Experimentally Validated hERG Pharmacophore Models as Cardiotoxicity Prediction Tools

Kratz, Jadel M.; Schuster, Daniela; Edtbauer, Michael; Saxena, Priyanka; Mair, Christina E.; Kirchebner, Julia; Matuszczak, Barbara; Baburin, Igor; Hering, Steffen; Rollinger, Judith M.

doi:10.1021/ci5001955

Cited by 58 publications

(58 citation statements)

References 69 publications

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“…Those fragments offer particularly valuable information for the compound design and avoiding undesirable hERG activity. The authors have noted that the positive ionizable nitrogen is beneficial for ligand–hERG interaction, in agreement with Kratz's previous work on pharmacophore models, and that increased hydrophobicity is correlated with increased hERG binding. Although many prediction models of hERG blockers have been developed, there are still some problems, including the unclear mechanism of hERG inhibition and the uncertainty of experimental data.…”

Section: Computational Methods For Cbddsupporting

confidence: 86%

Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies

Zheng

Zhao

Chen

et al. 2018

Medicinal Research Reviews

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Over the past quarter of a century, there has been rapid development in structural biology, which now can provide solid evidence for understanding the functions of proteins. Concurrently, computational approaches with particular relevance to the chemical biology and drug design (CBDD) field have also incrementally and steadily improved. Today, these methods help elucidate detailed working mechanisms and accelerate the discovery of new chemical modulators of proteins. In recent years, integrating computational simulations and predictions with experimental validation has allowed for more effective explorations of the structure, function and modulation of important therapeutic targets. In this review, we summarize the main advancements in computational methodology development, which are then illustrated by several successful applications in CBDD. Finally, we conclude with a discussion of the current major challenges and future directions in the field.

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Section: Computational Methods For Cbddsupporting

confidence: 86%

Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies

Zheng

Zhao

Chen

et al. 2018

Medicinal Research Reviews

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“…c), where the aromatic interactions are like the handle and the nitrogen feature is placed along the length of the plug. Kratz et al . constructed a pharmacophore model (Fig.…”

Section: Small Molecule Features and Herg Blockadementioning

confidence: 99%

“…A large number of studies 14,42,47,51,[126][127][128] have reported different pharmacophore features of hERG blockers and computational predictive models based on the structure properties r KALYAANAMOORTHY AND BARAKAT of the ligands. Some of the previously reported predictive models are summarized in Table III.…”

Section: A Pharmacophore and Sar Modelsmentioning

confidence: 99%

Development of Safe Drugs: The hERG Challenge

Kalyaanamoorthy

Barakat

2017

Medicinal Research Reviews

119

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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.

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“…Recently, Kratz et al [45] reported a study using the combination of two pharmacophore methods: Catalyst (Accelrys Software Inc.) and LigandScout [46]. Ten Catalyst models were built based on 18 hERG inhibitors and validated using a set of 19 inhibitors, Table 2.…”

Section: Pharmacophore Modelsmentioning

confidence: 99%

In Silico Prediction of hERG Inhibition

et al. 2015

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The voltage-gated potassium channel encoded by hERG carries a delayed rectifying potassium current (IKr) underlying repolarization of the cardiac action potential. Pharmacological blockade of the hERG channel results in slowed repolarization and therefore prolongation of action potential duration and an increase in the QT interval as measured on an electrocardiogram. Those are possible to cause sudden death, leading to the withdrawals of many drugs, which is the reason for hERG screening. Computational in silico prediction models provide a rapid, economic way to screen compounds during early drug discovery. In this review, hERG prediction models are classified as 2D and 3D quantitative structure-activity relationship models, pharmacophore models, classification models, and structure based models (using homology models of hERG).

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Experimentally Validated hERG Pharmacophore Models as Cardiotoxicity Prediction Tools

Cited by 58 publications

References 69 publications

Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies

Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies

Development of Safe Drugs: The hERG Challenge

In Silico Prediction of hERG Inhibition

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