NDLI: Consensus QSAR model for identifying novel H5N1 inhibitors

Content Provider	Springer Nature Link
Author	Sharma, Nitin Yap, Chun Wei
Copyright Year	2012
Abstract	Due to the importance of neuraminidase in the pathogenesis of influenza virus infection, it has been regarded as the most important drug target for the treatment of influenza. Resistance to currently available drugs and new findings related to structure of the protein requires novel neuraminidase 1 (N1) inhibitors. In this study, a consensus QSAR model with defined applicability domain (AD) was developed using published N1 inhibitors. The consensus model was validated using an external validation set. The model achieved high sensitivity, specificity, and overall accuracy along with low false positive rate (FPR) and false discovery rate (FDR). The performance of model on the external validation set and training set were comparable, thus it was unlikely to be overfitted. The low FPR and low FDR will increase its accuracy in screening large chemical libraries. Screening of ZINC library resulted in 64,772 compounds as probable N1 inhibitors, while 173,674 compounds were defined to be outside the AD of the consensus model. The advantage of the current model is that it was developed using a large and diverse dataset and has a defined AD which prevents its use on compounds that it is not capable of predicting. The consensus model developed in this study is made available via the free software, PaDEL-DDPredictor.
Starting Page	513
Ending Page	524
Page Count	12
File Format	PDF
ISSN	13811991
Journal	Molecular Diversity
Volume Number	16
Issue Number	3
e-ISSN	1573501X
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-07-21
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Applicability domain Consensus model H5N1 In silico screening Inhibitors QSAR Organic Chemistry Biochemistry Pharmacy Polymer Sciences
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Medicine Drug Discovery Molecular Biology Physical and Theoretical Chemistry Information Systems Catalysis Inorganic Chemistry

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