ArticleMolecular pharmaceutics2012
ADMET evaluation in drug discovery. 12. Development of binary classification models for prediction of hERG potassium channel blockage.
Article in Molecular pharmaceutics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed, 170 citations in OpenAlex.
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- An in silico approach to peptide-based dual-receptor targeting for IL13RA2 and VEGFR-2 extracellular domain.Journal of molecular modeling · 2026Article
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- Novel Crown Ether-Functionalized Fusidic Acid Butyl Ester: Synthesis, Biological Evaluation, In Silico ADMET, and Molecular Docking Studies.Molecules (Basel, Switzerland) · 2025Article
- Exploring Erythrina flavonoids as potential SARS-CoV-2 RdRp inhibitors through virtual screening, in silico ADMET evaluation, and molecular dynamics simulation studies.Scientific reports · 2025Article
- [Mechanism of Cnidii Fructus in the treatment of periodontitis with osteoporosis based on network pharmacology, molecular docking, and molecular dynamics simulation].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2025Article
- Pyrazinamide-based Co(II), Ni(II) and Cu(II) complexes: DFT exploration of structure, reactivity properties and in silico ADMET profiles.Journal of molecular modeling · 2024Article
- Modification of ibuprofen to improve the medicinal effect; structural, biological, and toxicological study.Heliyon · 2024Article
- Review of machine learning and deep learning models for toxicity prediction.Experimental biology and medicine (Maywood, N.J.) · 2023Review
- TargIDe: a machine-learning workflow for target identification of molecules with antibiofilm activity against Pseudomonas aeruginosa.Journal of computer-aided molecular design · 2023Article
- Virtual screening of DrugBank database for hERG blockers using topological Laplacian-assisted AI models.Computers in biology and medicine · 2023Article
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Inhibition of the human ether-a-go-go related gene (hERG) potassium channel may result in QT interval prolongation, which causes severe cardiac side effects and is a major problem in clinical studies of drug candidates. The development of in silico tools to filter out potential hERG potassium channel blockers in early stages of the drug discovery process is of considerable interest. Here, a diverse set of 806 compounds with hERG inhibition data was assembled, and the binary hERG classification models using naive Bayesian classification and recursive partitioning (RP) techniques were established and evaluated. The naive Bayesian classifier based on molecular properties and the ECFP_8 fingerprints yielded 84.8% accuracy for the training set using the leave-one-out (LOO) cross-validation procedure and 85% accuracy for the test set of 120 molecules. For the two additional test sets, the model achieved 89.4% accuracy for the WOMBAT-PK test set, and 86.1% accuracy for the PubChem test set. The naive Bayesian classifiers gave better predictions than the RP classifiers. Moreover, the Bayesian classifier, employing molecular fingerprints, highlights the important structural fragments favorable or unfavorable for hERG potassium channel blockage, which offers extra valuable information for the design of compounds avoiding undesirable hERG activity.
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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.