrates dataset curation, scaffold organization, R-group analysis, matched molecular pair analysis (MMPA), stereochemical evaluation, similarity assessment, and structure-activity landscape visualization into a single interactive workflow accessible to users with different levels of computational expertise. The utility of SARgate is demonstrated through representative case studies involving AKT1 and IL4I1 inhibitor datasets derived from public repositories, externally curated collections, and manually assembled patent-derived libraries. These applications show that SARgate can recover known SAR determinants, identify activity-driving substituents and stereochemical constraints, reveal context-dependent effects, and support mechanistically interpretable medicinal chemistry insights directly from large-scale bioactivity data. - Source: PubMed
Publication date: 2026/06/24
Labrano LucioPrimavera ErikaRocchi MarcoMassuoli MicheleRagni Maria GraziaPoletta LaraGargaro MarcoFallarino FrancescaManfroni GiuseppeBarreca Maria LetiziaAstolfi Andrea - AKT1 is a member of the AGC kinase family and represents a key therapeutic target in cancer. Although ATP-competitive compounds can act as potent inhibitors of AKT1, they may also exhibit off-target interactions with other kinases in the PI3K/AKT/mTOR pathway, a critical issue that requires systematic investigation. To address this challenge, we propose a computational framework that integrates a deep learning (DL) model with physics-based modeling approaches. Specifically, the developed DL model, CrossAtt-DTI, was first employed to perform binary classification and identify potential AKT1 binders. Subsequently, multiple molecular docking tools were used to predict binding conformations and identify poses that capture key binding residues. The stability of these docked conformations was then evaluated through all-atom molecular dynamics simulations in explicit solvent, followed by MM/PBSA calculations. The proposed framework was initially validated and subsequently applied to investigate the off-target interactions of ATP-competitive inhibitors with other kinases. The results indicate that, in addition to off-target interactions with members of the AGC kinase family predicted for most ATP-competitive inhibitors, Ipatasertib and NTQ1062 may exhibit strong interactions with PI3Kα, a member of the PI3K kinase family, while NTQ1062 may also interact with mTOR, a member of the PI3K-related kinase family. However, further and studies are required to validate these potential interactions. Overall, this work establishes a hybrid deep learning and physics-based computational framework for predicting the off-target effects of ATP-competitive AKT1 inhibitors and provides mechanistic insights into kinase cross-reactivity within the PI3K/AKT/mTOR signaling pathway. - Source: PubMed
Publication date: 2026/06/27
Huang JuanPan YuxueFan FangfangChen Qu - Radiation skin ulcer is a common adverse complication after radiotherapy. Currently, there is no efficient therapy for this complication. In this study, we searched for the potential pathological targets of radiation skin ulcer and the potential pharmacological targets of quercetin, respectively, and obtained the potential therapeutic targets after intersection. Subsequently, an array of bioinformatics assessments on possible therapeutic targets was conducted, encompassing functional enrichment studies, analysis of protein interaction networks, identification of key targets, and validation through molecular docking. The enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways shows that the therapeutic effect of quercetin on radiation skin ulcer may be through targeting aging cells. In addition, we identified 5 core targets, including AKT1, EGFR, MAPK3, SRC, and TP53. They are significantly enriched in EGFR tyrosine kinase inhibitors (SRC, AKT1, EGFR, and MAPK3) and epidermal growth factor receptor signaling pathways (SRC, EGFR, and AKT1), indicating the importance of EGFR signaling. Quercetin may have a therapeutic effect on radiation skin ulcer by targeting aging cells. Specifically, it may act through 4 core targets, including AKT1, EGFR, SRC, and TP53. - Source: PubMed
Liu GuoquanLi WeiWang HuanSu WenxingZou Jie - While studies suggested that Huangqi Guizhi Wuwu Decoction (HGWD) can mitigate doxorubicin-induced cardiotoxicity (DIC), the specific mechanism of action remains unclear. GSE106297, GSE157282, and GSE206803 were downloaded to screen for differentially expressed genes (DEGs), followed by gene set enrichment analysis and immune infiltration analysis. DIC-related genes were obtained by the intersection of weighted gene co-expression network analysis and DEGs. The active ingredients and target genes of HGWD were obtained from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform database, and HGWD-DIC common targets were identified by intersecting them with DIC-related genes. A drug-active ingredient-target network was constructed to select the core components of HGWD. Mitophagy-related genes were obtained from GeneCards, PHARMGKB, and OMIM databases, and intersecting them with common targets yielded the core genes, which were then subjected to enrichment analyses. A protein-protein interaction network was constructed to identify key genes, further assessing their diagnostic value. The effect of HGWD on the expression of key genes was further validated using prepared medicated serum. The interactions between the core components and key genes were validated through molecular docking and molecular dynamics simulation. A total of 2344 DEGs were identified, with gene set enrichment analysis results primarily enriched in categories such as apoptosis, p53 signaling pathway, cell cycle, PLK1 pathway, mitochondrial translation, and metabolism of RNA. Immune infiltration analysis suggested that the immune response may also be involved in the pathogenesis of DIC. We identified 2969 key modular genes by weighted gene co-expression network analysis, and intersecting these with DEGs yielded 1569 DIC-related genes. Network pharmacology analysis revealed 74 active ingredients and 692 target genes of HGWD, resulting in 64 common targets when intersected with DIC-related genes. The core components of HGWD were identified as quercetin and kaempferol. By intersecting the obtained mitophagy-related genes with common targets, 13 core genes were identified, with enrichment analyses indicating significant associations with cellular response to mitophagy and autophagy. Further analysis showed that 5 key genes: AKT1, TP53, BCL2L1, FASN, and HRAS, all demonstrated good diagnostic value, and their DOX-induced expression alterations were reversed by HGWD. Molecular docking and molecular dynamics simulation showed a strong binding affinity between the core components and key genes. HGWD may alleviate DIC by regulating mitophagy. - Source: PubMed
Yu JianWang JiangtaoLiu XinyaShi JingGao MengjiaoWu LiZhang Yuanming