It is an important research direction to load recognition ligands on nanoparticles for active recognition of tumors, so as to achieve targeted therapy. However, in recent years, the effectiveness of this method has been increasingly questioned.
It is an important research direction to load recognition ligands on nanoparticles for active recognition of tumors, so as to achieve targeted therapy. However, in recent years, the effectiveness of this method has been increasingly questioned. The latest research of Chinese researchers shows that it is effective to use nanoparticles to target tumor recognition, but its effect is obviously affected by the target modification mode.
Li Feng, researcher of Wuhan Institute of Virology, Chinese Academy of Sciences, and Zhang xianen, researcher of Institute of Biophysics, Chinese Academy of Sciences were the research team to carry out the research. Recently, with the help of the spatial addressable property of the protein nanocage, using controllable self-assembly and high-efficiency click chemical reaction, they successfully realized the precise and controllable modification of the targeted ligand on the mini ferritin nanocage, and obtained six nanoparticle models with specific ligand number and spatial distribution.
A series of cell level and tumor bearing animal model experiments showed that no matter what kind of ligand parameter, it has different contribution to active targeting. Further studies showed that the differences in the distribution patterns of these ligands were related to the clustering of receptors on the surface of target cells and the related effects of endocytosis and opsonin.
Li Feng said that this study helps to understand and clarify the controversy about the active targeting effect in the field of tumor nano medicine, and highlights the importance of precise functionalization in the construction of biological nano probes and devices. Relevant research results have recently been published online in the internationally renowned multidisciplinary journal small.
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