Evidence map›Paper›PMID 41936598›Full record

ArticleScientific reports2026

Identification of natural FGFR3 inhibitor for glioma using integrated computational and microRNA regulatory analysis.

Shehla Javaid, Nouman Ali, Samiah Shahid, Muhamamd Nouman Majeed

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

4 authors.

Shehla JavaidInstitute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan. shehla.javaid@rlku.edu.pk.
Nouman AliDepartment of Molecular Biosciences, Faculty of physical and Biological sciences, Rashid Latif Khan University, Lahore, Pakistan. Nouman.ali.anwar336@gmail.com.
Samiah ShahidInstitute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan.
Muhamamd Nouman MajeedDepartment of Biotechnology, Faculty of Science and Technology, University of Central Punjab, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma is an aggressive and treatment-resistant brain tumor with poor prognosis, frequently driven by aberrant activation of receptor tyrosine kinases such as fibroblast growth factor receptor 3 (FGFR3). Genetic alterations including FGFR3–TACC3 fusions and post-transcriptional deregulation mediated by tumor-suppressive microRNAs (miR-99a and miR-100) contribute to sustained FGFR3 signaling, glioma progression, and therapeutic resistance. In this study, a structure-based computational pipeline was employed to identify natural inhibitors targeting FGFR3. A phytochemical library comprising 25 plant-derived compounds was screened using ADME criteria, resulting in seven candidates with favorable gastrointestinal absorption and drug-likeness. Among them, Guggulsterone emerged as the top-ranked compound, exhibiting the highest docking affinity (− 10.1 kcal/mol) toward the FGFR3 kinase domain and forming stable hydrogen bonding and hydrophobic interactions with key active-site residues. The FGFR3 structure used showed high stereochemical quality (ERRAT score: 96.5; 93% residues in favored Ramachandran regions). Molecular dynamics simulations (500 ns) demonstrated stable complex formation, with RMSD convergence after 40 ns, low RMSF values, and consistent radius of gyration (1.96–2.04 nm). Persistent intermolecular hydrogen bonds (two to four) and stable solvent accessibility were observed throughout the simulation. MMGBSA binding free energy calculations predicted a favorable interaction (ΔGtotal = − 30.44 kcal/mol), primarily driven by van der Waals and electrostatic contributions. Pharmacophore analysis revealed two hydrogen bond acceptors and seven hydrophobic features, while density functional theory calculations indicated moderate chemical reactivity (HOMO–LUMO gap: 0.1797 a.u.). Toxicity assessment using ProTox 3.0 classified Guggulsterone as low-toxic (LD50 = 2300 mg/kg, Class 5). Collectively, these in-silico findings suggest Guggulsterone as a promising natural FGFR3-binding scaffold warranting further experimental validation in FGFR3-driven glioma models.

Indexed as

Brain NeoplasmsGliomaMicroRNAsPregnenedionesProtein Kinase InhibitorsReceptor, Fibroblast Growth Factor, Type 3Gene Expression Regulation, NeoplasticHumansHydrogen BondingMolecular Docking SimulationMolecular Dynamics SimulationFGFR3 protein, humanMicroRNAspregna-4,17-diene-3,16-dionePregnenedionesProtein Kinase InhibitorsReceptor, Fibroblast Growth Factor, Type 3FGFR3GlioblastomaGuggulsteroneMolecular dockingMolecular dynamics simulationNatural inhibitor

Identifiers

PMID41936598
PMCPMC13212756

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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.