ArticleNature2012
Large-scale prediction and testing of drug activity on side-effect targets.
Article in Nature, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 343 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
343 citing papers in PubMed, 2 syntheses or guidelines pooled it, 886 citations in OpenAlex.
- A systematic review on sex differences in adverse drug reactions related to psychotropic, cardiovascular, and analgesic medications.Frontiers in pharmacology · 2023Pooled it
- A Systematic Review of Computational Drug Discovery, Development, and Repurposing for Ebola Virus Disease Treatment.Molecules (Basel, Switzerland) · 2017Pooled it
- MacroTox: A Macroscopic Graph Topology-Based Multimodal Learning Framework for Robust Molecular Toxicity Prediction.JACS Au · 2026Article
- Artificial intelligence in drug discovery - what it is, where we stand and the path forward.Nature reviews. Drug discovery · 2026Review
- Ligand-agnostic off-target site prediction for early toxicity screening by leveraging point cloud-based protein cavity analysis.Briefings in bioinformatics · 2026Article
- Review
- ComTarget: Small-Molecule Target Prediction with Combinatorial Modeling.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Discovery of Novel Chemotype LRRK2 Inhibitors Through AlphaFold2-Generated Structure-Based Docking Screen.International journal of molecular sciences · 2026Article
- Machine Learning-Based QSAR Models for Discovery of Inhibitors TargetingPharmaceuticals (Basel, Switzerland) · 2026Article
- Explainable drug side effect prediction in central neural system via biologically informed graph neural network.Translational psychiatry · 2026Article
- Vinpocetine-An "Old" Drug with a New Face: Moving Toward a Better Understanding of Its Neuroprotective Mechanism of Action.Biomolecules · 2026Review
- KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge-Graph Reinforced Deep Q-Learning.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Assessing the performance of quantum-mechanical descriptors in physicochemical and biological property prediction.Digital discovery · 2026Article
- Comparison of In Vitro Metrics With Real-World Risk of Drug-Induced Parkinsonism Due to Antipsychotic Drugs: Retrospective Cohort Study.JMIR public health and surveillance · 2026Article
- PersADE: a database of personalized adverse drug events and their underlying molecular mechanisms.Nucleic acids research · 2026Article
- SOLVE: A structured orthogonal latent variable framework for disentangling confounding in matrix data.Biology methods & protocols · 2026Article
- From Gene Networks to Therapeutics: A Causal Inference and Deep Learning Approach for Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2025Article
- ColdstartCPI: Induced-fit theory-guided DTI predictive model with improved generalization performance.Nature communications · 2025Article
- ADME of Bromo-DragonFLY as an example of a new psychoactive substance (NPS) - application of in Silico methods for prediction: absorption, distribution, metabolism and excretion.Scientific reports · 2025Article
- DTBA-net: Drug-Target Binding Affinity prediction using feature selection in hybrid CNN model.Journal of computer-aided molecular design · 2025Article
283 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
Abstract
Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug-target-adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.
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What OpenQuestion holds
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.