ArticleScientific reports2020
A structure-based computational workflow to predict liability and binding modes of small molecules to hERG.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Advancing Medicinal Chemistry Through FMO: Sygnature's Platform.Methods in molecular biology (Clifton, N.J.) · 2026Article
- hERG toxicity prediction in early drug discovery using extreme gradient boosting and isometric stratified ensemble mapping.Scientific reports · 2025Article
- CardioGenAI: a machine learning-based framework for re-engineering drugs for reduced hERG liability.Journal of cheminformatics · 2025Article
- Role of CSF1R 550th-tryptophan in kusunokinin and CSF1R inhibitor binding and ligand-induced structural effect.Scientific reports · 2024Article
- Applications of Molecular Dynamics Simulations in Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Structural modeling of hERG channel-drug interactions using Rosetta.Frontiers in pharmacology · 2023Article
- hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties.Chemistry (Basel, Switzerland) · 2022Article
- Use of Solvent Mapping for Characterizing the Binding Site and for Predicting the Inhibition of the Human Ether-á-Go-Go-Related KChemical research in toxicology · 2022Article
- Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study.Journal of chemical information and modeling · 2021Article
- Molecular Dynamics-Derived Pharmacophore Model Explaining the Nonselective Aspect of KInternational journal of molecular sciences · 2021Article
- Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations.Journal of chemical information and modeling · 2020Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Off-target interactions of drugs with the human ether-à-go-go related gene 1 (hERG1) channel have been associated with severe cardiotoxic conditions leading to the withdrawal of many drugs from the market over the last decades. Consequently, predicting drug-induced hERG-liability is now a prerequisite in any drug discovery campaign. Understanding the atomic level interactions of drug with the channel is essential to guide the efficient development of safe drugs. Here we utilize the recent cryo-EM structure of the hERG channel and describe an integrated computational workflow to characterize different drug-hERG interactions. The workflow employs various structure-based approaches and provides qualitative and quantitative insights into drug binding to hERG. Our protocol accurately differentiated the strong blockers from weak and revealed three potential anchoring sites in hERG. Drugs engaging in all these sites tend to have high affinity towards hERG. Our results were cross-validated using a fluorescence polarization kit binding assay and with electrophysiology measurements on the wild-type (WT-hERG) and on the two hERG mutants (Y652A-hERG and F656A-hERG), using the patch clamp technique on HEK293 cells. Finally, our analyses show that drugs binding to hERG disrupt and hijack certain native-structural networks in the channel, thereby, gaining more affinity towards hERG.
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