ArticleJournal of molecular modeling2023
Structural requirement of RARγ agonism through computational aspects.
Article in Journal of molecular modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Targeting the JAK/STAT signalling axis in cancer: chemopreventive potential of natural compounds with emerging focus on retinoids.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- A Comprehensive Review of Acne Treatments: Unpacking the Chemical Structures and Effective Bioactive Compounds.Health science reports · 2026Article
- P18: Novel Anticancer Peptide from Induced Tumor-Suppressing Cells Targeting Breast Cancer and Bone Metastasis.Cancers · 2024Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
contextRARγ is a therapeutic target for many skin diseases and has potential in cancer treatment. In the current study, we put forward a comprehensive structure-activity relationship study of third and fourth generations of RARγ agonists, addressing multiple crystal structures of RARγ complexes and approved drugs. Adapalene and Trifarotene, through hybrid strategies including protein contacts Atlas analysis, molecular docking, dynamics simulations, MM-GBSA, ASM, and pharmacophore modeling. Our result revealed crucial amino acids Arg267, Ser278, Phe288, Phe230, Met272, Leu271, and Leu268 within the RARγ pocket, as well as pharmacophore features such as two hydrophobic groups, two aromatic rings, and negative ionic features, which are essential for the binding of RARγ agonists. Based on this study, the binding mechanism of RARγ agonists was elucidated, which will be helpful for the rational design of new RARγ agonists for skin diseases and cancer treatment.
methodsIn this study, Schrödinger suite 2021-2 with OPLS_4 force field, Discovery Studio program 3.0, LigandScout 4.3, and PyMOL are utilized in the investigation.
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Registered trials
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