Document Detail


Towards in silico identification of the human ether-a-go-go-related gene channel blockers: discriminative vs. generative classification models.
MedLine Citation:
PMID:  23152964     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
HERG potassium channels have a critical role in the normal electrical activity of the heart. The blockade of hERG channels in heart cells can result in a potentially fatal disorder called long QT syndrome. HERG channels can be blocked by compounds with diverse structures belonging to several drug classes. Presented herein are generative (Generative Topographic Maps) and discriminative (Support Vector Machines) classification models to categorize the compounds in silico into active and inactive classes by using different types of descriptors. The predictive performance of discriminative and generative classification models has been compared. Here, the possibility of using Generative Topographic Maps as an approach for applicability domain analysis and to generate probability-based descriptors was demonstrated to our knowledge for the first time. Comparison of obtained results with the models developed by other teams on the same data set has been performed.
Authors:
N Kireeva; S L Kuznetsov; A A Bykov; A Yu Tsivadze
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-16
Journal Detail:
Title:  SAR and QSAR in environmental research     Volume:  -     ISSN:  1029-046X     ISO Abbreviation:  SAR QSAR Environ Res     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9440156     Medline TA:  SAR QSAR Environ Res     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
a Frumkin Institute of Physical Chemistry and Electrochemistry RAS , Moscow , Russia.
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