ArticleFrontiers in big data2019
Novel Computational Approach to Predict Off-Target Interactions for Small Molecules.
Article in Frontiers in big data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 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
50 citing papers in PubMed.
- Multiscale cross modal fusion and cascaded signal propagation for drug target interaction prediction.iScience · 2026Article
- Deubiquitinases as Regulators and Therapeutic Targets in Vascular Diseases.International journal of molecular sciences · 2026Review
- TRIZ-guided computational innovation framework for the automated generation and prioritization of novel azole-like antifungal candidates targeting Candida auris CYP51.Journal of computer-aided molecular design · 2026Article
- Drugs inducing interstitial lung disease: in silico analysis of their structures and targets.Molecular medicine (Cambridge, Mass.) · 2026Article
- RNA modifications as innovative pharmaceutical targets: emerging drug delivery strategies and precision therapeutics for cancer immunotherapy and metabolic diseases.Molecular biology reports · 2026Review
- Prediction variability in physiologically based pharmacokinetic modeling of tissue disposition under deep uncertainty.NPJ systems biology and applications · 2026Article
- MAGC-DTI: modality-shared space and adaptive gated interactive cross-attention for drug-target interaction prediction.Scientific reports · 2026Article
- Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.Biotechnology journal · 2026Review
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025Review
- Biodegradable graphene nanocomposites as functional biomaterials: a review of their role in controlled drug delivery and tissue engineering.RSC advances · 2025Review
- In Vitro Skin Models as Non-Animal Methods for Dermal Drug Development and Safety Assessment.Pharmaceutics · 2025Review
- Modernizing Preclinical Drug Development: The Role of New Approach Methodologies.ACS pharmacology & translational science · 2025Review
- Establishing a Pharmacoinformatics Repository of Approved Medicines: A Database to Support Drug Product Development.Molecular pharmaceutics · 2025Article
- A Survey of Deep Learning Methods and Tools for Protein Binding Site Prediction.Methods in molecular biology (Clifton, N.J.) · 2025Review
- The computationally guided design of selective targeters of multiple proteins (STaMPs) as a new opportunity for small molecule drug discovery.Frontiers in pharmacology · 2025Review
- Development of cancer-associated fibroblasts-targeting polymeric nanoparticles loaded with 8-International journal of pharmaceutics: X · 2024Article
- Artificial Intelligence and Machine Learning Models for Predicting Drug-Induced Kidney Injury in Small Molecules.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Article
- De novo drug design through gradient-based regularized search in information-theoretically controlled latent space.Journal of computer-aided molecular design · 2024Article
- Safety Implications of Modulating Nuclear Receptors: A Comprehensive Analysis from Non-Clinical and Clinical Perspectives.Pharmaceuticals (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most small molecule drugs interact with unintended, often unknown, biological targets and these off-target interactions may lead to both preclinical and clinical toxic events. Undesired off-target interactions are often not detected using current drug discovery assays, such as experimental polypharmacological screens. Thus, improvement in the early identification of off-target interactions represents an opportunity to reduce safety-related attrition rates during preclinical and clinical development. In order to better identify potential off-target interactions that could be linked to predictable safety issues, a novel computational approach to predict safety-relevant interactions currently not covered was designed and evaluated. These analyses, termed Off-Target Safety Assessment (OTSA), cover more than 7,000 targets (~35% of the proteome) and > 2,46,704 preclinical and clinical alerts (as of January 20, 2019). The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known
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.