Construction Strategy of Functionalized Liposomes and Multidimensional Application

Liposomes are widely used in the biological field due to their good biocompatibility and surface modification properties. With the development of biochemistry and material science, many liposome structures and their surface functional components have been modified and optimized one by one, pushing the liposome platform from traditional to functionalized and intelligent, which will better satisfy and expand the needs of scientific research. However, a main limiting factor effecting the efficiency of liposomes is the complicated environmental conditions in the living body. Currently, in order to overcome the above problem, functionalized liposomes have become a very promising strategy. In this paper, binding strategies of liposomes with four main functional elements, namely nucleic acids, antibodies, peptides, and stimuli-responsive motif have been summarized for the first time. In addition, based on the construction characteristics of functionalized liposomes, such as drug-carrying, targeting, long-circulating, and stimulus-responsive properties, a comprehensive overview of their features and respective research progress are presented. Finally, the paper critically presents the limitations of these functionalized liposomes in the current applications and also prospectively suggests the future development directions, aiming to accelerate realization of their industrialization. In this review, the binding strategies of nucleic acids, antibodies, peptides and stimuli-responsive groups to liposomes are summarized. Then, according to the construction characteristics of functionalized liposomes, they are divided into drug-loaded, targeted, long-circulating, and stimulus-responsive liposomes, and the latest research progress and characteristics are comprehensively reviewed. Finally, the current application limitations and future development directions of functionalized liposomes to accelerate their industrialization process are critically proposed.image