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Eur J Med Chem. 2011 Feb;46(2):618-30. doi: 10.1016/j.ejmech.2010.11.042. Epub 2010 Dec 8.

Predicting hERG activities of compounds from their 3D structures: development and evaluation of a global descriptors based QSAR model.

Author information

1
Molecular Modeling Section, Biolab, Chembiotek, TCG Lifesciences Ltd., Bengal Intelligent Park, Tower-B, 2nd Floor, Block-EP & GP, Sector-V, Salt Lake Electronic Complex, Calcutta-700091, India. nandita@chembiotek.com

Abstract

A QSAR based predictive model of hERG activity in terms of 'global descriptors' has been developed and evaluated. The QSAR was developed by training 77 compounds covering a wide range of activities and was validated based on an external 'test set' of 80 compounds using neural network method. Statistical parameters and examination of enrichment factor indicated the effectiveness of the present model. Randomization test demonstrated the robustness of the model and cross-validation test further validated the QSAR. Domain of applicability test indicated to the high degree of reliability of the predicted results. Satisfactory performance in classifying compounds into 'active' and 'inactive' groups was also obtained. The cases where the QSAR failed, the possible sources of errors have been discussed.

PMID:
21185626
DOI:
10.1016/j.ejmech.2010.11.042
[Indexed for MEDLINE]

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