ArticleJournal of computer-aided molecular design2020
D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.
Article in Journal of computer-aided molecular design, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 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
70 citing papers in PubMed.
- Docking-based virtual screening: Past, present, and future.Biophysical journal · 2026Review
- Evaluating molecular docking for binding affinity predictions: a systematic analysis of key parameters and the utility of AlphaFold2 structures for the Schrödinger dataset.Journal of computer-aided molecular design · 2026Article
- Sequence-based prediction of drug-target binding using machine learning, deep learning and ensemble models without 3D structural information.Scientific reports · 2026Article
- Large-Scale Collaborative Assessment of Binding Free Energy Calculations for Drug Discovery Using OpenFE.Journal of chemical information and modeling · 2026Article
- Enabling Automatic Generation of Protein-Ligand Complex Data Sets with Atomistic Detail.Journal of chemical information and modeling · 2026Article
- Evaluating generalization in protein-ligand cofolding methods.Nature structural & molecular biology · 2026Article
- Discovery of potential RSV fusion protein inhibitors from benzimidazole derivatives using QSAR, molecular docking, and ADMET evaluation methods.Molecular diversity · 2026Article
- The Open Molecular Software Foundation (OMSF) and the Growing Role of Open Source Software in Molecular Modeling.Journal of chemical information and modeling · 2026Review
- A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data.Journal of chemical information and modeling · 2026Article
- A fully automated benchmarking suite to compare macromolecular complexes.Nature methods · 2026Review
- Progress and Bottlenecks for Deep Learning in Computational Structure Biology: CASP Round XVI.Proteins · 2026Article
- Article
- Skill-File-Guided Virtual Screening: A Single-Target Formyl Peptide Receptor 2 Case Study of Large-Language-Model-Coordinated Physics and Diffusion Docking.Computational and structural biotechnology journal · 2026Article
- Updates to the CASP Infrastructure in 2024.Proteins · 2026Article
- A high-resolution data set of fatty acid-binding protein structures. II. Crystallographic overview, ligand classes and binding pose.Acta crystallographica. Section D, Structural biology · 2025Article
- ABCG2: A Milestone Charge Model for Accurate Solvation Free Energy Calculation.Journal of chemical theory and computation · 2025Article
- GRADE and X-GRADE: Unveiling Novel Protein-Ligand Interaction Fingerprints Based on GRAIL Scores.Journal of chemical information and modeling · 2025Article
- The Need for Continuing Blinded Pose- and Activity Prediction Benchmarks.Journal of chemical information and modeling · 2025Review
- MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025Review
- The algebraic extended atom-type graph-based model for precise ligand-receptor binding affinity prediction.Journal of cheminformatics · 2025Article
10 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
15 authors.
Funding
Abstract
The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.
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.