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Aquatic Toxicology (Amsterdam, Netherlands)|May 1, 2010
Two farnesoid X receptor alpha isoforms in Japanese medaka (Oryzias latipes) are differentially activated in vitroDeanna L Howarth, Lee R Hagey, Sheran H W Law, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals|March 3, 2009
The major human pregnane X receptor (PXR) splice variant, PXR.2, exhibits significantly diminished ligand-activated transcriptional regulationYvonne S Lin, Kazuto Yasuda, Mahfoud Assem, et al.
Environmental Science & Technology|May 9, 2022
The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs)Adelene Lai, Alex M Clark, Beate I Escher, et al.
Journal of Molecular Graphics & Modelling|March 31, 2007
Flexible 3D pharmacophores as descriptors of dynamic biological spaceJames H Nettles, Jeremy L Jenkins, Chris Williams, et al.
Molecular Pharmacology|June 20, 2007
Human pregnane X receptor antagonists and agonists define molecular requirements for different binding sitesSean Ekins, Cheng Chang, Sridhar Mani, et al.
Molecular Pharmacology|December 2, 2020
Predicting Drug Interactions with Human Equilibrative Nucleoside Transporters 1 and 2 Using Functional Knockout Cell Lines and Bayesian ModelingSiennah R Miller, Xiaohong Zhang, Raymond K Hau, et al.
ACS Infectious Diseases|April 30, 2025
Cryo-EM Structure of HIV-1 Reverse Transcriptase with N-Phenyl-1-(phenylsulfonyl)-1H-1,2,4-triazol-3-amine: A New HIV-1 Non-nucleoside InhibitorMegan A Young, Thomas R Lane, Renuka Raman, et al.
Chemistry & Biology|March 26, 2013
Bayesian models leveraging bioactivity and cytotoxicity information for drug discoverySean Ekins, Robert C Reynolds, Hiyun Kim, et al.
Molecular Pharmaceutics|December 15, 2020
Enzyme Replacement Therapy for Mucopolysaccharidosis IIID using Recombinant Human α-N-Acetylglucosamine-6-Sulfatase in Neonatal MiceFeng Wang, Derek R Moen, Chelsee Sauni, et al.
Plos One|October 31, 2015
Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug DiscoverySean Ekins, Peter B Madrid, Malabika Sarker, et al.
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