ArticleJournal of chemical information and modeling2016
CSAR Benchmark Exercise 2013: Evaluation of Results from a Combined Computational Protein Design, Docking, and Scoring/Ranking Challenge.
Article in Journal of chemical information and modeling, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed, 64 citations in OpenAlex.
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- Evaluating generalization in protein-ligand cofolding methods.Nature structural & molecular biology · 2026Article
- A fully automated benchmarking suite to compare macromolecular complexes.Nature methods · 2026Review
- The Need for Continuing Blinded Pose- and Activity Prediction Benchmarks.Journal of chemical information and modeling · 2025Review
- The Histone Deacetylase Family: Structural Features and Application of Combined Computational Methods.Pharmaceuticals (Basel, Switzerland) · 2024Review
- In the quest for histone deacetylase inhibitors: current trends in the application of multilayered computational methods.Amino acids · 2023Review
- Template-guided method for protein-ligand complex structure prediction: Application to CASP15 protein-ligand studies.Proteins · 2023Article
- Characterization of allosteric modulators that disrupt androgen receptor co-activator protein-protein interactions to alter transactivation-Drug leads for metastatic castration resistant prostate cancer.SLAS discovery : advancing life sciences R & D · 2023Article
- Protein-Ligand Docking in the Machine-Learning Era.Molecules (Basel, Switzerland) · 2022Review
- Scoring Functions for Protein-Ligand Binding Affinity Prediction using Structure-Based Deep Learning: A Review.Frontiers in bioinformatics · 2022Article
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- DUBS: A Framework for DevelopingJournal of chemical information and modeling · 2020Article
- Optimization of Protein Thermostability and Exploitation of Recognition Behavior to Engineer Altered Protein-DNA Recognition.Structure (London, England : 1993) · 2020Article
- D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.Journal of computer-aided molecular design · 2020Article
- Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4.Journal of computer-aided molecular design · 2020Article
- D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU.Journal of computer-aided molecular design · 2019Article
- Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking.Structure (London, England : 1993) · 2019Article
- Binding mode information improves fragment docking.Journal of cheminformatics · 2019Article
- Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight.Journal of computer-aided molecular design · 2019Article
Corrections and comments
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Authors and funding
14 authors at 3 institutions in 1 country.
Funding
Abstract
Community Structure-Activity Resource (CSAR) conducted a benchmark exercise to evaluate the current computational methods for protein design, ligand docking, and scoring/ranking. The exercise consisted of three phases. The first phase required the participants to identify and rank order which designed sequences were able to bind the small molecule digoxigenin. The second phase challenged the community to select a near-native pose of digoxigenin from a set of decoy poses for two of the designed proteins. The third phase investigated the ability of current methods to rank/score the binding affinity of 10 related steroids to one of the designed proteins (pKd = 4.1 to 6.7). We found that 11 of 13 groups were able to correctly select the sequence that bound digoxigenin, with most groups providing the correct three-dimensional structure for the backbone of the protein as well as all atoms of the active-site residues. Eleven of the 14 groups were able to select the appropriate pose from a set of plausible decoy poses. The ability to predict absolute binding affinities is still a difficult task, as 8 of 14 groups were able to correlate scores to affinity (Pearson-r > 0.7) of the designed protein for congeneric steroids and only 5 of 14 groups were able to correlate the ranks of the 10 related ligands (Spearman-ρ > 0.7).
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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.