In silico structure-based models of hERG are being developed to predict drug affinity and avoid off-target interactions, though ambiguities in binding modes remain a significant challenge.
Drug-induced blockade of human ether-a-go-go-related gene (hERG) remains a major impediment in delivering safe drugs to the market. Several drugs have been withdrawn from the market due to their severe cardiotoxic side effects triggered by their off-target interactions with hERG. Thus, identifying the potential hERG blockers at early stages of lead discovery is fast evolving as a standard in drug design and development. A number of in silico structure-based models of hERG have been developed as a low-cost solution to evaluate drugs for hERG liability, and it is now agreed that the hERG blockers bind at the large central cavity of the channel. Nevertheless, there is no clear convergence on the appropriate drug binding modes against the channel. The proposed binding modes differ in their orientations and interpretations on the role of key residues in the channel. Such ambiguities in the modes of binding remain to be a significant challenge in achieving efficient computational predictive models and in saving many important already Food and Drug Administration approved drugs. In this review, we discuss the spectrum of reported binding modes for hERG blockers, the various in silico models developed for predicting a drug's affinity to hERG, and the known successful optimization strategies to avoid off-target interactions with hERG.
Kalyaanamoorthy et al. (Wed,) conducted a review in Drug-induced hERG blockade and cardiotoxicity. In silico structure-based models of hERG was evaluated. In silico structure-based models of hERG are being developed to predict drug affinity and avoid off-target interactions, though ambiguities in binding modes remain a significant challenge.
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