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ADMET Evaluation in Drug Discovery. 12. Development of Binary Classification Models for Prediction of hERG Potassium Channel Blockage
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Outgoing claims: the papers this work cites, builds on, or argues with.
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New insights about HERG blockade obtained from protein modeling, potential energy mapping, and docking studies
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Progress in computational toxicology
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In silico ADME/T modelling for rational drug design
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.6b00227openalex-snapshot
Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00671openalex-snapshot
Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00143openalex-snapshot
Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00144openalex-snapshot
Open Source Bayesian Models. 2. Mining a “Big Dataset” To Create and Validate Models with ChEMBL
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.8b00769openalex-snapshot
Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00587openalex-snapshot
Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.0c01192openalex-snapshot
Small Molecules Selectively Targeting Sigma-1 Receptor for the Treatment of Neurological Diseases
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b01301openalex-snapshot
Design and Synthesis of Cajanine Analogues against Hepatitis C Virus through Down-Regulating Host Chondroitin Sulfate N-Acetylgalactosaminyltransferase 1
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6c00049openalex-snapshot
In Silico ADMET: From Current Practices to Novel Profilers
inferred← citeshttps://doi.org/10.1021/acs.jpcb.7b12658openalex-snapshot
Benchmark Study Based on 2P2IDB to Gain Insights into the Discovery of Small-Molecule PPI Inhibitors
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.6b00471openalex-snapshot
ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.7b00317openalex-snapshot
ADMET Evaluation in Drug Discovery. Part 17: Development of Quantitative and Qualitative Prediction Models for Chemical-Induced Respiratory Toxicity
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.7b00578openalex-snapshot
Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets
inferred← citeshttps://doi.org/10.1021/acscombsci.0c00169openalex-snapshot
Activity Prediction of Small Molecule Inhibitors for Antirheumatoid Arthritis Targets Based on Artificial Intelligence
inferred← citeshttps://doi.org/10.1021/acsomega.2c05693openalex-snapshot
Machine Learning Toxicity Prediction: Latest Advances by Toxicity End Point
inferred← citeshttps://doi.org/10.1021/acsomega.5c07982openalex-snapshot
Escaping from Flatland: 3D Carborane-Based Bioisosteres of Erlotinib as Potential Anticancer Agents
inferred← citeshttps://doi.org/10.1021/acsomega.5c10745openalex-snapshot
Improving hERG Cardiotoxicity Prediction via SMILES Transformer, Molecular Fingerprints, and Layer-Wise Self-Adaptive Graph Attention Network
inferred← citeshttps://doi.org/10.1021/ci300112jopenalex-snapshot
ADMET Evaluation in Drug Discovery. 11. PharmacoKinetics Knowledge Base (PKKB): A Comprehensive Database of Pharmacokinetic and Toxic Properties for Drugs
inferred← citeshttps://doi.org/10.1021/ci300336vopenalex-snapshot
QSAR Classification Model for Antibacterial Compounds and Its Use in Virtual Screening
inferred← citeshttps://doi.org/10.1021/ci300367aopenalex-snapshot
admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties
inferred← citeshttps://doi.org/10.1021/ci300400aopenalex-snapshot
In silico Prediction of Chemical Ames Mutagenicity
inferred← citeshttps://doi.org/10.1021/ci400146uopenalex-snapshot
Modeling Compound–Target Interaction Network of Traditional Chinese Medicines for Type II Diabetes Mellitus: Insight for Polypharmacology and Drug Design
inferred← citeshttps://doi.org/10.1021/ci400382ropenalex-snapshot
Development and Evaluation of an Integrated Virtual Screening Strategy by Combining Molecular Docking and Pharmacophore Searching Based on Multiple Protein Structures
inferred← citeshttps://doi.org/10.1021/ci5001955openalex-snapshot
Experimentally Validated hERG Pharmacophore Models as Cardiotoxicity Prediction Tools
inferred← citeshttps://doi.org/10.1021/ci500414bopenalex-snapshot
Assessing an Ensemble Docking-Based Virtual Screening Strategy for Kinase Targets by Considering Protein Flexibility
inferred← citeshttps://doi.org/10.1021/mp300156ropenalex-snapshot
QSAR Modeling and Data Mining Link Torsades de Pointes Risk to the Interplay of Extent of Metabolism, Active Transport, and hERG Liability
inferred← citeshttps://doi.org/10.1021/mp300198dopenalex-snapshot
Drug-likeness Analysis of Traditional Chinese Medicines: Prediction of Drug-likeness Using Machine Learning Approaches
inferred← citeshttps://doi.org/10.1021/mp400450mopenalex-snapshot
ADMET Evaluation in Drug Discovery. 13. Development ofin SilicoPrediction Models for P-Glycoprotein Substrates
inferred← citeshttps://doi.org/10.1021/tx500389qopenalex-snapshot
Absorption, Distribution, Metabolism, Excretion, and Toxicity Evaluation in Drug Discovery. 14. Prediction of Human Pregnane X Receptor Activators by Using Naive Bayesian Classification Technique
inferred← citeshttps://doi.org/10.1038/aps.2014.35openalex-snapshot
Novel Bayesian classification models for predicting compounds blocking hERG potassium channels
inferred← citeshttps://doi.org/10.1038/aps.2015.143openalex-snapshot
Investigation of miscellaneous hERG inhibition in large diverse compound collection using automated patch-clamp assay
inferred← citeshttps://doi.org/10.1038/s41598-018-22631-zopenalex-snapshot
IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics
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/10.1038/s41598-025-97311-wopenalex-snapshot
Exploring Erythrina flavonoids as potential SARS-CoV-2 RdRp inhibitors through virtual screening, in silico ADMET evaluation, and molecular dynamics simulation studies
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/c8md00472bopenalex-snapshot
ADMET-score – a comprehensive scoring function for evaluation of chemical drug-likeness
inferred← citeshttps://doi.org/10.1039/c8ra01206gopenalex-snapshot
A novel adaptive ensemble classification framework for ADME prediction
inferred← citeshttps://doi.org/10.1039/d1ra07956eopenalex-snapshot
Predicting hERG channel blockers with directed message passing neural networks
inferred← citeshttps://doi.org/10.1039/d2gc03973gopenalex-snapshot
Toxicological data bank bridges the gap between environmental risk assessment and green organic chemical design in One Health world
inferred← citeshttps://doi.org/10.1080/07391102.2020.1765876openalex-snapshot
Repurposing of chloroquine and some clinically approved antiviral drugs as effective therapeutics to prevent cellular entry and replication of coronavirus
inferred← citeshttps://doi.org/10.1080/07391102.2022.2051748openalex-snapshot
Molecular insights of hyaluronic acid – ethambutol and hyaluronic acid – isoniazid drug conjugates act as promising novel drugs for the treatment of tuberculosis
inferred← citeshttps://doi.org/10.1080/07391102.2022.2161010openalex-snapshot
Molecular characterization of glutor-GLUT interaction and prediction of glutor’s drug-likeness: implications for its utility as an antineoplastic agent
inferred← citeshttps://doi.org/10.1080/07391102.2023.2274974openalex-snapshot
Molecular modeling, dynamic simulation, and metabolic reactivity studies of quinazoline derivatives to investigate their anti-angiogenic potential by targeting wild EGFR wt and mutant EGFR T790M receptor tyrosine kinases
inferred← citeshttps://doi.org/10.1080/07391102.2024.2328745openalex-snapshot
In silico validation of hyaluronic acid – drug conjugates based targeted drug delivery for the treatment of COVID-19
inferred← citeshttps://doi.org/10.1080/08927022.2017.1328556openalex-snapshot
Prediction of chemical biodegradability using computational methods
inferred← citeshttps://doi.org/10.1080/1062936x.2023.2251876openalex-snapshot
Discovery of dual-target natural antimalarial agents against DHODH and PMT of Plasmodium falciparum : pharmacophore modelling, molecular docking, quantum mechanics, and molecular dynamics simulations
inferred← citeshttps://doi.org/10.1080/17460441.2016.1216967openalex-snapshot
Getting the most out of PubChem for virtual screening
inferred← citeshttps://doi.org/10.1093/bib/bbab112openalex-snapshot
Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method
inferred← citeshttps://doi.org/10.1093/bib/bbac131openalex-snapshot
Knowledge-based BERT: a method to extract molecular features like computational chemists
inferred← citeshttps://doi.org/10.1093/bioinformatics/btac192openalex-snapshot
Interpretable-ADMET: a web service for ADMET prediction and optimization based on deep neural representation
inferred← citeshttps://doi.org/10.1109/iraset60544.2024.10548722openalex-snapshot
Advancements in Cardiotoxicity Detection and Assessment through Artificial Intelligence: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/tcbbio.2025.3614696openalex-snapshot
MTF-hERG: A Multi-Type Features Fusion-Based Framework for Predicting hERG Cardiotoxicity of Compounds
inferred← citeshttps://doi.org/10.1111/cbdd.13600openalex-snapshot
Prediction of hERG K+ channel blockage using deep neural networks
inferred← citeshttps://doi.org/10.1111/cbdd.13656openalex-snapshot
Bayesian machine learning to discover Bruton’s tyrosine kinase inhibitors
inferred← citeshttps://doi.org/10.1111/cbdd.13750openalex-snapshot
The rise of deep learning and transformations in bioactivity prediction power of molecular modeling tools
inferred← citeshttps://doi.org/10.1124/pr.112.007336openalex-snapshot
Computational Methods in Drug Discovery
inferred← citeshttps://doi.org/10.1155/2014/791246openalex-snapshot
A Statistical-Textural-Features Based Approach for Classification of Solid Drugs Using Surface Microscopic Images
inferred← citeshttps://doi.org/10.1177/15353702231209421openalex-snapshot
Review of machine learning and deep learning models for toxicity prediction
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/s13065-026-01785-2openalex-snapshot
Identification of α-glucosidase inhibitory phytochemicals from Erythrina crista-galli using combined experimental and computational methods
inferred← citeshttps://doi.org/10.1186/s13321-016-0117-7openalex-snapshot
ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling
inferred← citeshttps://doi.org/10.1186/s13321-018-0270-2openalex-snapshot
PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions
inferred← citeshttps://doi.org/10.1186/s13321-020-00421-yopenalex-snapshot
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning
inferred← citeshttps://doi.org/10.1186/s40064-016-1844-yopenalex-snapshot
Non-covalent interactions involving halogenated derivatives of capecitabine and thymidylate synthase: a computational approach
inferred← citeshttps://doi.org/10.1186/s40360-018-0282-6openalex-snapshot
eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
inferred← citeshttps://doi.org/10.1371/journal.pone.0178347openalex-snapshot
AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer’s disease
inferred← citeshttps://doi.org/10.1371/journal.pone.0196667openalex-snapshot
Epiisopilosine alkaloid has activity against Schistosoma mansoni in mice without acute toxicity
inferred← citeshttps://doi.org/10.1515/zpch-2023-0357openalex-snapshot
Unraveling the inhibitory potential of fatty acids from Cola lepidota seed against monoclonal antibody Fab fragment (9F8) (3VG0) leptin antagonism and restoration of ‘satiety’ in obesity condition: insight from quantum chemical analysis, pharmacokinetics, and molecular docking
inferred← citeshttps://doi.org/10.1520/jte20160388openalex-snapshot
Nondestructive Evaluation of Solid Pharmaceutical Products Using Wavelet Transformations and Multispectral Data
inferred← citeshttps://doi.org/10.17350/hjse19030000297openalex-snapshot
Novel 1,3,4-Thiadiazole Derivatives as Antibiofilm, Antimicrobial, Efflux Pump Inhibiting Agents and Their ADMET Characterizations
inferred← citeshttps://doi.org/10.17475/kastorman.1215281openalex-snapshot
In Silico Proof of the Effect of Quercetin and Umbelliferone as Alpha-Amylase Inhibitors, Which Can Be Used in the Treatment of Diabetes
inferred← citeshttps://doi.org/10.2139/ssrn.6184762openalex-snapshot
In Vitro and In Silico Evaluation of Piperazine-Schiff Base Derivatives: Antibacterial and Antifungal Activities, DFT, Docking, ADMET and Molecular Dynamics
inferred← citeshttps://doi.org/10.21448/ijsm.1846057openalex-snapshot
Pharmacological investigation of formyl and acetyl substituents on piperazine: Docking, ADMET and Molecular Dynamics Simulations
inferred← citeshttps://doi.org/10.2147/dddt.s149214openalex-snapshot
In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
inferred← citeshttps://doi.org/10.2174/0115701808277988240105083347openalex-snapshot
Unifying Theory and Experiments: Multi-Target Pharmacology of Dajihan Pill Against Hyperlipidemia
inferred← citeshttps://doi.org/10.2174/1386207322666190206163409openalex-snapshot
Network Pharmacology and Reverse Molecular Docking-Based Prediction of the Molecular Targets and Pathways for Avicularin Against Cancer
inferred← citeshttps://doi.org/10.2174/138945013804806460openalex-snapshot
Human Ether-a-Go-Go-Related Gene Channel Blockers and its Structural Analysis for Drug Design
inferred← citeshttps://doi.org/10.2174/15680266113139990036openalex-snapshot
Recent Developments in Computational Prediction of hERG Blockage
inferred← citeshttps://doi.org/10.2174/1568026614666140506124442openalex-snapshot
Tuning hERG Out: Antitarget QSAR Models for Drug Development
inferred← citeshttps://doi.org/10.2174/1568026618666180727152557openalex-snapshot
Applications of Machine Learning Methods in Drug Toxicity Prediction
inferred← citeshttps://doi.org/10.2174/1568026619666190902145116openalex-snapshot
Recent Advances in Developing K-Ras Plasma Membrane Localization Inhibitors
inferred← citeshttps://doi.org/10.22144/ctu.jvn.2021.038openalex-snapshot
Tổng hợp, tiếp cận dược lý và đánh giá khả năng ức chế enzyme histone deacetylase 8 (HDAC8) in silico của một số dẫn xuất tương tự belinostat
inferred← citeshttps://doi.org/10.24377/ljmu.t.00004554openalex-snapshot
Development of in silico models for the prediction of toxicity incorporating ADME information
inferred← citeshttps://doi.org/10.29294/ijase.10.3.2024.3581-3592openalex-snapshot
"Molecular Studies of Antiviral Drug Atazanavir and Hyaluronic Acid-Atazanavir conjugate as Novel Drugs to Target SARS-CoV-2 Viral Proteins"
inferred← citeshttps://doi.org/10.33263/briac116.1441314432openalex-snapshot
N-(5-Morpholino-2-arylimidazo[2,1-b][1,3,4]thiadiazol-6-yl)carboxamides as Potential Fer/FerT Kinase Inhibitors. Homology Modeling, Molecular Docking Studies and In Silico ADMET Profiling
inferred← citeshttps://doi.org/10.3389/fchem.2018.00030openalex-snapshot
In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts
inferred← citeshttps://doi.org/10.3389/fphar.2017.00889openalex-snapshot
vNN Web Server for ADMET Predictions
inferred← citeshttps://doi.org/10.3389/fphar.2019.01631openalex-snapshot
Capsule Networks Showed Excellent Performance in the Classification of hERG Blockers/Nonblockers
inferred← citeshttps://doi.org/10.3390/biom10040512openalex-snapshot
The Antioxidant Peptide Salamandrin-I: First Bioactive Peptide Identified from Skin Secretion of Salamandra Genus (Salamandra salamandra)
inferred← citeshttps://doi.org/10.3390/cancers12113423openalex-snapshot
Sunitinib-Containing Carborane Pharmacophore with the Ability to Inhibit Tyrosine Kinases Receptors FLT3, KIT and PDGFR-β, Exhibits Powerful In Vivo Anti-Glioblastoma Activity
inferred← citeshttps://doi.org/10.3390/cimb47080634openalex-snapshot
Computational Exploration of Bacterial Compounds Targeting Arginine-Specific Mono-Adp-Ribosyl-Transferase 1 (Art1): A Pathway to Novel Therapeutic Anticancer Strategies
inferred← citeshttps://doi.org/10.3390/ijms19041040openalex-snapshot
MetStabOn—Online Platform for Metabolic Stability Predictions
inferred← citeshttps://doi.org/10.3390/ijms21124380openalex-snapshot
Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement
inferred← citeshttps://doi.org/10.3390/molecules30092033openalex-snapshot
Novel Crown Ether-Functionalized Fusidic Acid Butyl Ester: Synthesis, Biological Evaluation, In Silico ADMET, and Molecular Docking Studies
inferred← citeshttps://doi.org/10.35118/apjmbb.2022.030.2.01openalex-snapshot
Identification of natural product inhibitors of de novo lipogenesis enzymes as an anti-cancer strategy: An in silico approach
inferred← citeshttps://doi.org/10.4155/fmc-2019-0060openalex-snapshot
Carboranylanilinoquinazoline EGFR-Inhibitors: Toward ‘Lead-to-Candidate’ Stage in the Drug-Development Pipeline
inferred← citeshttps://doi.org/10.4155/fmc.15.18openalex-snapshot
In Silico Prediction of hERG Inhibition
inferred← citeshttps://doi.org/10.4236/jbise.2019.124016openalex-snapshot
Discovery of Novel Irreversible HER2 Inhibitors for Breast Cancer Treatment
inferred← citeshttps://doi.org/10.54319/jjbs/140211openalex-snapshot
Thrombin protease-activated receptor inhibitors from the peel of Ananas comosus (L.) Merr.: an in silico approach
inferred← citeshttps://doi.org/10.70675/c9cacc57zdf38z489bzacf8z0d5ecf73c80copenalex-snapshot
Development of new virtual screening methods and novel unbiased benchmarking data sets
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.