Evidence map›Paper›PMID 40102529›Full record

ArticleScientific reports2025

Neutrophil elastase binds at the central domain of extracellular Toll-like receptor 4: AI prediction, docking, and validation in disease model.

Azeem Ali, Leena Gaba, Sujata Jetley, Imran A Khan, Prem Prakash

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

5 authors.

Azeem AliDepartment of Molecular Medicine, Jamia Hamdard, New Delhi, Delhi, 110062, India.
Leena GabaHamdard Institute of Medical Sciences, Jamia Hamdard, New Delhi, 110062, India.
Sujata JetleyHamdard Institute of Medical Sciences, Jamia Hamdard, New Delhi, 110062, India.
Imran A KhanDepartment of Chemistry, Jamia Hamdard, New Delhi, 110062, India.
Prem PrakashDepartment of Molecular Medicine, Jamia Hamdard, New Delhi, Delhi, 110062, India. prem@jamiahamdard.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interaction between Neutrophil Elastase (NE) and Toll-like receptor 4 (TLR4) has attracted substantial scientific attention, particularly regarding its potential role in cardiovascular diseases. Employing AlphaFold2, biomolecular docking, and MMGBSA calculation we aimed to predict their binding and validated the results through a co-immunoprecipitation study in a rat model with isoproterenol (ISO) -induced cardiac hypertrophy. Our findings strongly suggest a specific and plausible interaction between rat NE and rat TLR4, distinct from other neutrophil-derived serine proteases. Notably, AlphaFold2's precision was confirmed through cross-validation with known protein crystal structures, while Consurf analysis emphasized the evolutionary variable to conserve the rat NE - rat TLR4 binding site. HADDOCK, RosettaDock, ZDOCK, MD simulation, MMGBSA calculations, and superimposition with the stabilized structure complex all predicted strong binding between rat NE and rat TLR4. Our animal experiments revealed elevated NE and TLR4 expression in the hypertrophied myocardium following ISO infusion, with data confirming the physical interaction between NE and TLR4. Overall, this study sheds light on the intricate molecular association between NE and TLR4, underlining their potential significance in cardiovascular pathophysiology. Furthermore, it underscores AlphaFold2's reliability as a robust tool for predicting protein-protein interactions and complex structures.

Indexed as

CardiomegalyLeukocyte ElastaseToll-Like Receptor 4AnimalsBinding SitesDisease Models, AnimalIsoproterenolMaleMolecular Docking SimulationProtein BindingRatsIsoproterenolLeukocyte ElastaseTlr4 protein, ratToll-Like Receptor 4AlphaFold2Cardiac hypertrophyNeutrophil elastaseProtein-Protein interactionToll-like receptor 4

Identifiers

PMID40102529
PMCPMC11920248

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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.