ArticleACS omega2020
graphDelta: MPNN Scoring Function for the Affinity Prediction of Protein-Ligand Complexes.
Article in ACS omega, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed.
- Machine Learning Enables Rapid Prediction of Acid-Reducing Agent Drug Interactions: A Streamlined Complement to PBPK Modeling.CPT: pharmacometrics & systems pharmacology · 2026Article
- A hybrid high activity aware framework integrating graph attention network and transformer for half maximal inhibitory concentration prediction.Frontiers in immunology · 2026Article
- Article
- Analysis of the Toxicological Profile ofPlants (Basel, Switzerland) · 2025Article
- Drug Resistance Predictions Based on a Directed Flag Transformer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- EM-PLA: environment-aware heterogeneous graph-based multimodal protein-ligand binding affinity prediction.Bioinformatics (Oxford, England) · 2025Article
- A beginner's approach to deep learning applied to VS and MD techniques.Journal of cheminformatics · 2025Review
- iScore: A ML-Based Scoring Function for De Novo Drug Discovery.Journal of chemical information and modeling · 2025Article
- Normalized Protein-Ligand Distance Likelihood Score for End-to-End Blind Docking and Virtual Screening.Journal of chemical information and modeling · 2025Article
- Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data.Communications chemistry · 2025Article
- Robustly interrogating machine learning-based scoring functions: what are they learning?Bioinformatics (Oxford, England) · 2025Article
- AI meets physics in computational structure-based drug discovery for GPCRs.npj drug discovery · 2025Review
- Resolving data bias improves generalization in binding affinity prediction.Nature machine intelligence · 2025Article
- Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.Journal of chemical information and modeling · 2024Article
- Multiscale topology-enabled structure-to-sequence transformer for protein-ligand interaction predictions.Nature machine intelligence · 2024Article
- Machine Learning Empowering Drug Discovery: Applications, Opportunities and Challenges.Molecules (Basel, Switzerland) · 2024Review
- Prediction of protein-ligand binding affinity via deep learning models.Briefings in bioinformatics · 2024Review
- Integrated Molecular Modeling and Machine Learning for Drug Design.Journal of chemical theory and computation · 2023Review
- The Impact of Data on Structure-Based Binding Affinity Predictions Using Deep Neural Networks.International journal of molecular sciences · 2023Article
- A practical guide to machine-learning scoring for structure-based virtual screening.Nature protocols · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this work, we present graph-convolutional neural networks for the prediction of binding constants of protein-ligand complexes. We derived the model using multi task learning, where the target variables are the dissociation constant (
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.