Evidence map›Paper›PMID 40645560›Full record

ArticleJournal of molecular biology2025

Properties Governing Native State Entanglements and Relationships to Protein Function.

Justin Petucci, Ian Sitarik, Yang Jiang, Viraj Rana, Hyebin Song, Edward P O'Brien

Abstract read
In one paragraph

Article in Journal of molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Justin PetucciInstitute for Computational and Data Sciences, Pennsylvania State University, University Park, PA 16802, USA.
Ian SitarikDepartment of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.
Yang JiangDepartment of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.
Viraj RanaDepartment of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.
Hyebin SongBioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA; Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA. Electronic address: hps5320@psu.edu.
Edward P O'BrienInstitute for Computational and Data Sciences, Pennsylvania State University, University Park, PA 16802, USA; Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA; Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA. Electronic address: epo2@psu.edu.

Funding

Translation Kinetics and their Effects on Protein Structure and Function, mRNA half-lives, and Cellular PhenotypeR35GM124818 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI Edward Patrick O'Brien · 2017 to 2026
$4.0M
NIGMS NIH HHS R35 GM124818
6 · The paper itself

Abstract

Non-covalent lasso entanglements are structural motifs found in a majority of globular proteins, and their misfolding has been linked to a range of biological consequences. Here, we characterize these motifs' structural and physicochemical properties, sequence biases, functional site correlations, and universal features across E. coli, S. cerevisiae, and H. sapiens. We find that the crossing residues, which pierce the plane of the entanglement loop, are 11-times more likely to be a β-strand than an α-helix or random coil, and that around this position the protein sequence is 2.5-times more likely to be composed of a stretch of all hydrophobic residues (most often Val, Ile, or Phe) compared to other sequence motifs. Functionally, crossing residues are enriched at enzyme active sites in S. cerevisiae and small molecule binding residues across all species to degrees greater than expected by random chance. Metal binding residues are enriched in these entanglements in H. sapiens. Increasing statistical power by pooling together these species data, we find RNA-binding residues are enriched in these entanglement components. On the other hand, there is a spatial depletion of crossing residues at sites involved in protein binding. Using machine learning, we identified eight robust features predictive of these entanglements, achieving AUROC scores of 0.8 across species. These results are significant because they suggest a direct role for components of native entanglements in particular protein functions, as well as identifying strong secondary structure and sequence preferences in native entanglements.

Indexed as

ProteinsAmino Acid SequenceBinding SitesEscherichia coliHumansModels, MolecularProtein ConformationProtein FoldingSaccharomyces cerevisiaeProteinsmachine learning feature selectionnon-covalent lasso entanglementprotein functionsequence biases

Identifiers

PMID40645560
PMCPMC12503130

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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.