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Entropy in biological binding processes: Estimation of translational entropy loss
Abstract
The loss of translational degrees of freedom makes an important, unfavorable contribution to the free energy of binding. Examination of experimental values suggest that calculation of this entropy using the Sackur–Tetrode equation produces largely overestimated values. Better agreement is obtained using the cratic entropy. Theoretical considerations suggest that the volumes available for the movement of a ligand in solution and in a complex are rather similar, suggesting also that the cratic entropy provides the best estimate of the loss of translational entropy. © 1994 John Wiley & Sons, Inc.
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Cited by
Cooperativity in Noncovalent Interactions
Mahadevi, A. S., & Sastry, G. N. (2016) · Chemical Reviews · doi:10.1021/cr500344e · Cited by 933
Absolute Binding Free Energies: A Quantitative Approach for Their Calculation
Boresch, S., Tettinger, F., Leitgeb, M., & Karplus, M. (2003) · The Journal of Physical Chemistry B · doi:10.1021/jp0217839 · Cited by 569
Metadata
- Authors
- Murphy, K. P., Xie, D., Thompson, K. S., Amzel, L. M., & Freire, E.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 1994-01
- Volume
- 18
- Issue
- 1
- Pages
- 63-67
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2005367001
- Cited by
- 178
- References
- 0
- FWCI
- 10.08
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Entropy in biological binding processes: Estimation of translational entropy loss. https://app.cochat.ai/papers/10.1002/prot.340180108
- The paper
- Murphy, K. P., Xie, D., Thompson, K. S., Amzel, L. M., & Freire, E. (1994). Entropy in biological binding processes: Estimation of translational entropy loss. Proteins: Structure, Function, and Bioinformatics. https://doi.org/10.1002/prot.340180108
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
