3 years ago

Modeling of The hERG K+ Channel Blockage Using Online Chemical Database and Modeling Environment (OCHEM)

Modeling of The hERG K+ Channel Blockage Using Online Chemical Database and Modeling Environment (OCHEM)
Yong Zhao, Huanhuan Li, Xiao Li, Yuan Zhang
Human ether-a-go-go related gene (hERG) K+ channel plays an important role in cardiac action potential. Blockage of hERG channel may result in long QT syndrome (LQTS), even cause sudden cardiac death. Many drugs have been withdrawn from the market because of the serious hERG-related cardiotoxicity. Therefore, it is quite essential to estimate the chemical blockage of hERG in the early stage of drug discovery. In this study, a diverse set of 3721 compounds with hERG inhibition data was assembled from literature. Then, we make full use of the Online Chemical Modeling Environment (OCHEM), which supplies rich machine learning methods and descriptor sets, to build a series of classification models for hERG blockage. We also generated two consensus models based on the top-performing individual models. The consensus models performed much better than the individual models both on 5-fold cross validation and external validation. Especially, consensus model II yielded the prediction accuracy of 89.5 % and MCC of 0.670 on external validation. This result indicated that the predictive power of consensus model II should be stronger than most of the previously reported models. The 17 top-performing individual models and the consensus models and the data sets used for model development are available at https://ochem.eu/article/103592.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/minf.201700074

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.