Multifunctional MOF composites for advanced drug identification and screening: Innovations, applications and challenges.

Authors

Min Wang, Yanjie Cheng, Manyao Zhang, Shuang Liu, Linyuan Luo, Xiang Han, Jingdi Chen, Zhining Xia, Hongli Luo

Published in

Journal of pharmaceutical analysis. Volume 16. Issue 8. Pages 101543. Epub Jan 02, 2026.

Abstract

Drug identification and screening are crucial in precision medicine and pharmaceutical research, yet they face challenges such as interference from complex biological matrices, insufficient sensitivity for trace detection, and poor specificity. Multifunctional metal-organic framework (MOF) composites, leveraging their tunable pore structures, high specific surface area, and modular functional integration capabilities, have emerged as promising solutions to address these issues. Despite rapid progress, a systematic review comprehensively consolidating these advances remains absent. This review systematically summarizes the design strategies and performance advantages of four representative types of MOF composites (carbon dots (CDs)-MOFs, magnetic nanoparticles (MNPs)-MOFs, biomacromolecules-MOFs, covalent organic frameworks (COFs)-MOFs), along with their applications in multimodal sensing (fluorescence, electrochemical, colorimetric, and surface-enhanced Raman scattering (SERS)) and high-efficiency screening platforms (offline ligand fishing (LF) and immobilized enzyme microreactors (IMERs)). Collective findings demonstrate that rationally engineered multifunctional MOF composites can significantly meet the stringent requirements of drug analysis regarding sensitivity, selectivity, and stability. This review also provides an in-depth discussion of current challenges and future directions in the field, including stability, structure-activity relationships, biocompatibility, and scalable fabrication, aiming to offer design insights for the development of drug identification and screening technologies and to fill the gap in systematic reviews in this area.

PMID:
42633210
Bibliographic data and abstract were imported from PubMed on 23 Aug 2026.

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