The DOI matches its Crossref record.
Protein stability curves
Abstract
The stability curve of a protein is defined as the plot of the free energy of unfolding as a function of temperature. For most proteins the change in heat capacity on denaturation, or unfolding, is large but approximately constant. When unfolding is s two‐state process, most of the salient features of the stability curves of proteins can be derived from this fact. A number of relations are obtained, including the special features of low‐temperature denaturation, the properties of the maximum in stability, and the interrelationships of the characteristic temperatures of the protein. The paper closes with a formula that permits one to calculate small changes in stabilization free energy from changes in the melting temperature of the protein.
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
Role of the hydrophobic effect in stability of site-specific protein-DNA complexes
Ha, J.-H., Spolar, R. S., & Record, M. T. (1989) · Journal of Molecular Biology · doi:10.1016/0022-2836(89)90608-6 · Cited by 386
Strategy for analysing the co-operativity of intramolecular interactions in peptides and proteins
Horovitz, A., & Fersht, A. R. (1990) · Journal of Molecular Biology · doi:10.1016/0022-2836(90)90275-q · Cited by 335
Protein stability and enzyme activity at extreme biological temperatures
Feller, G. (2010) · Journal of Physics: Condensed Matter · doi:10.1088/0953-8984/22/32/323101 · Cited by 337
Psychrophilic Enzymes: From Folding to Function and Biotechnology
Feller, G. (2013) · Scientifica · doi:10.1155/2013/512840 · Cited by 323
Measuring the stability of partly folded proteins using TMAO
Mello, C. C., & Barrick, D. (2003) · Protein Science · doi:10.1110/ps.0372903 · Cited by 151
Metadata
- Authors
- Becktel, W. J., & Schellman, J. A.
- Venue
- Biopolymers
- Publisher
- Wiley
- Published
- 1987-11
- Volume
- 26
- Issue
- 11
- Pages
- 1859-1877
- ISSN
- 0006-3525 (ISSN-L)
- 1097-0282
- OpenAlex
- W2078933151
- Cited by
- 1,000
- References
- 0
- FWCI
- 6.34
- Type
- journal article
- Language
- en
- Open access
- closed
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: Protein stability curves. https://app.cochat.ai/papers/10.1002/bip.360261104
- The paper
- Becktel, W. J., & Schellman, J. A. (1987). Protein stability curves. Biopolymers. https://doi.org/10.1002/bip.360261104
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.