Abstract
Some antipsychotic drugs are known to cause valvular heart disease by activating serotonin 5-HT(2B) receptors. We have developed and validated binary classification QSAR models capable of predicting potential 5-HT(2B) actives. The classification accuracies of the models built to discriminate 5-HT(2B) actives from the inactives were as high as 80% for the external test set. These models were used to screen in silico 59,000 compounds included in the World Drug Index, and 122 compounds were predicted as actives with high confidence. Ten of them were tested in radioligand binding assays and nine were found active, suggesting a success rate of 90%. All validated actives were then tested in functional assays, and one compound was identified as a true 5-HT(2B) agonist. We suggest that the QSAR models developed in this study could be used as reliable predictors to flag drug candidates that are likely to cause valvulopathy.
Publication types
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Research Support, N.I.H., Extramural
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms
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Binding, Competitive
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Databases, Factual
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Dexfenfluramine / adverse effects
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Dexfenfluramine / chemistry
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Dexfenfluramine / metabolism
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Drug-Related Side Effects and Adverse Reactions
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Fenfluramine / adverse effects
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Fenfluramine / chemistry
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Fenfluramine / metabolism
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Heart Valve Diseases / chemically induced*
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Ligands
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Models, Molecular*
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Pharmaceutical Preparations / chemistry*
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Pharmaceutical Preparations / metabolism
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Quantitative Structure-Activity Relationship*
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Radioligand Assay
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Receptor, Serotonin, 5-HT2B / chemistry*
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Receptor, Serotonin, 5-HT2B / metabolism
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Serotonin 5-HT2 Receptor Agonists / adverse effects
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Serotonin 5-HT2 Receptor Agonists / chemistry*
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Serotonin 5-HT2 Receptor Agonists / metabolism
Substances
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Ligands
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Pharmaceutical Preparations
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Receptor, Serotonin, 5-HT2B
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Serotonin 5-HT2 Receptor Agonists
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Fenfluramine
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Dexfenfluramine