谷歌浏览器插件
订阅小程序
在清言上使用

A Dual-Targeting Peptide for Glioblastoma Screened by Phage Display Peptide Library Biopanning Combined with Affinity-Adaptability Analysis.

International journal of pharmaceutics(2023)

引用 1|浏览16
暂无评分
摘要
The obstruction of blood-brain barrier (BBB) and the poor specific targeting are still the major obstacles and challenges of targeted nano-pharmaceutical therapy for glioblastoma (GBM) up to now. It is critical to find appropriate targeting ligands that can effectively mediate the nano-pharmaceuticals to penetrate brain capillary endothelial cells (BCECs) and then specifically bind to glioblastoma cells (GCs). Herein, a dual-targeting ligand for GBM was screened by the combination of phage display peptide library biopanning and affinity-adaptability analysis. Based on the acquisition of sub-library of peptide which exhibited the specific affinity to both BCECs and GCs, a comparison parameter of relative affinity was deliberately introduced to evaluate the relative affinity of candidate peptides to U251-MG cells and bEnd.3 cells. The optimized WTW peptide (sequenced as WTWEYTK) was provided with a high relative affinity (R-U/B = 2.44), implying that its high affinity to U251-MG cells and moderate affinity to bEnd.3 cells might synergistically promote its receptor-mediated internalization and transport, the dissociation from bEnd.3, and the binding to U251-MG. The results of BBB model trials in vitro showed that the BBB penetration efficiency and GBM accumulation of WTW peptide were significantly higher than those of WSL peptide, GNH peptide, and REF peptide. Results of orthotopic GBM xenograft model assays in vivo also indicated that WTW peptide had successfully penetrated the BBB and improved accumulation in GBM. The screened WTW peptide might be the potential dual-targeting ligand to motivate the advancement of GBM targeted therapy.
更多
查看译文
关键词
Glioblastoma,Dual-targeting peptide,Phage display peptide library,Affinity-adaptability analysis,Blood-brain barrier
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要