Evidence map›Paper›PMID 40867649›Full record

ArticleBiomolecules2025

PInteract: Detecting Aromatic-Involving Motifs in Proteins and Protein-Nucleic Acid Complexes.

Dong Li, Fabrizio Pucci, Marianne Rooman

Abstract read
In one paragraph

Article in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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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.

Dong LiComputational Biology and Bioinformatics, Université Libre de Bruxelles, 1050 Brussels, Belgium.ORCID 0000-0001-7513-9136
Fabrizio PucciComputational Biology and Bioinformatics, Université Libre de Bruxelles, 1050 Brussels, Belgium.
Marianne RoomanComputational Biology and Bioinformatics, Université Libre de Bruxelles, 1050 Brussels, Belgium.

Funding

FNRS
6 · The paper itself

Abstract

With the recent development of accurate protein structure prediction tools, virtually all protein sequences now have an experimental or a modeled structure. It has therefore become essential to develop fast algorithms capable of detecting non-covalent interactions not only within proteins but also in protein-protein, protein-DNA, protein-RNA, and protein-ligand complexes. Interactions involving aromatic compounds, particularly their π molecular orbitals, hold unique significance among molecular interactions due to the electron delocalization, which is known to play a key role in processes such as protein aggregation. In this paper, we present PInteract, an algorithm that detects π-involving interactions in input structures based on geometric criteria, including π-π, cation-π, amino-π, His-π, and sulfur-π interactions. In addition, it is capable of detecting chains and clusters of π interactions as well as particular recurrent motifs at protein-DNA and protein-RNA interfaces, called stair motifs, consisting of a particular combination of π-π stacking, cation/amino/His-π and H-bond interactions.

Indexed as

AlgorithmsDNAProteinsRNAAmino Acid MotifsModels, MolecularProtein BindingDNAProteinsRNAaggregationprotein affinityprotein stabilitysolubilitystacking geometryT-shaped geometry

Identifiers

PMID40867649
PMCPMC12384504

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.