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• W2264043469 abstract "A series of 172 molecular structures that block the hERG K+ channel were used to develop a classification model where, initially, eight types of PaDEL fingerprints were used for k-nearest neighbor model development. A consensus model constructed using Extended-CDK, PubChem and Substructure count fingerprint-based models was found to be a robust predictor of hERG activity. This consensus model demonstrated sensitivity and specificity values of 0.78 and 0.61 for the internal dataset compounds and 0.63 and 0.54 for the external (PubChem) dataset compounds, respectively. This model has identified the highest number of true positives (i.e. 140) from the PubChem dataset so far, as compared to other published models, and can potentially serve as a basis for the prediction of hERG active compounds. Validating this model against FDA-withdrawn substances indicated that it may even be useful for differentiating between mechanisms underlying QT prolongation." @default.
• W2264043469 created "2016-06-24" @default.
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• W2264043469 date "2016-02-10" @default.
• W2264043469 modified "2023-10-16" @default.
• W2264043469 title "A k-nearest neighbor classification of hERG K+ channel blockers" @default.
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• W2264043469 doi "https://doi.org/10.1007/s10822-016-9898-z" @default.
• W2264043469 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4802000" @default.
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