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hERG Me Out

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/1439-7633(20020503)3:5<455::aid-cbic455>3.0.co;2-lopenalex-snapshot

A Virtual Screening Method for Prediction of the hERG Potassium Channel Liability of Compound Libraries

inferredcites →https://doi.org/10.1002/cmdc.200500047openalex-snapshot

An Accurate and Interpretable Bayesian Classification Model for Prediction of hERG Liability

inferredcites →https://doi.org/10.1002/cmdc.200700221openalex-snapshot

A Composite Model for hERG Blockade

inferredcites →https://doi.org/10.1002/cmdc.200900374openalex-snapshot

The hERG Potassium Channel and Drug Trapping: Insight from Docking Studies with Propafenone Derivatives

inferredcites →https://doi.org/10.1002/cmdc.201000024openalex-snapshot

Prospective Validation of a Comprehensive In silico hERG Model and its Applications to Commercial Compound and Drug Databases

inferredcites →https://doi.org/10.1002/minf.201000159openalex-snapshot

Development and Comparison of hERG Blocker Classifiers: Assessment on Different Datasets Yields Markedly Different Results

inferredcites →https://doi.org/10.1002/minf.201200059openalex-snapshot

Annotating Human P‐Glycoprotein Bioassay Data

inferredcites →https://doi.org/10.1007/s002280100290openalex-snapshot

Organising evidence on QT prolongation and occurrence of Torsades de Pointes with non-antiarrhythmic drugs: a call for consensus

inferredcites →https://doi.org/10.1007/s11030-009-9117-0openalex-snapshot

Similarity-based SIBAR descriptors for classification of chemically diverse hERG blockers

inferredcites →https://doi.org/10.1016/0014-5793(96)00355-9openalex-snapshot

Blockade of HERG channels expressed in Xenopus oocytes by the histamine receptor antagonists terfenadine and astemizole

inferredcites →https://doi.org/10.1016/j.asoc.2010.09.010openalex-snapshot

Prediction of the hERG potassium channel inhibition potential with use of artificial neural networks

inferredcites →https://doi.org/10.1016/j.bmc.2004.02.003openalex-snapshot

A model for identifying HERG K+ channel blockers

inferredcites →https://doi.org/10.1016/j.bmc.2005.12.030openalex-snapshot

Prediction of hERG potassium channel affinity by the CODESSA approach

inferredcites →https://doi.org/10.1016/j.bmc.2006.03.043openalex-snapshot

Determination of hERG channel blockers using a decision tree

inferredcites →https://doi.org/10.1016/j.bmc.2008.04.028openalex-snapshot

Support vector machines classification of hERG liabilities based on atom types

inferredcites →https://doi.org/10.1016/j.bmcl.2005.03.062openalex-snapshot

Predictive models for hERG potassium channel blockers

inferredcites →https://doi.org/10.1016/j.bmcl.2005.03.080openalex-snapshot

A discriminant model constructed by the support vector machine method for HERG potassium channel inhibitors

inferredcites →https://doi.org/10.1016/j.bmcl.2011.07.006openalex-snapshot

Novel and highly potent histamine H3 receptor ligands. Part 1: withdrawing of hERG activity

inferredcites →https://doi.org/10.1016/s0014-5793(97)01249-0openalex-snapshot

A mechanism for the proarrhythmic effects of cisapride (Propulsid): high affinity blockade of the human cardiac potassium channel HERG

inferredcites →https://doi.org/10.1016/s0960-894x(03)00196-3openalex-snapshot

Characterization of HERG potassium channel inhibition using CoMSiA 3D QSAR and homology modeling approaches

inferredcites →https://doi.org/10.1016/s0960-894x(03)00492-xopenalex-snapshot

Prediction of hERG potassium channel affinity by traditional and hologram qSAR methods

inferredcites →https://doi.org/10.1021/ci050308fopenalex-snapshot

Development and Evaluation of an in Silico Model for hERG Binding

inferredcites →https://doi.org/10.1021/ci100081jopenalex-snapshot

In Silico Binary Classification QSAR Models Based on 4D-Fingerprints and MOE Descriptors for Prediction of hERG Blockage

inferredcites →https://doi.org/10.1021/ci100084sopenalex-snapshot

WizePairZ: A Novel Algorithm to Identify, Encode, and Exploit Matched Molecular Pairs with Unspecified Cores in Medicinal Chemistry

inferredcites →https://doi.org/10.1021/ci100258popenalex-snapshot

Lead Optimization Using Matched Molecular Pairs: Inclusion of Contextual Information for Enhanced Prediction of hERG Inhibition, Solubility, and Lipophilicity

inferredcites →https://doi.org/10.1021/ci200271dopenalex-snapshot

A Critical Assessment of Combined Ligand- and Structure-Based Approaches to hERG Channel Blocker Modeling

inferredcites →https://doi.org/10.1021/ci300060bopenalex-snapshot

Predictive Toxicology Modeling: Protocols for Exploring hERG Classification and Tetrahymena pyriformis End Point Predictions

inferredcites →https://doi.org/10.1021/ci800304topenalex-snapshot

Similarity-Based Classifier Using Topomers to Provide a Knowledge Base for hERG Channel Inhibition

inferredcites →https://doi.org/10.1021/jm060500oopenalex-snapshot

Common Pharmacophores for Uncharged Human Ether-a-go-go-Related Gene (hERG) Blockers

inferredcites →https://doi.org/10.1021/jm300131xopenalex-snapshot

The Experimental Uncertainty of Heterogeneous Public Ki Data

inferredcites →https://doi.org/10.1021/mp300023xopenalex-snapshot

ADMET Evaluation in Drug Discovery. 12. Development of Binary Classification Models for Prediction of hERG Potassium Channel Blockage

inferredcites →https://doi.org/10.1021/mp700124eopenalex-snapshot

hERG Classification Model Based on a Combination of Support Vector Machine Method and GRIND Descriptors

inferredcites →https://doi.org/10.1021/tx060230copenalex-snapshot

A Novel Approach Using Pharmacophore Ensemble/Support Vector Machine (PhE/SVM) for Prediction of hERG Liability

inferredcites →https://doi.org/10.1021/tx200099jopenalex-snapshot

A Comprehensive Support Vector Machine Binary hERG Classification Model Based on Extensive but Biased End Point hERG Data Sets

inferredcites →https://doi.org/10.1093/nar/gkr777openalex-snapshot

ChEMBL: a large-scale bioactivity database for drug discovery

inferredcites →https://doi.org/10.1111/j.1540-8167.1999.tb00264.xopenalex-snapshot

Block of HERG Potassium Channels by the Antihistamine Astemizole and its Metabolites Desmethylastemizole and Norastemizole

inferredcites →https://doi.org/10.1161/01.cir.94.4.817openalex-snapshot

HERG, a Primary Human Ventricular Target of the Nonsedating Antihistamine Terfenadine

inferredcites →https://doi.org/10.1371/journal.pone.0061007openalex-snapshot

Comparability of Mixed IC50 Data – A Statistical Analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9781119282594.ch3openalex-snapshot

Computational Approaches for Predicting hERG Activity

inferred← citeshttps://doi.org/10.1002/cbdv.202401843openalex-snapshot

Investigation into the Quantitative Structure‐Biotoxicity Relationship of Antibiotics and their Estrogenic Receptor Disruption Effects

inferred← citeshttps://doi.org/10.1002/cmdc.202100707openalex-snapshot

hERG Optimization of Benzofuro−Pyridine and Pyrazino−Indole Derivatives as MCHR1 Antagonists

inferred← citeshttps://doi.org/10.1002/med.21445openalex-snapshot

Development of Safe Drugs: The hERG Challenge

inferred← citeshttps://doi.org/10.1002/minf.201400188openalex-snapshot

Screening Chemicals for Receptor‐Mediated Toxicological and Pharmacological Endpoints: Using Public Data to Build Screening Tools within a KNIME Workflow

inferred← citeshttps://doi.org/10.1002/minf.201600126openalex-snapshot

Prediction of hERG Liability – Using SVM Classification, Bootstrapping and Jackknifing

inferred← citeshttps://doi.org/10.1002/minf.201700074openalex-snapshot

Modeling of the hERG K+ Channel Blockage Using Online Chemical Database and Modeling Environment (OCHEM)

inferred← citeshttps://doi.org/10.1002/slct.202201221openalex-snapshot

A Review of Computational Methods in Predicting hERG Channel Blockers

inferred← citeshttps://doi.org/10.1007/s00894-021-04993-wopenalex-snapshot

Ursolic acid as a potential inhibitor of Mycobacterium tuberculosis cytochrome bc1 oxidase—a molecular modelling perspective

inferred← citeshttps://doi.org/10.1007/s10822-014-9759-6openalex-snapshot

Count on kappa

inferred← citeshttps://doi.org/10.1007/s10822-016-9986-0openalex-snapshot

Compilation and physicochemical classification analysis of a diverse hERG inhibition database

inferred← citeshttps://doi.org/10.1007/s10822-021-00417-2openalex-snapshot

Comparing classification models—a practical tutorial

inferred← citeshttps://doi.org/10.1007/s11030-026-11485-7openalex-snapshot

Enhancing ADMET property predictions using cross-aligned multimodal attention mechanisms

inferred← citeshttps://doi.org/10.1016/b978-0-443-29808-0.00032-7openalex-snapshot

Applications of machine learning in quantitative structure-activity relationships (QSAR)

inferred← citeshttps://doi.org/10.1016/j.addr.2015.03.003openalex-snapshot

Computational investigations of hERG channel blockers: New insights and current predictive models

inferred← citeshttps://doi.org/10.1016/j.ejmech.2020.112290openalex-snapshot

hERG toxicity assessment: Useful guidelines for drug design

inferred← citeshttps://doi.org/10.1016/j.jmgm.2017.01.012openalex-snapshot

3D-SDAR modeling of hERG potassium channel affinity: A case study in model design and toxicophore identification

inferred← citeshttps://doi.org/10.1016/j.jmgm.2023.108405openalex-snapshot

Structural analysis of hERG channel blockers and the implications for drug design

inferred← citeshttps://doi.org/10.1016/j.toxlet.2020.07.003openalex-snapshot

Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints

inferred← citeshttps://doi.org/10.1016/j.vascn.2023.107293openalex-snapshot

hERG agonists pose challenges to web-based machine learning methods for prediction of drug-hERG channel interaction

inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00884openalex-snapshot

Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the “Big Data” Era

inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00947openalex-snapshot

Using Graph Databases to Investigate Trends in Structure–Activity Relationship Networks

inferred← citeshttps://doi.org/10.1021/acs.jcim.0c01344openalex-snapshot

Coloring Molecules with Explainable Artificial Intelligence for Preclinical Relevance Assessment

inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00744openalex-snapshot

Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study

inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00616openalex-snapshot

General Purpose 2D and 3D Similarity Approach to Identify hERG Blockers

inferred← citeshttps://doi.org/10.1021/acs.jcim.6c03072openalex-snapshot

25 Years of Cardiac Ion Channel QSAR: From hERG Dominance to Multi-Channel Modeling

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00054openalex-snapshot

Conformal Regression for Quantitative Structure–Activity Relationship Modeling—Quantifying Prediction Uncertainty

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00150openalex-snapshot

The Catch-22 of Predicting hERG Blockade Using Publicly Accessible Bioactivity Data

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00769openalex-snapshot

Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00773openalex-snapshot

Revealing Molecular Determinants of hERG Blocker and Activator Binding

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b00518openalex-snapshot

Structure–Affinity Relationships (SARs) and Structure–Kinetics Relationships (SKRs) of Kv11.1 Blockers

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b00505openalex-snapshot

Discovery and Rational Design of Natural-Product-Derived 2-Phenyl-3,4-dihydro-2H-benzo[f]chromen-3-amine Analogs as Novel and Potent Dipeptidyl Peptidase 4 (DPP-4) Inhibitors for the Treatment of Type 2 Diabetes

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.9b02126openalex-snapshot

Computational Chemistry on a Budget: Supporting Drug Discovery with Limited Resources

inferred← citeshttps://doi.org/10.1021/ci5001955openalex-snapshot

Experimentally Validated hERG Pharmacophore Models as Cardiotoxicity Prediction Tools

inferred← citeshttps://doi.org/10.1021/ci500342qopenalex-snapshot

Generalized Workflow for Generating Highly Predictive in Silico Off-Target Activity Models

inferred← citeshttps://doi.org/10.1021/jm500317aopenalex-snapshot

Matched Molecular Pair Analysis: Significance and the Impact of Experimental Uncertainty

inferred← citeshttps://doi.org/10.1038/s41598-019-47536-3openalex-snapshot

Support Vector Machine model for hERG inhibitory activities based on the integrated hERG database using descriptor selection by NSGA-II

inferred← citeshttps://doi.org/10.1039/c5tx00294jopenalex-snapshot

In silico prediction of hERG potassium channel blockage by chemical category approaches

inferred← citeshttps://doi.org/10.1039/c8sc04175jopenalex-snapshot

Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations

inferred← citeshttps://doi.org/10.1093/bib/bbaa160openalex-snapshot

Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development

inferred← citeshttps://doi.org/10.1126/sciadv.ado3501openalex-snapshot

Delocalized quinolinium-macrocyclic peptides, an atypical chemotype for CNS penetration

inferred← citeshttps://doi.org/10.1186/s12859-019-2814-5openalex-snapshot

Computational determination of hERG-related cardiotoxicity of drug candidates

inferred← citeshttps://doi.org/10.1186/s13321-019-0334-yopenalex-snapshot

Avoiding hERG-liability in drug design via synergetic combinations of different (Q)SAR methodologies and data sources: a case study in an industrial setting

inferred← citeshttps://doi.org/10.1371/journal.pone.0118324openalex-snapshot

Global Analysis Reveals Families of Chemical Motifs Enriched for hERG Inhibitors

inferred← citeshttps://doi.org/10.1371/journal.pone.0199348openalex-snapshot

Construction of an integrated database for hERG blocking small molecules

inferred← citeshttps://doi.org/10.2174/1568026614666140506124442openalex-snapshot

Tuning hERG Out: Antitarget QSAR Models for Drug Development

inferred← citeshttps://doi.org/10.3389/fbioe.2019.00485openalex-snapshot

DeepSnap-Deep Learning Approach Predicts Progesterone Receptor Antagonist Activity With High Performance

inferred← citeshttps://doi.org/10.3389/fphar.2017.00889openalex-snapshot

vNN Web Server for ADMET Predictions

inferred← citeshttps://doi.org/10.3390/app15158350openalex-snapshot

Insight into the in Silico Structural, Physicochemical, Pharmacokinetic and Toxicological Properties of Antibacterially Active Viniferins and Viniferin-Based Compounds as Derivatives of Resveratrol Containing a (2,3-Dihydro)benzo[b]furan Privileged Scaffold

inferred← citeshttps://doi.org/10.3390/chemistry4030045openalex-snapshot

hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties

inferred← citeshttps://doi.org/10.3390/ijms24010635openalex-snapshot

Toward Quantitative Models in Safety Assessment: A Case Study to Show Impact of Dose–Response Inference on hERG Inhibition Models

inferred← citeshttps://doi.org/10.4155/fmc-2017-0303openalex-snapshot

The Current Limits in Virtual Screening and Property Prediction

inferred← citeshttps://doi.org/10.4155/fmc.15.18openalex-snapshot

In Silico Prediction of hERG Inhibition

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