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Updated: Nov 8, 2025

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
Published on: December 4, 2017
Comprehensive Characterization of the Self-Folding Cavitand Dynamics.
Ricard López-Coll1, Rubén Álvarez-Yebra1, Ferran Feixas1
1Institut de Química Computacional i Catàlisi (IQCC), Departament de Química, Universitat de Girona, Maria Aurèlia Capmany 69, 17003, Girona.
This study details the dynamic behavior of self-folding cavitand receptors using molecular dynamics simulations and NMR. Accelerated MD simulations revealed key folding and guest exchange processes, validating experimental findings.
Area of Science:
- Supramolecular Chemistry
- Computational Chemistry
- Chemical Physics
Background:
- Cavitand receptors, derived from resorcin[4]arenes, exhibit complex conformational dynamics.
- Understanding these dynamics is crucial for designing effective synthetic host-guest systems.
Purpose of the Study:
- To comprehensively characterize the conformational equilibria and guest exchange of a self-folding cavitand receptor.
- To develop and validate a multi-timescale simulation strategy for exploring fluxional behavior.
Main Methods:
- Utilized conventional and accelerated molecular dynamics (MD and aMD) simulations.
- Employed 1H Nuclear Magnetic Resonance (NMR) spectroscopy, specifically 1H EXSY experiments.
- Developed a multi-timescale strategy to capture events from nanoseconds to seconds.
Main Results:
- Reconstructed the folding/unfolding process, including partially open intermediates.
- Observed guest departure occurring at various folding stages.
- aMD simulations, after reweighing, accurately predicted kinetic barriers matching experimental NMR data.
Conclusions:
- Provided the first detailed characterization of cavitand receptor dynamics.
- Demonstrated the utility of aMD simulations for studying high-energy barrier processes in host-guest systems.
- The developed approach serves as a valuable tool for the rational design of synthetic host-guest systems.
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