ArticleEuropean journal of medicinal chemistry2012
First chemical feature-based pharmacophore modeling of potent retinoidal retinoic acid metabolism blocking agents (RAMBAs): identification of novel RAMBA scaffolds.
Article in European journal of medicinal chemistry, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The discovery of a new nonbile acid modulator of Takeda G protein-coupled receptor 5: An integrated computational approach.Archiv der Pharmazie · 2025Article
- Retinol Depletion in COVID-19.Clinical nutrition open science · 2022Article
- Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics.International journal of molecular sciences · 2021Article
- Retinoic Acid and Its Derivatives in Skin.Cells · 2020Review
- Human cytochrome P450 enzymes 5-51 as targets of drugs and natural and environmental compounds: mechanisms, induction, and inhibition - toxic effects and benefits.Drug metabolism reviews · 2018Review
- Comparison of the ligand binding site of CYP2C8 with CYP26A1 and CYP26B1: a structural basis for the identification of new inhibitors of the retinoic acid hydroxylases.Journal of enzyme inhibition and medicinal chemistry · 2016Article
- Establishment of a screening protocol for identification of aminopeptidase N inhibitors.Journal of the Taiwan Institute of Chemical Engineers · 2015Article
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Authors and funding
5 authors.
Funding
Abstract
The first three-dimensional (3D) pharmacophore model was developed for potent retinoidal retinoic acid metabolism blocking agents (RAMBAs) with IC(50) values ranging from 0.0009 to 5.84nM. The seven common chemical features in these RAMBAs as deduced by the Catalyst/HipHop program include five hydrophobic groups (hydrophobes), and two hydrogen bond acceptors. Using the pharmacophore model as a 3D search query against NCI and Maybridge conformational Catalyst formatted databases; we retrieved several compounds with different structures (scaffolds) as hits. Twenty-one retrieved hits were tested for RAMBA activity at 100nM concentration. The most potent of these compounds, NCI10308597 and HTS01914 showed inhibitory potencies less (54.7% and 53.2%, respectively, at 100nM) than those of our best previously reported RAMBAs VN/12-1 and VN/14-1 (90% and 86%, respectively, at 100nM). Docking studies using a CYP26A1 homology model revealed that our most potent RAMBAs showed similar binding to the one observed for a series of RAMBAs reported previously by others. Our data shows the potential of our pharmacophore model in identifying structurally diverse and potent RAMBAs. Further refinement of the model and searches of other robust databases is currently in progress with a view to identifying and optimizing new leads.
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