Linked Life Data

19673539

Source:http://linkedlifedata.com/resource/pubmed/id/19673539

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2009-10-5
pubmed:abstractText
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.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1543-8384
pubmed:author
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1591-603
pubmed:dateRevised
2010-12-3
pubmed:meshHeading
pubmed-meshheading:19673539-Animals, pubmed-meshheading:19673539-Artificial Intelligence, pubmed-meshheading:19673539-Bayes Theorem, pubmed-meshheading:19673539-Bile Acids and Salts, pubmed-meshheading:19673539-Calcium Channel Blockers, pubmed-meshheading:19673539-Cell Line, pubmed-meshheading:19673539-Colonic Neoplasms, pubmed-meshheading:19673539-Diuretics, pubmed-meshheading:19673539-Dogs, pubmed-meshheading:19673539-Drug Discovery, pubmed-meshheading:19673539-Drug Evaluation, Preclinical, pubmed-meshheading:19673539-Humans, pubmed-meshheading:19673539-Hydroxymethylglutaryl-CoA Reductase Inhibitors, pubmed-meshheading:19673539-Intestinal Absorption, pubmed-meshheading:19673539-Models, Biological, pubmed-meshheading:19673539-Models, Molecular, pubmed-meshheading:19673539-Models, Statistical, pubmed-meshheading:19673539-Organic Anion Transporters, Sodium-Dependent, pubmed-meshheading:19673539-Quantitative Structure-Activity Relationship, pubmed-meshheading:19673539-Recombinant Proteins, pubmed-meshheading:19673539-Risk Factors, pubmed-meshheading:19673539-Symporters, pubmed-meshheading:19673539-Transfection
pubmed:articleTitle
Computational models for drug inhibition of the human apical sodium-dependent bile acid transporter.
pubmed:affiliation
Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, 20 Penn Street, Baltimore, Maryland 21201, USA.
pubmed:publicationType
Journal Article, In Vitro, Research Support, N.I.H., Extramural