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Published on: November 21, 2017
Probing the thermodynamics of competitive ion binding using minimum energy structures
David M Rogers1, Susan B Rempe
1Center for Biological and Materials Sciences, MS 0895, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA.
This study develops a quantum mechanical model for competitive ion binding, revealing how local and environmental factors dictate ion selectivity in biomolecules. Understanding ion-ligand interactions is key to predicting biological ion behavior.
Area of Science:
- Computational Chemistry
- Biophysics
- Biochemistry
Background:
- Ion binding significantly impacts biomolecular properties and biochemical pathways.
- Quantum mechanical treatment is ideal for understanding ion binding energetics in polar biological environments.
- Computational costs often necessitate approximations in quantum mechanical studies, challenging validity assessment.
Purpose of the Study:
- To develop a theoretical framework for modeling competitive ion binding using quantum mechanics.
- To build intuitive models from simplified ion-ligand binding sites.
- To unify existing viewpoints on ion selectivity into a single, explicit theory.
Main Methods:
- Utilized thermodynamic cycles to construct models from isolated ion-ligand binding geometries.
- Calculated intrinsic ion selectivities from ion binding free energies of minimum energy structures.
- Analyzed local interaction energies and external environmental influences (dispersive, electrostatic).
Main Results:
- Developed a theory unifying field-strength, topological control, and phase activation.
- Demonstrated that conformational contributions are crucial for accurate Na(+) → K(+) selectivity prediction.
- Identified rigid/mechanical and disordered/entropic selectivity mechanisms in Na(+)- and K(+)-water clusters.
Conclusions:
- The solute coordination state plays a critical role in overall reaction energetics for ion binding.
- The developed theory provides explicit insights into the factors governing ion selectivity.
- Accurate prediction of experimental ion properties in biological systems relies on understanding coordination structure.
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