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A k-nearest neighbor classification of hERG K+ channel blockers
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (BBCL)ORCID iD: 0000-0003-4158-4148
eADMET GmbH, Germany.
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (BBCL)
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Uppsala University. (BBCL;Linnaeus Ctr Biomat Chem, BMC)ORCID iD: 0000-0002-0407-6542
2016 (English)In: Journal of Computer-Aided Molecular Design, ISSN 0920-654X, E-ISSN 1573-4951, Vol. 30, no 3, p. 229-236Article in journal (Refereed) Published
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Text
Abstract [en]

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 Validating this model against FDA-withdrawn substances indicated that it may even be useful for differentiating between mechanisms underlying QT prolongation.

Place, publisher, year, edition, pages
2016. Vol. 30, no 3, p. 229-236
Keywords [en]
Classification model, hERG blockers, Ikr, KCNH2, k-nearest neighbor (k-NN), Toxicity
National Category
Bioinformatics (Computational Biology)
Research subject
Chemistry, Medical Chemistry
Identifiers
URN: urn:nbn:se:lnu:diva-52222DOI: 10.1007/s10822-016-9898-zISI: 000373117200004PubMedID: 26860111Scopus ID: 2-s2.0-84957695003OAI: oai:DiVA.org:lnu-52222DiVA, id: diva2:922758
Available from: 2016-04-25 Created: 2016-04-25 Last updated: 2018-11-02Bibliographically approved

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Chavan, SwapnilWiklander, Jesper G.Nicholls, Ian A.

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