Excel · study · 2026
Disease correlation mapping based discovery of 2-methoxyestradiol as an endogenous ligand of the orphan nuclear receptor Nur77
Listed in NCBI GEO
Identifying endogenous ligands for orphan nuclear receptors is pivotal for understanding their roles in disease pathogenesis.
Description
In this study, we introduce DCM-Endo, a novel computational tool employing a deep clustering algorithm to analyze disease correlations from PubMed abstracts, thereby predicting potential endogenous ligands for nuclear receptors, and other receptor proteins. Utilizing DCM-Endo, we identified 2-methoxyestradiol as an endogenous ligand for Nur77, an orphan nuclear receptor implicated in various diseases and biological processes.
Subsequent molecular docking and hydrogen deuterium exchange mass spectrometry confirmed the interaction, revealing that 2-methoxyestradiol binds to the Nur77 ligand-binding domain (Nur77-LBD), inducing a conformational loosening. The binding affinity of 2-methoxyestradiol to Nur77-LBD, measured by surface plasmon resonance, is 3.03μM. Moreover, 2-methoxyestradiol significantly modulates the transcription of TNF-α, FABP4, and CHOP, effects that are nullified by Nur77 knockdown, confirming its functionality as an endogenous ligand of Nur77.
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Our discovery of 2-methoxyestradiol as an endogenous ligand for Nur77 not only reveals a new regulatory mechanism but also highlights the efficacy of DCM-Endo as a tool for endogenous ligand discovery.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE281nnn/GSE281700 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE281700 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1185259 ncbi.nlm.nih.gov/bioproject/PRJNA1185259 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Bioinformatics and computational biology 73% · Disease 75% · Mass spectrometry 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE281700 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3102 | enrichment · NCBI GEO | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:mass-spectrometry | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |