ArticleChemical science2023
A generalized protein-ligand scoring framework with balanced scoring, docking, ranking and screening powers.
Article in Chemical science, 2023. 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
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
38 citing papers in PubMed.
- DockM8: an all-in-one open-source platform for consensus virtual screening in drug design.Journal of cheminformatics · 2026Article
- Docking-based virtual screening: Past, present, and future.Biophysical journal · 2026Review
- Atomic-level protein-ligand recognition with PBCNet2.0 for probe discovery.Nature chemical biology · 2026Article
- AI decodes protein-ligand binding.Nature chemical biology · 2026Article
- Graph-based drug-target interaction modeling: from representation learning to output-driven drug discovery.Briefings in bioinformatics · 2026Review
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- Article
- Molecular Dynamics Workflows to Compute Large-Scale Sets of Absolute Binding Free Energies Aiding Drug Candidate and Binding Pose Selection.Journal of chemical theory and computation · 2026Article
- GRIPHIN: grids of pharmacophore interaction fields for affinity prediction.Journal of cheminformatics · 2026Article
- BA-Pred and RMSD-Pred: Integrated Graph Neural Network Models for Accurate Protein-Ligand Binding Affinity and Binding Pose Prediction.Journal of chemical information and modeling · 2026Article
- Graph-based deep learning approach for high-throughput protein-DNA interaction scoring.Acta pharmacologica Sinica · 2026Article
- DeepMice: a novel protein-ligand molecular docking model based on multilevel mapping modules.Molecular diversity · 2026Article
- Could statistical potential models achieve comparable or better performance than deep learning models?Briefings in bioinformatics · 2026Article
- IgPose: a generative data-augmented pipeline for robust immunoglobulin-antigen binding prediction.Bioinformatics (Oxford, England) · 2026Article
- LamNet: an alchemical-path-aware graph neural network to accelerate binding free energy calculations for drug discovery and beyond.National science review · 2026Article
- AI-enhanced virtual screening approach to hit identification for GluN1/GluN3A NMDA receptor.Acta pharmacologica Sinica · 2026Article
- Extremely Randomized Trees to Determine Binding Affinity.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Flexible protein-ligand docking with diffusion-based side-chain packing.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- SCORCH2: A Generalized Heterogeneous Consensus Model for High-Enrichment Interaction-Based Virtual Screening.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- CarsiDock-Cov: A deep learning-guided approach for automated covalent docking and screening.Acta pharmaceutica Sinica. B · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Applying machine learning algorithms to protein-ligand scoring functions has aroused widespread attention in recent years due to the high predictive accuracy and affordable computational cost. Nevertheless, most machine learning-based scoring functions are only applicable to a specific task,
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.