Ganoderic acid C2
(Synonyms: 灵芝酸C2) 目录号 : GC36117
A triterpene
Cas No.:103773-62-2
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: >99.00%
- COA (Certificate Of Analysis)
- SDS (Safety Data Sheet)
- Datasheet
Ganoderic acid C2 is a triterpene that has been found in G. lucidum.1 It inhibits histamine release from isolated rat mast cells induced by concanavalin A or compound 48/80 when used at a concentration of 2 mg/ml.
1.Kohda, H., Tokumoto, W., Sakamoto, K., et al.The biologically active constituents of Ganoderma lucidum (Fr.) Karst. histamine release-inhibitory triterpenesChem. Pharm. Bull.33(4)1367-1374(1985)
| Cas No. | 103773-62-2 | SDF | |
| 别名 | 灵芝酸C2 | ||
| Canonical SMILES | CC1(C)[C@@H](O)CC[C@]2(C)C3=C([C@@]4([C@@H](O)C[C@@H]([C@]4(CC3=O)C)[C@H](C)CC(C[C@@H](C)C(O)=O)=O)C)[C@@H](O)C[C@@]12[H] | ||
| 分子式 | C30H46O7 | 分子量 | 518.68 |
| 溶解度 | Methanol: soluble | 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 | 1.928 mL | 9.6399 mL | 19.2797 mL |
| 5 mM | 0.3856 mL | 1.928 mL | 3.8559 mL |
| 10 mM | 0.1928 mL | 0.964 mL | 1.928 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。
Structural characterization of minor metabolites and pharmacokinetics of Ganoderic acid C2 in rat plasma by HPLC coupled with electrospray ionization tandem mass spectrometry
J Pharm Biomed Anal 2013 Mar 5;75:64-73.PMID:23312386DOI:10.1016/j.jpba.2012.11.024.
The metabolites and pharmacokinetics of Ganoderic acid C2 (GAC2), a bioactive triterpenoid in Ganoderma lucidum in rat plasma were investigated by high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Totally, ten minor phase I metabolites of GAC2 were characterized after oral administration of GAC2, on the basis of their mass fragmentation pathways or direct comparison with authentic compounds by high-performance liquid chromatography coupled with diode array detection and electrospray ion trap tandem mass spectrometry (HPLC-DAD-ESI-MS(n)), and liquid chromatography coupled with electrospray ionization hybrid ion trap and time-of-flight mass spectrometry (LC-ESI-IT-TOF/MS) methods. Moreover, a rapid and specific method for quantification of GAC2 in rat plasma after oral administration was developed by using a liquid-liquid extraction procedure and HPLC-ESI-MS/MS analysis. It is the first time to report the metabolites and pharmacokinetics of GAC2.
Triterpenes from the spores of Ganoderma lucidum and their cytotoxicity against meth-A and LLC tumor cells
Chem Pharm Bull (Tokyo) 2000 Jul;48(7):1026-33.PMID:10923835DOI:10.1248/cpb.48.1026.
Six new highly oxygenated lanostane-type triterpenes, called ganoderic acid gamma (1), ganoderic acid delta (2), ganoderic acid epsilon (3), ganoderic acid zeta (4), ganoderic acid eta (5) and ganoderic acid theta (6), were isolated from the spores of Ganoderma lucidum, together with known ganolucidic acid D (7) and Ganoderic acid C2 (8). Their structures of the new triterpenes were determined as (23S)-7beta,15alpha,23-trihydroxy-3,11-dioxolanosta-8, 24(E)-diene-26-oic acid (1), (23S)-7alpha,15alpha23-trihydroxy-3,11-dioxolanosta-8, 24(E)-diene-26-oic acid (2), (23S)-3beta3,7beta, 23-trihydroxy-11,15-dioxolanosta-8,24(E)-diene-26-oic acid (3), (23S)-3beta,23-dihydroxy-7,11,15-trioxolanosta-8, 24(E)-diene-26-oic acid (4), (23S)-3beta,7beta,12beta,23-tetrahydroxy-11,15-dioxolanos ta-8,24(E)-diene-26-oic acid (5) and (23S)-3beta,12beta23-trihydroxy-7,11,15-trioxolanosta-8,24(E )-diene-26-oic acid (6), respectively, by chemical and spectroscopic means, which included the determination of a chiral center in the side chain by a modification of Mosher's method. The cytotoxicity of the compounds isolated from the Ganoderma spores was carried out in vitro against Meth-A and LLC tumor cell lines.
Network pharmacology analysis of the anti-cancer pharmacological mechanisms of Ganoderma lucidum extract with experimental support using Hepa1-6-bearing C57 BL/6 mice
J Ethnopharmacol 2018 Jan 10;210:287-295.PMID:28882624DOI:10.1016/j.jep.2017.08.041.
Ethnopharmacological relevance: Ganoderma lucidum (GL) is an oriental medical fungus, which was used to prevent and treat many diseases. Previously, the effective compounds of Ganoderma lucidum extract (GLE) were extracted from two kinds of GL, [Ganoderma lucidum (Leyss. Ex Fr.) Karst.] and [Ganoderma sinense Zhao, Xu et Zhang], which have been used for adjuvant anti-cancer clinical therapy for more than 20 years. However, its concrete active compounds and its regulation mechanisms on tumor are unclear. Aim of the study: In this study, we aimed to identify the main active compounds from GLE and to investigate its anti-cancer mechanisms via drug-target biological network construction and prediction. Materials and methods: The main active compounds of GLE were identified by HPLC, EI-MS and NMR, and the compounds related targets were predicted using docking program. To investigate the functions of GL holistically, the active compounds of GL and related targets were predicted based on four public databases. Subsequently, the Identified-Compound-Target network and Predicted-Compound-Target network were constructed respectively, and they were overlapped to detect the hub potential targets in both networks. Furthermore, the qRT-PCR and western-blot assays were used to validate the expression levels of target genes in GLE treated Hepa1-6-bearing C57 BL/6 mice. Results: In our work, 12 active compounds of GLE were identified, including Ganoderic acid A, Ganoderenic acid A, Ganoderic acid B, Ganoderic acid H, Ganoderic acid C2, Ganoderenic acid D, Ganoderic acid D, Ganoderenic acid G, Ganoderic acid Y, Kaemferol, Genistein and Ergosterol. Using the docking program, 20 targets were mapped to 12 compounds of GLE. Furthermore, 122 effective active compounds of GL and 116 targets were holistically predicted using public databases. Compare with the Identified-Compound-Target network and Predicted-Compound-Target network, 6 hub targets were screened, including AR, CHRM2, ESR1, NR3C1, NR3C2 and PGR, which was considered as potential markers and might play important roles in the process of GLE treatment. GLE effectively inhibited tumor growth in Hepa1-6-bearing C57 BL/6 mice. Finally, consistent with the results of qRT-PCR data, the results of western-blot assay demonstrated the expression levels of PGR and ESR1 were up-regulated, as well as the expression levels of NR3C2 and AR were down-regulated, while the change of NR3C1 and CHRM2 had no statistical significance. Conclusions: The results indicated that these 4 hub target genes, including NR3C2, AR, ESR1 and PGR, might act as potential markers to evaluate the curative effect of GLE treatment in tumor. And, the combined data provide preliminary study of the pharmacological mechanisms of GLE, which may be a promising potential therapeutic and chemopreventative candidate for anti-cancer.
Inhibition of aldose reductase in vitro by constituents of Ganoderma lucidum
Planta Med 2010 Oct;76(15):1691-3.PMID:20379959DOI:10.1055/s-0030-1249782.
CHCl(3) extract of the fruiting body of Ganoderma lucidum was found to show inhibitory activity on human aldose reductase in vitro. From the acidic fraction, potent human aldose reductase inhibitors, Ganoderic acid C2 (1) and ganoderenic acid A (2), were isolated together with three related compounds. It was found that the free carboxyl group of Ganoderic acid C2 and ganoderenic acid A is essential in eliciting the inhibitory activity considering the much lower activity of their methyl esters.
Metabolomic Selection in the Progression of Type 2 Diabetes Mellitus: A Genetic Algorithm Approach
Diagnostics (Basel) 2022 Nov 15;12(11):2803.PMID:36428864DOI:10.3390/diagnostics12112803.
According to the World Health Organization (WHO), type 2 diabetes mellitus (T2DM) is a result of the inefficient use of insulin by the body. More than 95% of people with diabetes have T2DM, which is largely due to excess weight and physical inactivity. This study proposes an intelligent feature selection of metabolites related to different stages of diabetes, with the use of genetic algorithms (GA) and the implementation of support vector machines (SVMs), K-Nearest Neighbors (KNNs) and Nearest Centroid (NEARCENT) and with a dataset obtained from the Instituto Mexicano del Seguro Social with the protocol name of the following: "Análisis metabolómico y transcriptómico diferencial en orina y suero de pacientes pre diabéticos, diabéticos y con nefropatía diabética para identificar potenciales biomarcadores pronósticos de daño renal" (differential metabolomic and transcriptomic analyses in the urine and serum of pre-diabetic, diabetic and diabetic nephropathy patients to identify potential prognostic biomarkers of kidney damage). In order to analyze which machine learning (ML) model is the most optimal for classifying patients with some stage of T2DM, the novelty of this work is to provide a genetic algorithm approach that detects significant metabolites in each stage of progression. More than 100 metabolites were identified as significant between all stages; with the data analyzed, the average accuracies obtained in each of the five most-accurate implementations of genetic algorithms were in the range of 0.8214-0.9893 with respect to average accuracy, providing a precise tool to use in detections and backing up a diagnosis constructed entirely with metabolomics. By providing five potential biomarkers for progression, these extremely significant metabolites are as follows: "Cer(d18:1/24:1) i2", "PC(20:3-OH/P-18:1)", "Ganoderic acid C2", "TG(16:0/17:1/18:1)" and "GPEtn(18:0/20:4)".