Double level selection in a constitutional dynamic library of coordination driven supramolecular polygons

Area of Science:

• Supramolecular Chemistry
• Materials Science
• Chemical Biology

Background:

• Constitutional dynamic libraries (CDLs) offer a versatile platform for creating complex molecular architectures.
• Metallo-supramolecular assemblies, particularly polygons, are of interest for their unique structural and functional properties.
• Molecular recognition is a fundamental principle governing host-guest interactions and self-assembly processes.

Purpose of the Study:

• To investigate molecular recognition mechanisms within a CDL of Cu(II) metallo-supramolecular polygons.
• To explore guest-induced selection and templated self-assembly pathways.
• To quantify the selectivity and affinity of host-guest interactions.

Main Methods:

• Utilized a constitutional dynamic library (CDL) of Cu(II) metallo-supramolecular polygons.
• Employed guest molecules to induce selective sorting and templated self-assembly.
• Determined association constants through competition and exchange studies.
• Analyzed data using variable temperature UV-Vis absorption spectroscopy and single crystal X-ray diffraction.
• Performed all-electron density functional theory (DFT) and time-dependent DFT (TDDFT) calculations.

Main Results:

• Observed two selection mechanisms: guest-induced pathways and guest-templated self-assembly.
• Demonstrated high selectivity (up to ~10^4) of the triangular host for various guests.
• Identified a dual-level selection process involving guest-driven assembly and host-based guest discrimination.
• DFT calculations confirmed the dispersive nature of host-guest interactions.
• TDDFT provided detailed assignments of spectral features for host and host-guest systems.

Conclusions:

• The study successfully established a model system for molecular recognition within a CDL.
• The findings highlight the potential of metallo-supramolecular polygons for selective guest binding and separation.
• The combination of experimental and computational methods provides a comprehensive understanding of the underlying interactions.