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Published on: February 7, 2017
Entropy-driven homochiral self-sorting of a dynamic library
Joan Atcher1, Jordi Bujons, Ignacio Alfonso
1Department of Biological Chemistry and Molecular Modelling, Institute of Advance Chemistry of Catalonia (IQAC-CSIC), Jordi Girona 18-26, 08034, Barcelona, Spain. ignacio.alfonso@iqac.csic.es.
Chemical Communications (Cambridge, England)
|April 1, 2017
Summary
Glutamic acid macrocycles self-sort into homochiral structures in response to solvent changes. This self-selection is driven by entropy, particularly at higher temperatures, and requires anionic side chains, revealing insights into adaptive chemical systems.
Area of Science:
- Supramolecular Chemistry
- Chemical Systems Biology
- Organic Chemistry
Background:
- Dynamic mixtures of stereoisomeric macrocycles are key components in adaptive chemical systems.
- Understanding self-selection mechanisms in these systems is crucial for developing novel materials and processes.
Purpose of the Study:
- To investigate the phenomenon of homochiral self-selection in macrocycles derived from glutamic acid.
- To elucidate the driving forces and conditions governing this self-sorting behavior.
Main Methods:
- Dynamic combinatorial chemistry using macrocycles derived from glutamic acid.
- Solvent composition manipulation (acetonitrile content).
- Nuclear Magnetic Resonance (NMR) spectroscopy and Molecular Dynamics (MD) simulations for conformational analysis.
Main Results:
- Homochiral self-selection was observed upon increasing acetonitrile concentration in the aqueous medium.
- The self-sorting process necessitates the anionic form of glutamic acid side chains.
- Higher temperatures enhanced the self-sorting, indicating an entropic contribution.
- Conformational analysis provided mechanistic insights into the observed behavior.
Conclusions:
- Entropy plays a significant role in driving homochiral self-sorting in adaptive bio-inspired chemical systems.
- The study demonstrates a controllable self-organization mechanism in complex molecular mixtures.
- Findings contribute to the understanding of self-assembly principles in synthetic and biological systems.
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