PMID- 27477818
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20160802
LR  - 20160801
IS  - 1868-1743 (Print)
IS  - 1868-1743 (Linking)
VI  - 31
IP  - 9
DP  - 2012 Sep
TI  - Probability Based hERG Blocker Classifiers.
PG  - 679-85
LID - 10.1002/minf.201200011 [doi]
AB  - 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.
CI  - Copyright (c) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
FAU - Wang, Zhi
AU  - Wang Z
AD  - 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.
FAU - Mussa, Hamse Y
AU  - Mussa HY
AD  - Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, 
      University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
FAU - Lowe, Robert
AU  - Lowe R
AD  - Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, 
      University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
FAU - Glen, Robert C
AU  - Glen RC
AD  - Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, 
      University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
FAU - Yan, Aixia
AU  - Yan A
AD  - 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.
LA  - eng
PT  - Journal Article
DEP - 20120907
PL  - Germany
TA  - Mol Inform
JT  - Molecular informatics
JID - 101529315
OTO - NOTNLM
OT  - Human ether-a-go-go related (hERG)
OT  - Kernelised naive Bayes (KNB)
OT  - Naive Bayes (NB)
OT  - Parzen-window based model (PWM)
OT  - Probabilistic classification
EDAT- 2012/09/01 00:00
MHDA- 2012/09/01 00:01
CRDT- 2016/08/02 06:00
PHST- 2012/02/02 00:00 [received]
PHST- 2012/07/03 00:00 [accepted]
PHST- 2016/08/02 06:00 [entrez]
PHST- 2012/09/01 00:00 [pubmed]
PHST- 2012/09/01 00:01 [medline]
AID - 10.1002/minf.201200011 [doi]
PST - ppublish
SO  - Mol Inform. 2012 Sep;31(9):679-85. doi: 10.1002/minf.201200011. Epub 2012 Sep 7.