ArticleNucleic acids research2016
BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 706 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
706 citing papers in PubMed.
- Alzheimer's disease target and drug discovery by leveraging multiomics and electronic health data.Nature neuroscience · 2026Article
- Machine Learning-Guided Discovery of Natural BACE1 Inhibitors with Enzymatic and Cellular Validation.ACS omega · 2026Article
- Chemical language models for early-stage drug discovery: applications, pitfalls, and future directions.Journal of computer-aided molecular design · 2026Review
- Predicting Oncogenic Mutants of Epidermal Growth Factor Receptor in Lung Cancer by Molecular Dynamics Simulation with Machine Learning.ACS omega · 2026Article
- Confidence-Gated Triage: Coupling Drug-Target Affinity and ADME-T Predictions to Prioritise Compounds for Docking.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Free energy perturbation and machine learning-assisted identification of novel molecules for the Mycobacterium tuberculosis KasA protein: a fragment-based drug design approach.Molecular diversity · 2026Article
- MolGraphGAN: a graph transformer-adversarial framework for target-specific molecule generation.Journal of computer-aided molecular design · 2026Article
- AI-driven drug design: a comprehensive review.Journal of computer-aided molecular design · 2026Review
- Gaps in AI-Driven Pharmacokinetic Property Prediction for Early Drug Development: A Scoping Review.Journal of chemical information and modeling · 2026Article
- UniPept: A Universal Model for Predicting Peptide Properties Based on Atom-Residue Dual-Scale Integration.Interdisciplinary sciences, computational life sciences · 2026Article
- Benchmarking Classical and Quantum Machine Learning for Potency Prediction across Ten Therapeutically Relevant Targets.ACS medicinal chemistry letters · 2026Article
- Integrated computational and experimental approaches for drug repurposing targeting key Mycobacterium tuberculosis proteins.Molecular diversity · 2026Article
- ASCENT: an active transfer learning paradigm for efficient drug-target interaction prediction.Science China. Life sciences · 2026Article
- Deep Contrastive Learning for High-Throughput Prediction of Drug Resistance Mutations from Sequences.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Chemical features consistently associated with kinase inhibitor activity: a cross-target SHAP analysis under scaffold-split evaluation.Molecular diversity · 2026Article
- Prioritising search for virtual screening via preliminary interpretable low-feature likelihood-based rankings of drug-target activity measures.BMC bioinformatics · 2026Article
- Tetrapeptide inhibitors of BACE-1 revealed by combined data-driven screening and physics-based free-energy refinement.Molecular diversity · 2026Article
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- Contextual Representation Learning With ResNet Refinement and Deep Classification for Enhanced Drug Target Interaction Prediction.Chemical biology & drug design · 2026Article
- In Silico Selection of GAT-1 Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2026Article
646 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
BindingDB, www.bindingdb.org, is a publicly accessible database of experimental protein-small molecule interaction data. Its collection of over a million data entries derives primarily from scientific articles and, increasingly, US patents. BindingDB provides many ways to browse and search for data of interest, including an advanced search tool, which can cross searches of multiple query types, including text, chemical structure, protein sequence and numerical affinities. The PDB and PubMed provide links to data in BindingDB, and vice versa; and BindingDB provides links to pathway information, the ZINC catalog of available compounds, and other resources. The BindingDB website offers specialized tools that take advantage of its large data collection, including ones to generate hypotheses for the protein targets bound by a bioactive compound, and for the compounds bound by a new protein of known sequence; and virtual compound screening by maximal chemical similarity, binary kernel discrimination, and support vector machine methods. Specialized data sets are also available, such as binding data for hundreds of congeneric series of ligands, drawn from BindingDB and organized for use in validating drug design methods. BindingDB offers several forms of programmatic access, and comes with extensive background material and documentation. Here, we provide the first update of BindingDB since 2007, focusing on new and unique features and highlighting directions of importance to the field as a whole.
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.