N-Methyl-D-threonine

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N-Methyl-D-threonine
Category Others
Catalog number BBF-05242
CAS 2812-27-3
Molecular Weight 133.15
Molecular Formula C5H11NO3
Purity >95% by HPLC

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Specification

Related CAS 2812-28-4 (L-configuration) 95539-41-6 (DL-configuration)
Synonyms D-Threonine, N-Methyl-; N-methyl-D(S)-threonine; (2R,3S)-N-methylthreonine; Me-D-Thr-OH; methyl-D-threonine
Storage Store at -20°C
IUPAC Name (2R,3S)-3-hydroxy-2-(methylamino)butanoic acid
Canonical SMILES CC(C(C(=O)O)NC)O
InChI InChI=1S/C5H11NO3/c1-3(7)4(6-2)5(8)9/h3-4,6-7H,1-2H3,(H,8,9)/t3-,4+/m0/s1
InChI Key CCAIIPMIAFGKSI-IUYQGCFVSA-N

Properties

Boiling Point 301.5±32.0°C at 760 mmHg
Melting Point 251°C
Density 1.180 g/cm3

Reference Reading

1. Molecular basis for substrate recruitment to the PRMT5 methylosome
Kathleen M Mulvaney, Christa Blomquist, Nischal Acharya, et al. Mol Cell. 2021 Sep 2;81(17):3481-3495.e7. doi: 10.1016/j.molcel.2021.07.019. Epub 2021 Aug 5.
PRMT5 is an essential arginine methyltransferase and a therapeutic target in MTAP-null cancers. PRMT5 uses adaptor proteins for substrate recruitment through a previously undefined mechanism. Here, we identify an evolutionarily conserved peptide sequence shared among the three known substrate adaptors (CLNS1A, RIOK1, and COPR5) and show that it is necessary and sufficient for interaction with PRMT5. We demonstrate that PRMT5 uses modular adaptor proteins containing a common binding motif for substrate recruitment, comparable with other enzyme classes such as kinases and E3 ligases. We structurally resolve the interface with PRMT5 and show via genetic perturbation that it is required for methylation of adaptor-recruited substrates including the spliceosome, histones, and ribosomal complexes. Furthermore, disruption of this site affects Sm spliceosome activity, leading to intron retention. Genetic disruption of the PRMT5-substrate adaptor interface impairs growth of MTAP-null tumor cells and is thus a site for development of therapeutic inhibitors of PRMT5.
2. The protein arginine methyltransferase PRMT1 promotes TBK1 activation through asymmetric arginine methylation
Zhenzhen Yan, Haifeng Wu, Hansen Liu, Guimin Zhao, Honghai Zhang, Wanxin Zhuang, Feng Liu, Yi Zheng, Bingyu Liu, Lei Zhang, Chengjiang Gao Cell Rep. 2021 Sep 21;36(12):109731. doi: 10.1016/j.celrep.2021.109731.
TBK1 is an essential kinase for the innate immune response against viral infection. However, the key molecular mechanisms regulating the TBK1 activation remain elusive. Here, we identify PRMT1, a type I protein arginine methyltransferase, as an essential regulator of TBK1 activation. PRMT1 directly interacts with TBK1 and catalyzes asymmetric methylation of R54, R134, and R228 on TBK1. This modification enhances TBK1 oligomerization after viral infection, which subsequently promotes TBK1 phosphorylation and downstream type I interferon production. More important, myeloid-specific Prmt1 knockout mice are more susceptible to infection with DNA and RNA viruses than Prmt1fl/fl mice. Our findings reveal insights into the molecular regulation of TBK1 activation and demonstrate the essential function of protein arginine methylation in innate antiviral immunity.
3. Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival
Yong Li, Dandan Qi, Baoli Zhu, Xin Ye Int J Mol Sci. 2021 Feb 2;22(3):1474. doi: 10.3390/ijms22031474.
N6-methyladenosine (m6A) modification on RNA plays an important role in tumorigenesis and metastasis, which could change gene expression and even function at multiple levels such as RNA splicing, stability, translocation, and translation. In this study, we aim to conduct a comprehensive analysis on m6A RNA methylation-related genes, including m6A RNA methylation regulators and m6A RNA methylation-modified genes, in liver hepatocellular carcinoma, and their relationship with survival and clinical features. Data, which consist of the expression of widely reported m6A RNA methylation-related genes in liver hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), were analyzed by one-way ANOVA, Univariate Cox regression, a protein-protein interaction network, gene enrichment analysis, feature screening, a risk prognostic model, correlation analysis, and consensus clustering analysis. In total, 405 of the m6A RNA methylation-related genes were found based on one-way ANOVA. Among them, DNA topoisomerase 2-alpha (TOP2A), exodeoxyribonuclease 1 (EXO1), ser-ine/threonine-protein kinase Nek2 (NEK2), baculoviral IAP repeat-containing protein 5 (BIRC5), hyaluronan mediated motility receptor (HMMR), structural maintenance of chromosomes protein 4 (SMC4), bloom syndrome protein (BLM), ca-sein kinase I isoform epsilon (CSNK1E), cytoskeleton-associated protein 5 (CKAP5), and inner centromere protein (INCENP), which were m6A RNA methylation-modified genes, were recognized as the hub genes based on the protein-protein interaction analysis. The risk prognostic model showed that gender, AJCC stage, grade, T, and N were significantly different between the subgroup with the high and low risk groups. The AUC, the evaluation parameter of the prediction model which was built by RandomForest, was 0.7. Furthermore, two subgroups were divided by consensus clustering analysis, in which stage, grade, and T differed. We identified the important genes expressed significantly among two clusters, including uridine-cytidine kinase 2 (UCK2), filensin (BFSP1), tubulin-specific chaperone D (TBCD), histone-lysine N-methyltransferase PRDM16 (PRDM16), phosphorylase b ki-nase regulatory subunit alpha (PHKA2), serine/threonine-protein kinase BRSK2 (BRSK2), Arf-GAP with coiled-coil (ACAP3), general transcription factor 3C polypep-tide 2 (GTF3C2), and guanine nucleotide exchange factor MSS4 (RABIF). In our study, the m6A RNA methylation-related genes in liver hepatocellular carcinoma were analyzed systematically, including the expression, interaction, function, and prognostic values, which provided an important theoretical basis for m6A RNA methylation in liver cancer. The nine important m6A-related genes could be prognostic markers in the survival time of patients.

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