ArticleActa pharmacologica Sinica2019
Molecular dynamics simulations on RORγt: insights into its functional agonism and inverse agonism.
Article in Acta pharmacologica Sinica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 11 citations in OpenAlex.
- Uricolysis by Arthrobacter globiformis uricase: structural basis for its catalytic activity and thermostability.Acta pharmacologica Sinica · 2025Article
- Discovery, Synthesis, and In Vitro Characterization of 2,3 Derivatives of 4,5,6,7-Tetrahydro-Benzothiophene as Potent Modulators of Retinoic Acid Receptor-Related Orphan Receptor γt.Journal of medicinal chemistry · 2023Article
- Recent applications of computational methods to allosteric drug discovery.Frontiers in molecular biosciences · 2022Review
- Delineation of the molecular determinants of the unique allosteric binding site of the orphan nuclear receptor RORγt.The Journal of biological chemistry · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The retinoic acid receptor-related orphan receptor (ROR) γt receptor is a member of nuclear receptors, which is indispensable for the expression of pro-inflammatory cytokine IL-17. RORγt has been established as a drug target to design and discover novel treatments for multiple inflammatory and immunological diseases. It is important to elucidate the molecular mechanisms of how RORγt is activated by an agonist, and how the transcription function of RORγt is interrupted by an inverse agonist. In this study we performed molecular dynamics simulations on four different RORγt systems, i.e., the apo protein, protein bound with agonist, protein bound with inverse agonist in the orthosteric-binding pocket, and protein bound with inverse agonist in the allosteric-binding pocket. We found that the orthosteric-binding pocket in the apo-form RORγt was mostly open, confirming that apo-form RORγt was constitutively active and could be readily activated (ca. tens of nanoseconds scale). The tracked data from MD simulations supported that RORγt could be activated by an agonist binding at the orthosteric-binding pocket, because the bound agonist helped to enhance the triplet His479-Tyr502-Phe506 interactions and stabilized H12 structure. The stabilized H12 helped RORγt to form the protein-binding site, and therefore made the receptor ready to recruit a coactivator molecule. We also showed that transcription function of RORγt could be interrupted by the binding of inverse agonist at the orthosteric-binding pocket or at the allosteric-binding site. After the inverse agonist was bound, H12 either structurally collapsed, or reorientated to a different position, at which the presumed protein-binding site was not able to be formed.
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.