Evidence map›Paper›PMID 42354196›Full record

ArticleFoods (Basel, Switzerland)2026

Secondary-Structure-Dependent Cooperation and Interference Between Peptides of Different Chain Lengths in Antifreeze Activity: Insights from Molecular Dynamics Simulations.

Yuan Yuan, Micholas Dean Smith, Tong Wang

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuan YuanDepartment of Food Science, Institute of Agriculture, University of Tennessee, 2510 River Dr., Knoxville, TN 37996, USA.ORCID 0009-0008-8365-8284
Micholas Dean SmithDepartment of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA.ORCID 0000-0002-0777-7539
Tong WangDepartment of Food Science, Institute of Agriculture, University of Tennessee, 2510 River Dr., Knoxville, TN 37996, USA.

Funding

U.S. National Science Foundation 2103558
6 · The paper itself

Abstract

Ice recrystallization inhibition (IRI) activity of peptides is influenced by both peptide length and secondary structure; however, whether combinations of peptides with different lengths exhibit cooperative or antagonistic effects remains poorly understood. Using molecular dynamics simulations, this study investigated how secondary structure and chain-length heterogeneity jointly affect the IRI activity of peptide-pair mixtures. For systems containing only β-sheet-rich peptides, mixtures of different chain lengths consistently reduced ice content relative to the corresponding single-peptide systems, suggesting cooperative enhancement of IRI activity. In contrast, individual α-helical peptides showed strong inhibition of ice growth, but this effect was diminished after they were mixed into peptide pairs. Structural analyses suggested that the improved performance of β-sheet mixtures was associated less with the simple preservation of native β-sheet structure than with mixing-induced changes in peptide-peptide coupling and surface exposure. By contrast, helix-containing mixtures retained more of their original local structure in some cases, but this structural retention was not accompanied by improved ice-growth suppression after mixing. Together, these findings suggest that peptide length effects on IRI are not universally synergistic but depend strongly on secondary-structure compatibility.

Indexed as

antifreeze peptideschain lengthmolecular dynamics simulationsecondary structure

Identifiers

PMID42354196
PMCPMC13298197

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.