International Journal of Molecular Sciences · 2014 · 39 citations · 35 references
ImmunologyLiver SteatosisPparγ Full AgonistsSystem PharmacologyFatty Liver DiseasePharmacodynamic ModelingPre-clinical PharmacologyTranslational PharmacologySystems PharmacologyMetabolic SyndromeMolecular PharmacologyHepatotoxicityHealth SciencesSystems BiologyPharmacokinetic ModelingBiochemistryLiver PhysiologyReceptor (Biochemistry)Mechanism Of ActionPparγ ReceptorPharmacologyMolecular ModelingDrug-induced Liver InjuryAdverse Outcome PathwayMolecular Modelling StudyHepatologyPparγ ComplexesLiver DiseasePparγ ActivationMedicineDrug DiscoveryQuantitative Pharmacology
The comprehensive understanding of the precise mode of action and/or adverse outcome pathway (MoA/AOP) of chemicals has become a key step toward the development of a new generation of predictive toxicology tools. One of the challenges of this process is to test the feasibility of the molecular modelling approaches to explore key molecular initiating events (MIE) within the integrated strategy of MoA/AOP characterisation. The description of MoAs leading to toxicity and liver damage has been the focus of much interest. Growing evidence underlines liver PPARγ ligand-dependent activation as a key MIE in the elicitation of liver steatosis. Synthetic PPARγ full agonists are of special concern, since they may trigger a number of adverse effects not observed with partial agonists. In this study, molecular modelling was performed based on the PPARγ complexes with full agonists extracted from the Protein Data Bank. The receptor binding pocket was analysed, and the specific ligand-receptor interactions were identified for the most active ligands. A pharmacophore model was derived, and the most important pharmacophore features were outlined and characterised in relation to their specific role for PPARγ activation. The results are useful for the characterisation of the chemical space of PPARγ full agonists and could facilitate the development of preliminary filtering rules for the effective virtual ligand screening of compounds with PPARγ full agonistic activity.
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Helen M. Berman · Nucleic Acids Research · 2000 · 38.9K citations
Biological Database, Biochemistry, Structural Bioinformatics +12
ChEMBL: a large-scale bioactivity database for drug discovery
Anna Gaulton, Louisa J. Bellis, A. Patrícia Bento et al. · Nucleic Acids Research · 2011 · 4.3K citations · Full text
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Vikas Chandra, Pengxiang Huang, Srilatha Raghuram et al. · Nature · 2008 · 809 citations · Full text
Nucleic Acid Chemistry, Nuclear Structure, Natural Sciences +8