title: Probability Based hERG Blocker Classifiers.
abstract: The US Food and Drug Administration (FDA) require in vitro human ether-a-go-go related (hERG) ion channel affinity tests for all drug candidates prior to clinical trials. In this study, probabilistic-based methods were employed to develop prediction models on hERG inhibition prediction, which are different from traditional QSAR models that are mainly based on supervised 'hard point' (HP) classification approaches giving 'yes/no' answers. The obtained models can 'ascertain' whether or not a given set of compounds can block hERG ion channels. The results presented indicate that the proposed probabilistic-based method can be a valuable tool for ranking compounds with respect to their potential cardio-toxicity and will be promising for other toxic property predictions.
authors.affiliation: State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, 15 Bei San Huan East Road, P.O. Box 53, Beijing 100029, P. R. China telephone: +86-10-64421335, fax: +86-10-64416428.
authors.forename: Zhi
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
authors.forename: Hamse Y
authors.initials: HY
authors.lastname: Mussa
authors.affiliation: Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
authors.forename: Robert
authors.initials: R
authors.lastname: Lowe
authors.affiliation: Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
authors.forename: Robert C
authors.initials: RC
authors.lastname: Glen
authors.affiliation: State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, 15 Bei San Huan East Road, P.O. Box 53, Beijing 100029, P. R. China telephone: +86-10-64421335, fax: +86-10-64416428. aixia_yan@yahoo.com, yanax@mail.buct.edu.cn.
authors.forename: Aixia
authors.initials: A
authors.lastname: Yan
keywords: Human ether-a-go-go related (hERG); Kernelised naive Bayes (KNB); Naive Bayes (NB); Parzen-window based model (PWM); Probabilistic classification