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- MCE
- HY-L070
- 2026年03月25日
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- 详细信息
- 文献和实验
- 技术资料
- 库存：
【化合物数量】1553
- 供应商：
广州市左克生物
神经退行性疾病是以神经元进行性功能障碍和死亡为特征的一种疾病，如阿尔茨海默病、帕金森病和多发性硬化症 (MS) 等。神经保护是在神经退行性疾病中保护神经元使其不受不同病理因素损伤的一种方法。常用的神经保护剂通常为一些靶向神经保护通路中关键靶点的阻断剂和激动剂，如钙离子通道或钠离子通道阻断剂，GABA 受体激动剂，NMDA 受体拮抗剂等。虽然目前神经保护剂不能逆转已有的损伤，但它们可以防止进一步的神经损伤，减缓中枢神经系统的退化，在神经退行性疾病的治疗中仍然发挥重要作用。 MCE 收录了 [0] 种具有潜在神经保护作用的化合物，这些化合物主要靶向神经保护通路中的主要靶点，如钙离子通道，钠离子通道，腺苷 A1 受体等。MCE 神经保护化合物库是开发神经保护药物，研究神经保护机制的有效工具。
活性描述 & 特点
Biological Activity
• A unique collection of 1,648 compounds for high throughput screening (HTS) and high content screening (HCS).
• Targets include calcium channel, sodium channel, adenosine A1 receptor, PI3K, etc.
• A useful tool for exploring the mechanism of neuroprotection and discovery new drugs for neurodegenerative diseases.
• Bioactivity and safety confirmed by preclinical research and clinical trials. Some have been approved by FDA.
• Structurally diverse, medicinally active, and cell permeable.
• Detailed compound information with structure, IC50, and brief introduction.
• Validated NMR and HPLC to ensure high purity and quality.
• All compounds are in stock and continuously updated.
产品详情
Product Details
Formulation:
A collection of 1,648 neuroprotective compounds supplied as pre-dissolved Solutions or Solid
Solution: 1,602 compounds supplied in 10 mM solution, 40 compounds supplied in 2 mM solution, 6 compounds supplied in 3 mg/mL solution.
Layout:
96-well storage tube or 96-well plate: 1st and 12th column are left empty.
384-well plate: the first two columns and the last two columns are left empty.
Compounds with different concentrations or dissolved in different solvents will be put on separate plates. This way of layout may increase the number of plates because there could be three solvents and three concentrations.
If you have other requirements, please let us know.
Container:
96- or 384-well Plate with Peelable Foil Seal; 96-well Format Sample Storage Tube With Screw Cap and Optional 2D Barcode
Storage:
-80°C
Shipping:
Blue ice or dry ice
化合物库组成
Composition
Apoptosis(265)
Calcium Channel(216)
Sodium Channel(184)
NO Synthase(169)
Wnt(159)
iGluR(144)
Potassium Channel(128)
NF-κB(126)
Endogenous Metabolite(120)
Akt(115)
Reactive Oxygen Species (ROS)(113)
ERK(101)
β-catenin(97)
Autophagy(89)
GABA Receptor(88)
Bacterial(83)
COX(74)
mGluR(71)
Interleukin Related(68)
p38 MAPK(68)
PI3K(56)
Caspase(51)
TNF Receptor(46)
JNK(42)
Parasite(39)
Amyloid-β(36)
Keap1-Nrf2(31)
GSK-3(29)
Antibiotic(28)
Sigma Receptor(28)
Cholinesterase (ChE)(27)
Cytochrome P450(27)
PARP(23)
Ferroptosis(22)
Monoamine Oxidase(22)
STAT(22)
5-HT Receptor(21)
Histamine Receptor(21)
mAChR(21)
PPAR(21)
Toll-like Receptor (TLR)(21)
CDK(20)
Phosphodiesterase (PDE)(20)
Adrenergic Receptor(19)
Fungal(19)
mTOR(18)
TRP Channel(18)
Dopamine Receptor(17)
Adenosine Receptor(16)
AMPK(16)
Bcl-2 Family(16)
MMP(16)
HIV(15)
P-glycoprotein(15)
TGF-beta/Smad(15)
HIF/HIF Prolyl-Hydroxylase(14)
Influenza Virus(14)
DNA/RNA Synthesis(13)
NOD-like Receptor (NLR)(13)
SOD(12)
Heme Oxygenase (HO)(11)
IKK(11)
MEK(11)
PKC(11)
Drug Metabolite(10)
MDM-2/p53(10)
Mitochondrial Metabolism(10)
PKA(10)
SARS-CoV(10)
Glucocorticoid Receptor(9)
PERK(9)
Prostaglandin Receptor(9)
Sirtuin(9)
Estrogen Receptor/ERR(8)
JAK(8)
nAChR(8)
Opioid Receptor(8)
Pyroptosis(8)
Serotonin Transporter(8)
Angiotensin Receptor(7)
Casein Kinase(7)
Chloride Channel(7)
HSV(7)
LPL Receptor(7)
Phosphatase(7)
Trk Receptor(7)
Tyrosinase(7)
Virus Protease(7)
AP-1(6)
EGFR(6)
Glutathione Peroxidase(6)
Glycosidase(6)
Lipoxygenase(6)
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文献和实验with this topic (1,2), but an update seemed necessary due to the rapid evolution of this field. The scope of this chapter is the management of different types of compound collec-tions from both physical and electronic points of view, including some aspects
Informatics in Compound Library Management
for compound library management, these systems do not come cheaply. Without doubt, for large pharma the return on investment for one of these systems can be justified; however, the upfront cost is typically prohibitive for smaller businesses looking to stretch
Compound Library Design for Target Families
and the extremely high-cost procedure jointly force the scientist to use additional computational tools for rational compound library design and selection. The present chapter will focus specifically on application of a predictive mapping computational technology
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