Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 334

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

A statistical mechanical model for β-hairpin kinetics

Open access
Muñoz, Victor, Henry, Eric R., Hofrichter, James, Eaton, William A.·1998·Proceedings of the National Academy of Sciences

Abstract

Understanding the mechanism of protein secondary structure formation is an essential part of the protein-folding puzzle. Here, we describe a simple statistical mechanical model for the formation of a β-hairpin, the minimal structural element of the antiparallel β-pleated sheet. The model accurately describes the thermodynamic and kinetic behavior of a 16-residue, β-hairpin-forming peptide, successfully explaining its two-state behavior and apparent negative activation energy for folding. The model classifies structures according to their backbone conformation, defined by 15 pairs of dihedral angles, and is further simplified by considering only the 120 structures with contiguous stretches of native pairs of backbone dihedral angles. This single sequence approximation is tested by comparison with a more complete model that includes the 2 15 possible conformations and 15 × 2 15 possible kinetic transitions. Finally, we use the model to predict the equilibrium unfolding curves and kinetics for several variants of the β-hairpin peptide.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.95.11.5872

Cites

2 of 2 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cites

Show all 2 references

Cited by

See all 334

Metadata

Authors
Muñoz, V., Henry, E. R., Hofrichter, J., & Eaton, W. A.
Venue
Proceedings of the National Academy of Sciences
Published
1998-05-26
Volume
95
Issue
11
Pages
5872-5879
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1966712500
Cited by
334
References
2
FWCI
5.06
Type
journal article
Language
en
Open access
green

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: A statistical mechanical model for β-hairpin kinetics. https://app.cochat.ai/papers/10.1073/pnas.95.11.5872
The paper
Muñoz, V., Henry, E. R., Hofrichter, J., & Eaton, W. A. (1998). A statistical mechanical model for β-hairpin kinetics. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.95.11.5872

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.