ArticleCurrent topics in medicinal chemistry2014
Tuning HERG out: antitarget QSAR models for drug development.
Article in Current topics in medicinal chemistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed, 104 citations in OpenAlex.
- Modeling hERG Channel Liability: From Structural Insight to Highly Accurate Qualitative and Quantitative Models.Journal of chemical information and modeling · 2026Article
- Endocyclic Trisubstituted Hydroxylamine Isosteres of Basic Amines for ADME Modulation and Reduction of hERG Activity.ACS medicinal chemistry letters · 2026Article
- In-silico identification of COX-2 inhibitory phytochemicals from traditional medicinal plants: molecular docking, dynamics, and safety predictions.In silico pharmacology · 2025Article
- AttenhERG: a reliable and interpretable graph neural network framework for predicting hERG channel blockers.Journal of cheminformatics · 2024Article
- Effect of 3-hydrazinylquinoxaline-2-thiol hydrogel on skin wound healing process in diabetic rats.Scientific reports · 2024Article
- Enhancing hERG Risk Assessment with Interpretable Classificatory and Regression Models.Chemical research in toxicology · 2024Article
- Unveiling the Antiviral Capabilities of Targeting Human Dihydroorotate Dehydrogenase against SARS-CoV-2.ACS omega · 2024Article
- Aspergillus Species from the Sabkha Marsh: Potential Antimicrobial and Anticancer Agents Revealed Through Molecular and Pharmacological Analysis.Biologics : targets & therapy · 2024Article
- School of cheminformatics in Latin America.Journal of cheminformatics · 2023Article
- Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels.International journal of molecular sciences · 2023Review
- Discovery of new Schistosoma mansoni aspartyl protease inhibitors by structure-based virtual screening.Memorias do Instituto Oswaldo Cruz · 2023Article
- Toward Quantitative Models in Safety Assessment: A Case Study to Show Impact of Dose-Response Inference on hERG Inhibition Models.International journal of molecular sciences · 2022Article
- Article
- hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties.Chemistry (Basel, Switzerland) · 2022Article
- Interactions of selected cardiovascular active natural compounds with CXCR4 and CXCR7 receptors: a molecular docking, molecular dynamics, and pharmacokinetic/toxicity prediction study.BMC complementary medicine and therapies · 2022Article
- Further exploration of the structure-activity relationship of dual soluble epoxide hydrolase/fatty acid amide hydrolase inhibitors.Bioorganic & medicinal chemistry · 2021Article
- Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study.Journal of chemical information and modeling · 2021Article
- Prediction of arrhythmia susceptibility through mathematical modeling and machine learning.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Dihydroquinoline derivative as a potential anticancer agent: synthesis, crystal structure, and molecular modeling studies.Molecular diversity · 2021Article
- Evaluation of QSAR Equations for Virtual Screening.International journal of molecular sciences · 2020Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Several non-cardiovascular drugs have been withdrawn from the market due to their inhibition of hERG K+ channels that can potentially lead to severe heart arrhythmia and death. As hERG safety testing is a mandatory FDArequired procedure, there is a considerable interest for developing predictive computational tools to identify and filter out potential hERG blockers early in the drug discovery process. In this study, we aimed to generate predictive and well-characterized quantitative structure-activity relationship (QSAR) models for hERG blockage using the largest publicly available dataset of 11,958 compounds from the ChEMBL database. The models have been developed and validated according to OECD guidelines using four types of descriptors and four different machine-learning techniques. The classification accuracies discriminating blockers from non-blockers were as high as 0.83-0.93 on external set. Model interpretation revealed several SAR rules, which can guide structural optimization of some hERG blockers into non-blockers. We have also applied the generated models for screening the World Drug Index (WDI) database and identify putative hERG blockers and non-blockers among currently marketed drugs. The developed models can reliably identify blockers and non-blockers, which could be useful for the scientific community. A freely accessible web server has been developed allowing users to identify putative hERG blockers and non-blockers in chemical libraries of their interest (http://labmol.farmacia.ufg.br/predherg).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.