ArticleMolecular pharmaceutics
Computational models for drug inhibition of the human apical sodium-dependent bile acid transporter.
Article in Molecular pharmaceutics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed, 92 citations in OpenAlex.
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- The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach.Frontiers in cell and developmental biology · 2021Article
- Current Models for Predicting Drug-induced Cholestasis: The Role of Hepatobiliary Transport System.Iranian journal of pharmaceutical research : IJPR · 2021Review
- Identification prognosis-associated immune genes in colon adenocarcinoma.Bioscience reports · 2020Article
- Bile acid transporter-mediated oral drug delivery.Journal of controlled release : official journal of the Controlled Release Society · 2020Review
- Apical Sodium-Dependent Bile Acid Cotransporter, A Novel Transporter of Indocyanine Green, and Its Application in Drug Screening.International journal of molecular sciences · 2020Article
- A multiparametric organ toxicity predictor for drug discovery.Toxicology mechanisms and methods · 2020Article
- Repurposing Approved Drugs as Inhibitors of KPharmaceutical research · 2019Article
- AMagma (New York, N.Y.) · 2019Review
- Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.Molecular pharmaceutics · 2018Article
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- Organic solute transporter OSTα/β is overexpressed in nonalcoholic steatohepatitis and modulated by drugs associated with liver injury.American journal of physiology. Gastrointestinal and liver physiology · 2018Article
- Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.Molecular pharmaceutics · 2017Article
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- Using Multi-fluorinated Bile Acids and In Vivo Magnetic Resonance Imaging to Measure Bile Acid Transport.Journal of visualized experiments : JoVE · 2016Article
- The Next Era: Deep Learning in Pharmaceutical Research.Pharmaceutical research · 2016Review
- Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses.Journal of chemical information and modeling · 2016Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The human apical sodium-dependent bile acid transporter (ASBT; SLC10A2) is the primary mechanism for intestinal bile acid reabsorption. In the colon, secondary bile acids increase the risk of cancer. Therefore, drugs that inhibit ASBT have the potential to increase the risk of colon cancer. The objectives of this study were to identify FDA-approved drugs that inhibit ASBT and to derive computational models for ASBT inhibition. Inhibition was evaluated using ASBT-MDCK monolayers and taurocholate as the model substrate. Computational modeling employed a HipHop qualitative approach, a Hypogen quantitative approach, and a modified Laplacian Bayesian modeling method using 2D descriptors. Initially, 30 compounds were screened for ASBT inhibition. A qualitative pharmacophore was developed using the most potent 11 compounds and applied to search a drug database, yielding 58 hits. Additional compounds were tested, and their K(i) values were measured. A 3D-QSAR and a Bayesian model were developed using 38 molecules. The quantitative pharmacophore consisted of one hydrogen bond acceptor, three hydrophobic features, and five excluded volumes. Each model was further validated with two external test sets of 30 and 19 molecules. Validation analysis showed both models exhibited good predictability in determining whether a drug is a potent or nonpotent ASBT inhibitor. The Bayesian model correctly ranked the most active compounds. In summary, using a combined in vitro and computational approach, we found that many FDA-approved drugs from diverse classes, such as the dihydropyridine calcium channel blockers and HMG CoA-reductase inhibitors, are ASBT inhibitors.
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