Pillararene-based supramolecular systems for theranostics and bioapplications

Huangtianzhi Zhu, Qi Li, Laila E. Khalil-Cruz, Niveen M. Khashab, Guocan Yu, Feihe Huang

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

As an emerging type of important macrocycles for supramolecular chemistry, pillararenes and their derivatives have been widely studied and applied in numerous fields, which intensively promotes the development of chemistry, materials science and biology. Pillararene-based theranostic systems are of special interest in the biological and medical areas as they have shown very promising results. Owing to easy preparation, reliable guest affinity, good biocompatibility and stability, pillararenes are frequently used to construct functional biomaterials. On one hand, pillararenes can either be used individually or form diversiform self-assemblies such as micelles, nanoparticles and vesicles to increase water solubility and biocompatibility of drugs. On the other hand, it is promising to modify solid materials like framework materials, silica nanoparticles and graphene oxides with pillararene derivatives to enhance their functions and controllability. In this review, we summarize recent endeavors of pillararene-based supramolecular systems with theranostics and other biological applications comprising drug delivery chemotherapy, photodynamic/photothermal therapy, antimicrobials, bioimaging, etc. By introducing several typical examples, the design principles, preparation strategies, identifications and bio-applications of these pillararene-based supramolecular systems are described. Future challenges and directions of this field are also outlined.
Original languageEnglish (US)
JournalScience China Chemistry
DOIs
StatePublished - Mar 23 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-04-05
Acknowledged KAUST grant number(s): OSR-2019-CRG8-4032
Acknowledgements: This work was supported by the National Natural Science Foundation of China (22035006). This publication is based in part upon work supported by the King Abdullah University of Science and Technology Office of Sponsored Research (OSR-2019-CRG8-4032).

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