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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 Several drugs have been withdrawn from the market due to their severe cardiotoxic side effects triggered by their off-target interactions with hERG.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.
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 Several drugs have been withdrawn from the market due to their severe cardiotoxic side effects triggered by their off-target interactions with hERG.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.
The pharmacophore modeling in modern drug research has been applied for both bioactivity profiling and early stage of risk assessment of potential side effects and toxicity due to interactions of drug candidates with antitargets namely P-glycoprotein, hERG, cytochrome P450 and pregnane X-receptor. In this article, an existing state concerning with pharmacophore modeling applied for promiscuous proteins in drug research were updated and reviewed. In an attempt to create new safe medicines faster, the partial overlap of substrate properties of hERG, P-glycoprotein, pregnane X-receptor and cytochrome P450 has to be considered and drug safety has to be dealt on a system level on the off-targets.
This chapter is a comprehensive account of the medicinal chemistry of antihypertensive drugs, Ca2+-channel blockers (CCBs). It provides the mechanism of drug action and detailed structure-activity relationships (SAR) of the CCBs to give the knowledge base for pharmacists. After studying this chapter, students will be able to: • Comprehend the historical background of the CCBs. • Classify different types of voltage-gated Ca2+ channels (VGCCs) and their clinical significance. • Explain CCBs and their clinical significance. • Describe the mechanisms of action of CCBs at the molecular level including their binding modes against the VGCCs. • Describe the SAR of the different classes of CCBs. • Delineate clinical significance and therapeutic evaluations of these classes of drugs by solving case studies. • Articulate the discovery process of a few CCBs.
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