CBDB
(Synonyms: Cannabidibutol, Cannabidiol-C4, CBD-C4) 目录号 : GC46115An Analytical Reference Standard
Cas No.:60113-11-3
Sample solution is provided at 25 µL, 10mM.
;)
,-1-7$$$37316672.jpg');)
;)
;)
$$$36806353.jpg');)
;33(7)%EF%BC%9A546-561$$$37156877.jpg');)
;)
;)
;)
%201124-1138.$$$35908550.jpg');)
%20766-780.$$$37100057.jpg');)
%20418-432.$$$36893736.jpg');)
%EF%BC%9A-240-255.$$$35108512.jpg');)
533-545$$$36543525.jpg');)
%201-13.$$$36600053.jpg');)
;)
Quality Control & SDS
- View current batch:
- Purity: >98.00%
- COA (Certificate Of Analysis)
- SDS (Safety Data Sheet)
- Datasheet
CBDB is an analytical reference standard categorized as a phytocannabinoid.1 CBDB has been found in strains of cannabis and hemp.1,2 CBDB is considered an impurity in commercial extractions of cannabidiol (CBD) from hemp.2 This product is intended for research and forensic applications.This item has been tested to contain ≤0.3% δ9-THC on a dry weight basis meeting the 2018 Farm Bill requirements to be a non-controlled substance in the US.
|1. Linciano, P., Citti, C., Luongo, L., et al. Isolation of a high-affinity cannabinoid for the human CB1 receptor from a medicinal Cannabis sativa variety: D9-Tetrahydrocannabutol, the butyl homologue of D9-tetrahydrocannabinol. J. Nat. Med. (2019).|2. Citti, C., Linciano, P., Forni, F., et al. Analysis of impurities of cannabidiol from hemp. Isolation, characterization and synthesis of cannabidibutol, the novel cannabidiol butyl analog. J. Pharm. Biomed. Anal. 175, 112752 (2019).
| Cas No. | 60113-11-3 | SDF | |
| 别名 | Cannabidibutol, Cannabidiol-C4, CBD-C4 | ||
| Canonical SMILES | CC1=C[C@@H](C2=C(O)C=C(CCCC)C=C2O)[C@H](C(C)=C)CC1 | ||
| 分子式 | C20H28O2 | 分子量 | 300.4 |
| 溶解度 | DMF: 50 mg/ml,DMSO: 60 mg/ml,DMSO:PBS (pH 7.2) (1:3): 0.25 mg/ml,Ethanol: 35 mg/ml | 储存条件 | Store at -20°C |
| General tips | 请根据产品在不同溶剂中的溶解度选择合适的溶剂配制储备液；一旦配成溶液，请分装保存，避免反复冻融造成的产品失效。 储备液的保存方式和期限：-80°C 储存时，请在 6 个月内使用，-20°C 储存时，请在 1 个月内使用。 为了提高溶解度，请将管子加热至37℃，然后在超声波浴中震荡一段时间。 |
||
| Shipping Condition | 评估样品解决方案：配备蓝冰进行发货。所有其他可用尺寸：配备RT，或根据请求配备蓝冰。 | ||
| 制备储备液 | |||
 |
1 mg | 5 mg | 10 mg |
| 1 mM | 3.3289 mL | 16.6445 mL | 33.2889 mL |
| 5 mM | 0.6658 mL | 3.3289 mL | 6.6578 mL |
| 10 mM | 0.3329 mL | 1.6644 mL | 3.3289 mL |
| 第一步：请输入基本实验信息（考虑到实验过程中的损耗，建议多配一只动物的药量） | ||||||||||
| 给药剂量 | mg/kg |  |
动物平均体重 | g | |
每只动物给药体积 | ul | |
动物数量 | 只 |
| 第二步：请输入动物体内配方组成（配方适用于不溶于水的药物；不同批次药物配方比例不同，请联系GLPBIO为您提供正确的澄清溶液配方） | ||||||||||
| % DMSO % % Tween 80 % saline | ||||||||||
| 计算重置 | ||||||||||
计算结果:
工作液浓度： mg/ml；
DMSO母液配制方法： mg 药物溶于 μL DMSO溶液（母液浓度 mg/mL，
体内配方配制方法：取 μL DMSO母液，加入 μL PEG300，混匀澄清后加入μL Tween 80，混匀澄清后加入 μL saline，混匀澄清。
1. 首先保证母液是澄清的；
2.
一定要按照顺序依次将溶剂加入，进行下一步操作之前必须保证上一步操作得到的是澄清的溶液，可采用涡旋、超声或水浴加热等物理方法助溶。
3. 以上所有助溶剂都可在 GlpBio 网站选购。
CBDB: the codon bias database
BMC Bioinformatics 2012 Apr 26;13:62.PMID:22536831DOI:10.1186/1471-2105-13-62.
Background: In many genomes, a clear preference in the usage of particular codons exists. The mechanisms that induce codon biases remain an open question; studies have attributed codon usage to translational selection, mutational bias and drift. Furthermore, correlations between codon usage within host genomes and their viral pathogens have been observed for a myriad of host-virus systems. As such, numerous studies have investigated codon usage and codon bias in an effort to better understand how species evolve. Numerous metrics have been developed to identify biases in codon usage. In addition, a few data repositories of codon bias data are available, differing in the metrics reported as well as the number and taxonomy of strains examined. Description: We have created a new web resource called the Codon Bias Database (CBDB) which provides information regarding the codon bias within the set of highly expressed genes for 300+ bacterial genomes. CBDB was developed to provide a resource for researchers investigating codon bias in bacteria, facilitating comparisons between strains and species. Furthermore, the site was created to serve those studying adaptation in phage; the genera selected for this first release of CBDB all have sequenced, annotated bacteriophages. The annotations and sequences for the highly expressed gene set are available for each strain in addition to the strain's codon bias measurements. Conclusions: Comparing species and strains provides a comprehensive look at how codon usage has been shaped over evolutionary time and can elucidate the putative mechanisms behind it. The Codon Bias Database provides a centralized repository of look-up tables and codon usage bias measures for a wide variety of genera, species and strains. Through our analysis of the variation in codon usage within the strains presently available, we find that most members of a genus have a codon composition most similar to other members of its genus, although not necessarily other members of its species.
Oxidative Stress and Multi-Organel Damage Induced by Two Novel Phytocannabinoids, CBDB and CBDP, in Breast Cancer Cells
Molecules 2021 Sep 14;26(18):5576.PMID:34577048DOI:10.3390/molecules26185576.
Over the last few years, much attention has been paid to phytocannabinoids derived from Cannabis for their therapeutic potential. Δ9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD) are the most abundant compounds of the Cannabis sativa L. plant. Recently, novel phytocannabinoids, such as cannabidibutol (CBDB) and cannabidiphorol (CBDP), have been discovered. These new molecules exhibit the same terpenophenolic core of CBD and differ only for the length of the alkyl side chain. Roles of CBD homologs in physiological and pathological processes are emerging but the exact molecular mechanisms remain to be fully elucidated. Here, we investigated the biological effects of the newly discovered CBDB or CBDP, compared to the well-known natural and synthetic CBD (nat CBD and syn CBD) in human breast carcinoma cells that express CB receptors. In detail, our data demonstrated that the treatment of cells with the novel phytocannabinoids affects cell viability, increases the production of reactive oxygen species (ROS) and activates cellular pathways related to ROS signaling, as already demonstrated for natural CBD. Moreover, we observed that the biological activity is significantly increased upon combining CBD homologs with drugs that inhibit the activity of enzymes involved in the metabolism of endocannabinoids, such as the monoacylglycerol lipase (MAGL) inhibitor, or with drugs that induces the activation of cellular stress pathways, such as the phorbol ester 12-myristate 13-acetate (PMA).
Chemical and spectroscopic characterization data of 'cannabidibutol', a novel cannabidiol butyl analog
Data Brief 2019 Sep 5;26:104463.PMID:31667233DOI:10.1016/j.dib.2019.104463.
Cannabidibutol (CBDB), a novel butyl analog of cannabidiol, was identified as impurity of commercial cannabidiol (CBD) extracted from hemp (for full data and results interpretation see "Analysis of impurities of cannabidiol from hemp. Isolation, characterization and synthesis of cannabidibutol, the novel cannabidiol butyl analog" Citti et al, 2019). The compound was isolated from a CBD sample and subject to a full characterization. First, a complete spectroscopic characterization was performed by Nuclear Magnetic Resonance (NMR): in particular, 1H-NMR, 13C-NMR, COSY, HSQC and HMBC, which were followed by UV absorption and circular dichroism (CD) spectra. In order to confirm the structural identity and stereochemistry of the compound, a stereoselective synthesis of the trans isomer (1R,6R) was carried out and all the chemical and spectroscopic properties were analyzed. The synthesized compound was characterized by NMR (1H-NMR, 13C-NMR, COSY, HSQC and HMBC), Infra-Red spectroscopy (IR), UV and CD absorption, matching the results obtained for the natural isolated compound. With the analytical standard in hand, a simple high-performance liquid chromatography method coupled to UV detection (HPLC-UV) was developed and validated in house in terms of linearity, accuracy, precision, dilution integrity and stability. The present data might be useful to any researcher or industry that may run into a very common impurity of CBD extracted from hemp, so it can be easily compared with their own experimental data.
Modification of cyanobacterial bloom-derived biomass using potassium permanganate enhanced the removal of microcystins and adsorption capacity toward cadmium (II)
J Hazard Mater 2014 May 15;272:83-8.PMID:24681589DOI:10.1016/j.jhazmat.2014.03.013.
Cyanobacterial biomass shows high adsorption capacity toward heavy metal ions. However, the cyanotoxins in the cyanobacterial biomass inhibit its application in heavy metals removal. In order to safely and effectively remove Cd(II) from water using cyanobacterial bloom-derived biomass (CBDB), KMnO4 was used to modify CBDB. The results indicated that the microcystins in the CBDB were successfully removed by KMnO4. Potassium permanganate oxidation caused the transformation of hydroxyl to carboxyl on the CBDB, and formed manganese dioxide on the surface of CBDB. The oxidized CBDB showed higher adsorption capacity toward Cd(II) than that of unoxidized treatment. The optimal KMnO4 concentration for increasing the adsorption capacity of CBDB toward Cd(II) was 0.2g/L. The adsorption isotherm of Cd(II) by oxidized- or unoxidized-CBDB was well fitted by Langmuir model, indicating that the adsorption of Cd(II) by CBDB was monolayer adsorption. The desorption ratio of Cd(II) from oxidized CBDB was higher than that from unoxidized CBDB in the desorption process using NH4NO3 and EDTA as desorbent. The results presented in this study suggest that KMnO4 modified CBDB may be used as a safe and high efficient adsorbent in Cd(II) removal from water.
The Dynamic Codon Biaser: calculating prokaryotic codon usage biases
Microb Genom 2021 Oct;7(10):000663.PMID:34699346DOI:10.1099/mgen.0.000663.
Bacterial genomes often reflect a bias in the usage of codons. These biases are often most notable within highly expressed genes. While deviations in codon usage can be attributed to selection or mutational biases, they can also be functional, for example controlling gene expression or guiding protein structure. Several different metrics have been developed to identify biases in codon usage. Previously we released a database, CBDB: The Codon Bias Database, in which users could retrieve precalculated codon bias data for bacterial RefSeq genomes. With the increase of bacterial genome sequence data since its release a new tool was needed. Here we present the Dynamic Codon Biaser (DCB) tool, a web application that dynamically calculates the codon usage bias statistics of prokaryotic genomes. DCB bases these calculations on 40 different highly expressed genes (HEGs) that are highly conserved across different prokaryotic species. A user can either specify an NCBI accession number or upload their own sequence. DCB returns both the bias statistics and the genome's HEG sequences. These calculations have several downstream applications, such as evolutionary studies and phage-host predictions. The source code is freely available, and the website is hosted at www.CBDB.info.