ReviewJournal of chemical information and modeling2022
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design.
Review in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
What it found
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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.
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Who cites it
56 citing papers in PubMed.
- In silico modeling and in vitro evaluation of antidiabetic potential of exopolysaccharides from Brassicaceae root endophytic bacteria.Journal, genetic engineering & biotechnology · 2026Article
- AIDrugDesigner: a web server for drug-like molecules generation and optimization.Bioinformatics (Oxford, England) · 2026Article
- Beyond the flat screen: evaluating virtual reality as a complementary tool for molecular docking in drug discovery.Journal of computer-aided molecular design · 2026Review
- End-to-End Intelligent Drug Discovery via a Scalable and Explainable Graph-Transformer Framework.Bioengineering (Basel, Switzerland) · 2026Article
- EasyDock 1.3: An Automated Pipeline for Molecular Docking.Journal of chemical information and modeling · 2026Article
- Deep generative models for 3D structure-based drug design and molecular optimisation: a comprehensive survey.Journal of computer-aided molecular design · 2026Review
- Prioritising search for virtual screening via preliminary interpretable low-feature likelihood-based rankings of drug-target activity measures.BMC bioinformatics · 2026Article
- Virtual screening and molecular dynamics analysis of Plasmodium falciparum dihydroorotate dehydrogenase (DHODH) inhibitors targeting pyrimidine biosynthesis pathway.Folia microbiologica · 2026Article
- 3DOpt: Benchmark for Automated Design of 3D Molecular Structures across the Periodic Table.Journal of chemical information and modeling · 2026Article
- Assessing the factors influencing the quality of pocket-conditioned 3D generative models.Journal of cheminformatics · 2026Article
- Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision.Pharmacopsychiatry · 2026Review
- Distribution-preserved sampling (DPS) for smarter machine learning assisted ultra-large-scale virtual screening.RSC advances · 2026Article
- Machine learning and free energy clustering reveal PAH protein binding linked to AD risk.iScience · 2026Article
- A simple compound prioritization method for drug discovery considering multi-target binding.Digital discovery · 2026Article
- Prodrug-ML: prodrug-likeness prediction via machine learning on sampled negative decoys.Journal of computer-aided molecular design · 2026Article
- Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation ofCurrent drug targets · 2026Article
- Computational Study of Enzyme Inhibition.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Transfer learning enables discovery of sub-micromolar antibacterials for ESKAPE pathogens from ultra-large chemical spaces.Chemical science · 2025Article
- Stereochemistry-aware string-based molecular generation.PNAS nexus · 2025Article
- MolPrice: assessing synthetic accessibility of molecules based on market value.Journal of cheminformatics · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The field of machine learning for drug discovery is witnessing an explosion of novel methods. These methods are often benchmarked on simple physicochemical properties such as solubility or general druglikeness, which can be readily computed. However, these properties are poor representatives of objective functions in drug design, mainly because they do not depend on the candidate compound's interaction with the target. By contrast, molecular docking is a widely applied method in drug discovery to estimate binding affinities. However, docking studies require a significant amount of domain knowledge to set up correctly, which hampers adoption. Here, we present dockstring, a bundle for meaningful and robust comparison of ML models using docking scores. dockstring consists of three components: (1) an open-source Python package for straightforward computation of docking scores, (2) an extensive dataset of docking scores and poses of more than 260,000 molecules for 58 medically relevant targets, and (3) a set of pharmaceutically relevant benchmark tasks such as virtual screening or
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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.