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重要文件

QBD10903

Sigma-Aldrich

Fmoc-N-amido-dPEG®36-acid

>95% (HPLC)

同義詞:

Fmoc-N-amido-PEG36-acid, Fmoc-NH-PEG36-acid, Fmoc-PEG-acid, Fmoc-PEG1500-acid, Fmoc-PEG36-acid

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About This Item

經驗公式(希爾表示法):
C90H161NO40
分子量::
1897.22
MDL號碼:
分類程式碼代碼:
12352106
NACRES:
NA.22
暫時無法取得訂價和供貨情況

化驗

>95% (HPLC)

形狀

solid or viscous liquid

反應適用性

reaction type: Pegylations

聚合物結構

shape: linear
functionality: heterobifunctional

運輸包裝

ambient

儲存溫度

−20°C

SMILES 字串

N(CCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCC(=O)O)C(=O)OCC1c2c(cccc2)c3c1cccc3

InChI

1S/C90H161NO40/c92-89(93)9-11-95-13-15-97-17-19-99-21-23-101-25-27-103-29-31-105-33-35-107-37-39-109-41-43-111-45-47-113-49-51-115-53-55-117-57-59-119-61-63-121-65-67-123-69-71-125-73-75-127-77-79-129-81-82-130-80-78-128-76-74-126-72-70-124-68-66-122-64-6

InChI 密鑰

XXEJJMXFEIKVOC-UHFFFAOYSA-N

特點和優勢

Fmoc-N-amido-dPEG36-acid is a monodisperse PEG product that is useful for peptide synthesis. The 112-atom dPEG spacer allows the introduction of a long, hydrophilic spacer onto either end of a peptide chain or between two peptide chains. The flexible dPEG spacer conjugates to peptides using conventional peptide synthesis chemistry. Peptide PEGylation imparts water solubility to hydrophobic peptide chains. Also, PEGylated peptides have expanded hydrodynamic volumes, which can reduce or eliminate renal clearance, and are protected from proteolysis. The combination of decreased renal clearance and protection from proteolysis contributes to longer in vivo circulation times for PEGylated (as compared to non-PEGylated) peptides. Additionally, PEGylation diminishes a peptide′s antigenicity. Fmoc-N-amido-dPEG36-acid is the monodisperse PEG equivalent of polymeric PEG1500. This product is part of the Fmoc-N-amido-dPEGn-acid (n=2, 3, 4, 5, 6, 8, 12, 24, 36) product series.

法律資訊

Products Protected under U.S. Patent #s 7,888,536 & 8,637,711 and European Patent #s 1,594,440 & 2,750,681
dPEG is a registered trademark of Quanta BioDesign

儲存類別代碼

11 - Combustible Solids

水污染物質分類(WGK)

WGK 3

閃點(°F)

Not applicable

閃點(°C)

Not applicable


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Peng Zhang et al.
Biomacromolecules, 18(8), 2509-2520 (2017-06-27)
Here, we report novel lipo-oligoaminoamide nanoformulations for targeted intracellular protein delivery. Formulations are generated by first bioreversibly conjugating a sequence-defined amphiphilic lipo-oligomer 728 to the cargo protein via disulfide bonds, followed by formulation of the formed 728-SS-protein conjugate with different
Jared F Stefanick et al.
ACS nano, 7(4), 2935-2947 (2013-02-21)
PEGylated liposomes are attractive pharmaceutical nanocarriers; however, literature reports of ligand-targeted nanoparticles have not consistently shown successful results. Here, we employed a multifaceted synthetic strategy to prepare peptide-targeted liposomal nanoparticles with high purity, reproducibility, and precisely controlled stoichiometry of functionalities
Peng-Cheng Lv et al.
Bioconjugate chemistry, 27(7), 1762-1769 (2016-07-01)
As tumors grow, vasculature is often deficient or malformed, resulting in many localized areas of hypoxia. Cells located in these hypoxic regions exhibit an altered gene expression pattern that can significantly alter resistance to conventional anticancer treatments such as ionizing
Ian W Hamley
Biomacromolecules, 15(5), 1543-1559 (2014-04-12)
The remarkable diversity of the self-assembly behavior of PEG-peptides is reviewed, including self-assemblies formed by PEG-peptides with β-sheet and α-helical (coiled-coil) peptide sequences. The modes of self-assembly in solution and in the solid state are discussed. Additionally, applications in bionanotechnology
Jared F Stefanick et al.
ACS nano, 7(9), 8115-8127 (2013-09-06)
Ligand-targeted nanoparticles are emerging drug delivery vehicles for cancer therapy. Here, we demonstrate that the cellular uptake of peptide-targeted liposomes and micelles can be significantly enhanced by increasing the hydrophilicity of the targeting peptide sequence while simultaneously optimizing the EG

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