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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

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Precisely Creating Enzyme-Mimetic Metal-Organic Framework for Unnatural Peptide Synthesis.

Jing Ouyang1, Peiqi Zhang1, Le Yang1

  • 1Department of Chemistry, The Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Kowloon 999077, Hong Kong SAR, China.

Journal of the American Chemical Society
|March 3, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel metal-organic framework (MOF) catalyst for synthesizing unnatural gamma-amino acids and peptides. This MOF system enables efficient amino acid homologation and peptide synthesis, mimicking natural enzymatic processes.

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Area of Science:

  • Catalysis
  • Organic Chemistry
  • Materials Science

Background:

  • Unnatural gamma-amino acids and peptides are crucial in drug discovery and biomaterials due to their structural flexibility and specific biological interactions.
  • Nature lacks efficient biosynthetic pathways for complex gamma-amino acids and peptides, creating a synthetic challenge.

Purpose of the Study:

  • To design a metal-organic framework (MOF)-based catalytic system for synthesizing complex gamma-amino acids and peptides.
  • To mimic enzymatic catalytic pockets using MOFs with integrated hydrogen-bond donors and photosensitizers.

Main Methods:

  • Development of a MOF-based catalytic system incorporating hydrogen-bond donors and organic photosensitizers.
  • Utilizing synergistic catalysis involving hydrogen-bonding and photoredox mechanisms for amino acid homologation.
  • Employing mechanistic studies and density functional theory (DFT) calculations to understand catalytic processes.

Main Results:

  • Achieved efficient amino acid homologation and modular synthesis of gamma-amino acid derivatives.
  • Enabled programmable and divergent synthesis of gamma-peptides.
  • MOF catalysts demonstrated high efficiency (turnover numbers up to 7800) and robustness due to their rigid framework.

Conclusions:

  • The MOF system successfully mimics natural enzymatic systems, featuring multisite activation, induced fit, and synergistic catalysis.
  • This research advances MOF catalysis and peptide synthesis, offering a new platform for designing synergistic catalytic systems.