ArticleScientific reports2017
Predicting the Reliability of Drug-target Interaction Predictions with Maximum Coverage of Target Space.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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
33 citing papers in PubMed, 78 citations in OpenAlex.
- Drug toxicity prediction based on genotype-phenotype differences between preclinical models and humans.EBioMedicine · 2025Article
- Application of new approach methodologies for nonclinical safety assessment of drug candidates.Nature reviews. Drug discovery · 2025Review
- Advanced Proteomics Approaches Hold Potential for the Risk Assessment of Metabolism-Disrupting Chemicals as Omics-Based NAM: A Case Study Using the Phthalate Substitute DINCH.Environmental science & technology · 2025Article
- Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms.BMC biology · 2025Article
- Article
- The Missing Enzymes: A Call to Update Pharmacological Profiling Practices for Better Drug Safety Assessment.Journal of medicinal chemistry · 2025Review
- Network pharmacology and molecular dynamics simulation reveal antineoplastic potential of Antarctic sponge-derived suberitenones.Frontiers in chemistry · 2025Article
- Artificial Intelligence-Driven Innovations in Oncology Drug Discovery: Transforming Traditional Pipelines and Enhancing Drug Design.Drug design, development and therapy · 2025Review
- Therapeutic Implications of Ceritinib in Cholangiocarcinoma beyond ALK Expression and Mutation.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Exposure to the Natural Compound Climacostol Induces Cell Damage and Oxidative Stress in the Fruit FlyToxics · 2024Article
- Withdrawn 2.0-update on withdrawn drugs with pharmacovigilance data.Nucleic acids research · 2024Article
- Graph neural networks are promising for phenotypic virtual screening on cancer cell lines.Biology methods & protocols · 2024Article
- In-silico target prediction by ensemble chemogenomic model based on multi-scale information of chemical structures and protein sequences.Journal of cheminformatics · 2023Article
- On the Best Way to Cluster NCI-60 Molecules.Biomolecules · 2023Article
- Molecular Modeling and In Vitro Evaluation of Piplartine Analogs against Oral Squamous Cell Carcinoma.Molecules (Basel, Switzerland) · 2023Article
- SuperNatural 3.0-a database of natural products and natural product-based derivatives.Nucleic acids research · 2023Article
- A novel HSP90 inhibitor SL-145 suppresses metastatic triple-negative breast cancer without triggering the heat shock response.Oncogene · 2022Article
- Computational modeling predicts potential effects of the herbal infusion "horchata" against COVID-19.Food chemistry · 2022Article
- Repositioning of a novel GABA-B receptor agonist, AZD3355 (Lesogaberan), for the treatment of non-alcoholic steatohepatitis.Scientific reports · 2021Article
- Recent Advances in In Silico Target Fishing.Molecules (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many computational methods to predict the macromolecular targets of small organic molecules have been presented to date. Despite progress, target prediction methods still have important limitations. For example, the most accurate methods implicitly restrict their predictions to a relatively small number of targets, are not systematically validated on drugs (whose targets are harder to predict than those of non-drug molecules) and often lack a reliability score associated with each predicted target. Here we present a systematic validation of ligand-centric target prediction methods on a set of clinical drugs. These methods exploit a knowledge-base covering 887,435 known ligand-target associations between 504,755 molecules and 4,167 targets. Based on this dataset, we provide a new estimate of the polypharmacology of drugs, which on average have 11.5 targets below IC
Indexed as
Identifiers
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.