ArticleFrontiers in endocrinology2026
Research on the influence of bisphenol A on precocious puberty based on network toxicology and molecular dynamics simulation.
Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Precocious puberty (PP) is a pediatric endocrine disorder. Bisphenol A (BPA) is an endocrine disruptor. This study aimed to computationally investigate BPA-associated PP targets and mechanisms via network toxicology and molecular dynamics. Methods: BPA information was obtained from PubChem. Target genes were collected from multiple databases, and PP-related genes were identified via GeneCards and Online Mendelian Inheritance in Man. ProTox was used to predict BPA toxicity. After gene set intersection, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed (P < 0.05). A protein-protein interaction (PPI) network was constructed to identify key genes, and a BPA-key gene-pathway network was established. The subcellular localization of key genes was analyzed, followed by molecular docking (score ≤ -5 kcal/mol) and 100-ns GROMACS-based molecular dynamics simulation. Results: A total of 722 BPA targets and 1,126 potential PP targets were identified using multiple databases. Their intersection gave 99 potential target genes for BPA-induced PP, and further intersection with 16 toxic target genes of BPA resulted in six candidate genes. GO enrichment had 378 pathways, and KEGG enrichment had 18 pathways, with the top 10 being related to processes such as chemical carcinogenesis-receptor activation. The PPI network analysis revealed four key genes. Subcellular localization showed key gene product distribution. Molecular docking revealed a strong binding force, and molecular dynamics simulation further indicated that the complexes formed by BPA and these proteins were structurally stable. Conclusions: This study identified potential BPA-PP targets, providing a hypothesis-generating basis for future validation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.