Precise estimation of transfer free energies for ionic species between similar media
文献情報
Carmen Esposito, Andreas Vitalis
Transfer properties and partition coefficients for individual ions are relevant in a variety of scientific and engineering contexts, such as predicting the effects of different electrolytes on biomacromolecules in a preferential interaction sense or predicting the distribution of heavy metal ions in soils, rivers, etc. Computer simulations allow free energies of transfer to be estimated by considering single ions explicitly. When the two media under consideration are similar to each other regarding ion solvation, the resultant free energies are small in absolute magnitude. In these cases, it is advisable to simulate the transfer process directly. Here, we demonstrate how this can be achieved using two-dimensional umbrella sampling in conjunction with canonical ensemble molecular dynamics simulations where two liquid media are in direct contact. By calculating full two-dimensional potentials of mean force, these simulations allow the estimation of single-ion transfer free energies by integrating this surface accordingly. We report statistical accuracies to highlight that very high precision is achieved and needed to make even just qualitative statements about the transfer process. We close by discussing implications of our results for the specific case considered: the transfer of polypeptide side chain analogs from water to aqueous denaturant solutions.
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掲載誌
Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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