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Updated: Mar 21, 2026

Development of Heterogeneous Enantioselective Catalysts using Chiral Metal-Organic Frameworks MOFs
Published on: January 17, 2020
Organic Acid-Induced Twisting in Heterometallic Clusters Enables Multimodal Chiroptical Sensing and Enantioselective
Jia-Yin Wang1,2, Jun-Ru Wang1, Miao-Miao Liu1
1Tianjian Laboratory of Advanced Biomedical Sciences, Henan Key Laboratory of Crystalline Molecular Functional Materials, College of Chemistry, Zhengzhou University, Zhengzhou, China.
Abstract:
Rapid, reusable, and quantitative recognition of chiral acids and drugs remains challenging, as conventional covalent or host-guest strategies suffer from poor reversibility and limited adaptability. Here, atomically precise heterometallic nanoclusters undergo organic acid-induced coordination twisting and core symmetry breaking, dynamically modulating their coordination environment for enantiomeric resolution. Chiral amino acids stabilize cluster chirality, yielding enantiopure clusters matching the amino acid configuration. These clusters exhibit strong chiroptical responses, including circular dichroism (CD) and circularly polarized luminescence (CPL), enabling reliable quantification of enantiomeric excess (ee) across 20 chiral acids. Significantly, the system can be rationally regenerated and reused, enabling multiple cycles of consistent, quantitative chiral sensing. Mechanistic studies reveal that recognition arises from electrostatic preconcentration, followed by coordination and hydrogen bonding, which lock substrate configurations and transfer chiral information. Furthermore, threonine-modified chiral heterometallic clusters also enable enantioselective coordination-driven drug sensing, exemplified by ibuprofen recognition via ligand exchange, as unambiguously confirmed by single-crystal X-ray analysis. This work establishes a versatile coordination-driven platform for high-throughput, real-time, and quantitative enantioselective sensing, highlighting the potential of atomically precise clusters for chiral recognition and drug analysis.
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