Journal
JOURNAL OF MEDICINAL CHEMISTRY
Volume 53, Issue 21, Pages 7573-7586Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jm100600y
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Funding
- NIH [GM066940, HG003898, U19MH82441]
- University of Jordan scholarship
- [ROIMH61887]
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Some antipsychotic drugs are known to cause valvular heart disease by activating serotonin 5-HT2B receptors. We have developed and validated binary classification QSAR models capable of predicting potential 5-HT2B actives. The classification accuracies of the models built to discriminate 5-HT2B 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-HT2B 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.
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