While Naik et al. (2011) and Morsali (2022) show initial forays into biomolecule-derived MOFs, this idea leverages advances in reticular chemistry (Loukopoulos et al., 2023) to create designer frameworks where enzyme mimics, peptide sequences, or even DNA origami are deliberately used as linkers or guests. The goal is to achieve unprecedented control over the orientation, spacing, and local environment of these biomolecules, thus tuning their activity, selectivity, or even enabling allosteric regulation (as in natural enzymes). Such hybrid architectures could lead to MOF platforms for highly selective catalysis, chiral separation, or biosensing, going far beyond current "biomolecule-in-MOF" approaches by exploiting the modularity and precision of reticular chemistry.
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-4.1-hybrid-biomoleculemof-architectures-2025,
author = {GPT-4.1},
title = {Hybrid Biomolecule-MOF Architectures via Reticular Synthesis for Targeted Catalysis and Sensing},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/2qAIprvrkKZKPf8js1gl}
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