ArticleBMC pharmacology & toxicology2019
eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates.
Article in BMC pharmacology & toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed.
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- Shiny binary modeling platform: a reproducibility-oriented software platform for structured binary modeling with integrated interpretation, validation support, model comparison, and archive export.Frontiers in pharmacology · 2026Article
- Succinic acid enhances sedative activity of diazepam through GABAergic receptor modulation: Evidence from behavioral approach and computational insights.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Phytochemical Profiling, Molecular Docking, ADMET Analysis ofACS omega · 2025Article
- Mycobacterium tuberculosis FAS-II pathway targeted integrative deep learning based identification of potential anti-tubercular agents.Journal of computer-aided molecular design · 2025Article
- Drug toxicity prediction based on genotype-phenotype differences between preclinical models and humans.EBioMedicine · 2025Article
- ProToxin, a Predictor of Protein Toxicity.Toxins · 2025Article
- Deciphering and targeting oncogenic pathways through integrated approaches and amino acid metabolism in hematologic malignancies.Discover oncology · 2025Review
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- novoStoic2.0: An integrated framework for pathway synthesis, thermodynamic evaluation, and enzyme selection.PLoS computational biology · 2025Article
- An Imbalance Regression Approach to Toxicity Prediction of Chemicals for Potential Use in Environmentally Acceptable Lubricants.ACS applied materials & interfaces · 2025Article
- Computational approaches to predict the toxicity of bioactive natural products: a mini review of methodologies.Food science and biotechnology · 2025Review
- Isoliquiritigenin Alleviates Periodontitis by Suppressing Inflammation via NF-κB Signaling Pathway of Immune Cell.Journal of inflammation research · 2025Article
- Integrated Artificial Intelligence and Physics-Based Methods for theMedicinal chemistry (Shariqah (United Arab Emirates)) · 2025Article
- Recent Development, Applications, and Patents of Artificial Intelligence in Drug Design and Development.Current drug discovery technologies · 2025Review
- Role of Artificial Intelligence in Drug Discovery to Revolutionize the Pharmaceutical Industry: Resources, Methods and Applications.Recent patents on biotechnology · 2025Review
- Evaluating chemical effects on human neural cells through calcium imaging and deep learning.iScience · 2024Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe efficiency of drug development defined as a number of successfully launched new pharmaceuticals normalized by financial investments has significantly declined. Nonetheless, recent advances in high-throughput experimental techniques and computational modeling promise reductions in the costs and development times required to bring new drugs to market. The prediction of toxicity of drug candidates is one of the important components of modern drug discovery.
resultsIn this work, we describe eToxPred, a new approach to reliably estimate the toxicity and synthetic accessibility of small organic compounds. eToxPred employs machine learning algorithms trained on molecular fingerprints to evaluate drug candidates. The performance is assessed against multiple datasets containing known drugs, potentially hazardous chemicals, natural products, and synthetic bioactive compounds. Encouragingly, eToxPred predicts the synthetic accessibility with the mean square error of only 4% and the toxicity with the accuracy of as high as 72%.
conclusionseToxPred can be incorporated into protocols to construct custom libraries for virtual screening in order to filter out those drug candidates that are potentially toxic or would be difficult to synthesize. It is freely available as a stand-alone software at https://github.com/pulimeng/etoxpred .
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Registered trials
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.