The DOI matches its Crossref record.
How Hofmeister ion interactions affect protein stability
Open accessAbstract
Model compound studies in the literature show how Hofmeister ion interactions affect protein stability. Although model compound results are typically obtained as salting-out constants, they can be used to find out how the interactions affect protein stability. The null point in the Hofmeister series, which divides protein denaturants from stabilizers, arises from opposite interactions with different classes of groups: Hofmeister ions salt out nonpolar groups and salt in the peptide group. Theories of how Hofmeister ion interactions work need to begin by explaining the mechanisms of these two classes of interactions. Salting-out nonpolar groups has been explained by the cavity model, but its use is controversial. When applied to model compound data, the cavity model 1) uses surface tension increments to predict the observed values of the salting-out constants, within a factor of 3, and 2) predicts that the salting-out constant should increase with the number of carbon atoms in the aliphatic side chain of an amino acid, as observed. The mechanism of interaction between Hofmeister ions and the peptide group is not well understood, and it is controversial whether this interaction is ion-specific, or whether it is nonspecific and the apparent specificity resides in interactions with nearby nonpolar groups. A nonspecific salting-in interaction is known to occur between simple ions and dipolar molecules; it depends on ionic strength, not on position in the Hofmeister series. A theory by Kirkwood predicts the strength of this interaction and indicates that it depends on the first power of the ionic strength. Ions interact with proteins in various ways besides the Hofmeister ion interactions discussed here, especially by charge interactions. Much of what is known about these interactions comes from studies by Serge Timasheff and his co-workers. A general model, suitable for analyzing diverse ion-protein interactions, is provided by the two-domain model of Record and co-workers.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Charge density-dependent strength of hydration and biological structure
Collins, K. D. (1997) · Biophysical Journal · doi:10.1016/s0006-3495(97)78647-8 · Cited by 1,334
LL-37, the only human member of the cathelicidin family of antimicrobial peptides
Dürr, U. H. N., Sudheendra, U. S., & Ramamoorthy, A. (2006) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2006.03.030 · Cited by 1,049
How Ions Affect the Structure of Water
Hribar, B., Southall, N. T., Vlachy, V., & Dill, K. A. (2002) · Journal of the American Chemical Society · doi:10.1021/ja026014h · Cited by 860
The present state of affairs with Hofmeister effects
Kunz, W., Lo Nostro, P., & Ninham, B. W. (2004) · Current Opinion in Colloid & Interface Science · doi:10.1016/j.cocis.2004.05.004 · Cited by 854
How Water’s Properties Are Encoded in Its Molecular Structure and Energies
Brini, E., Fennell, C. J., Fernandez-Serra, M., Hribar-Lee, B., Lukšič, M., & Dill, K. A. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00259 · Cited by 518
Metadata
- Authors
- Baldwin, R. L.
- Venue
- Biophysical Journal
- Publisher
- Elsevier BV
- Published
- 1996-10
- Volume
- 71
- Issue
- 4
- Pages
- 2056-2063
- ISSN
- 0006-3495 (ISSN-L)
- OpenAlex
- W2123331319
- Cited by
- 1,124
- References
- 0
- FWCI
- 3.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: How Hofmeister ion interactions affect protein stability. https://app.cochat.ai/papers/10.1016/s0006-3495(96)79404-3
- The paper
- Baldwin, R. L. (1996). How Hofmeister ion interactions affect protein stability. Biophysical Journal. https://doi.org/10.1016/s0006-3495(96)79404-3
Data sources
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.