ArticleJournal of molecular modeling2025
Structural insights into molecular and cellular level FXR binding potentials of GW4064 and LY2562175 hybrids by multi in silico modelling analyses.
Article in Journal of molecular modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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
2 citing papers in PubMed.
- The Bile Acid Signaling Axis: Deciphering the Roles of FXR and TGR5 in Hepatic Steatosis, Fibrosis, and Cancer.Pharmacology research & perspectives · 2026Review
- MicroRNA: unveiling novel mechanistic and theranostic pathways in diabetic cardiomyopathy.Frontiers in pharmacology · 2025Review
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.
Funding
Abstract
contextNon-alcoholic fatty liver disease (NAFLD) has become a significant health concern. Existing farnesoid X receptor (FXR) agonists like GW4064 and LYS2562175 show poor pharmacokinetics, prompting researchers to develop alternative molecules. This study aims to pinpoint the structural features responsible for exhibiting FXR agonism of a series of hybrid structures of GW4064 and LYS2562175 with improved pharmacokinetic properties which supersede the existing parent ligands. Electronegative components were found to critically influence biological activity on the molecular level, supported by 2D- and 3D-Quantitative Structure Activity Relationship (2D- and 3D-QSAR) analyses. Quantitative Activity-Activity Relationship (QAAR) highlighted key descriptors impacting cellular level FXR binding potential. Molecular dynamics (MD) simulations identified pivotal interactions, such as π-π and H-bond interactions with key residues. Furthermore, binding free energy calculated with Molecular Mechanics with Generalised Born and Surface Area solvation (MM-GBSA) analyses with selected compounds reflected the variations in their binding potential towards FXR protein.
methodsThe study began by curating ligand SMILES and preparing a dataset with molecular and cellular activity as dependent variables. AlvaDesc descriptors and interpretable descriptors were calculated using the OCHEM webserver. QSAR analyses were performed using Sequential Forward Selection (SFS) and Genetic Algorithm (GA) methods, while QAAR analysis used 50% effective concentration at the molecular level as an independent variable with the same algorithms. 3D QSAR analysis was performed with the Open3DQSAR tool. Docking studies in AutoDock 4.2 with FXR protein identified optimal ligand poses, and 500 ns MD simulations were performed with Amber 20. The use of open-access tools ensures reproducibility and accessibility for future research.
Indexed as
Identifiers
40095214What 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.