Original paper

Journal of Computer-Aided Molecular Design

, Volume 21, Issue 4, pp 189-206

First online:

Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data

  • Claire L. GavaghanAffiliated withComputational Toxicology, Safety Assessment, AstraZeneca R&D Email author 
  • , Catrin Hasselgren ArnbyAffiliated withComputational Toxicology, Safety Assessment, AstraZeneca R&D
  • , Niklas BlombergAffiliated withGlobal DECS Computational Chemistry, AstraZeneca R&D
  • , Gert StrandlundAffiliated withLead Generation, AstraZeneca R&D
  • , Scott BoyerAffiliated withComputational Toxicology, Safety Assessment, AstraZeneca R&D

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Abstract

A ‘global’ model of hERG K+ channel was built to satisfy three basic criteria for QSAR models in drug discovery: (1) assessment of the applicability domain, (2) assuring that model decisions can be interpreted by medicinal chemists and (3) assessment of model performance after the model was built. A combination of D-optimal onion design and hierarchical partial least squares modelling was applied to construct a global model of hERG blockade in order to maximize the applicability domain of the model and to enhance its interpretability. Additionally, easily interpretable hERG specific fragment-based descriptors were developed. Model performance was monitored, throughout a time period of 15 months, after model implementation. It was found that after this time duration a greater proportion of molecules were outside the model’s applicability domain and that these compounds had a markedly higher average prediction error than those from molecules within the model’s applicability domain. The model’s predictive performance deteriorated within 4 months after building, illustrating the necessity of regular updating of global models within a drug discovery environment.

Keywords

hERG Hierarchical PLS modelling Onion design QSAR