ArticleJournal of chemical information and modeling2011
CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions.
Article in Journal of chemical information and modeling, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed, 148 citations in OpenAlex.
- Docking-based virtual screening: Past, present, and future.Biophysical journal · 2026Review
- Template-guided method for protein-ligand complex structure prediction: Application to CASP15 protein-ligand studies.Proteins · 2023Article
- CoDock-Ligand: combined template-based docking and CNN-based scoring in ligand binding prediction.BMC bioinformatics · 2023Article
- Exploring Natural Alkaloids from Brazilian Biodiversity as Potential Inhibitors of theMolecules (Basel, Switzerland) · 2023Article
- Novel Sulfonamide-Triazine Hybrid Derivatives: Docking, Synthesis, and Biological Evaluation as Anticancer Agents.ACS omega · 2023Article
- Sunsetting Binding MOAD with its last data update and the addition of 3D-ligand polypharmacology tools.Scientific reports · 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
- Computational Identification of Possible Allosteric Sites and Modulators of the SARS-CoV-2 Main Protease.Journal of chemical information and modeling · 2022Article
- Identification of Cryptic Binding Sites Using MixMD with Standard and Accelerated Molecular Dynamics.Journal of chemical information and modeling · 2021Article
- DUBS: A Framework for DevelopingJournal of chemical information and modeling · 2020Article
- RASPD+: Fast Protein-Ligand Binding Free Energy Prediction Using Simplified Physicochemical Features.Frontiers in molecular biosciences · 2020Article
- Key Topics in Molecular Docking for Drug Design.International journal of molecular sciences · 2019Review
- Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking.Structure (London, England : 1993) · 2019Article
- Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight.Journal of computer-aided molecular design · 2019Article
- Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities.Frontiers in chemistry · 2019Review
- D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.Journal of computer-aided molecular design · 2019Article
- Visualizing convolutional neural network protein-ligand scoring.Journal of molecular graphics & modelling · 2018Article
- A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions.ACS omega · 2018Article
- Assessing protein-ligand interaction scoring functions with the CASF-2013 benchmark.Nature protocols · 2018Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
As part of the Community Structure-Activity Resource (CSAR) center, a set of 343 high-quality, protein-ligand crystal structures were assembled with experimentally determined K(d) or K(i) information from the literature. We encouraged the community to score the crystallographic poses of the complexes by any method of their choice. The goal of the exercise was to (1) evaluate the current ability of the field to predict activity from structure and (2) investigate the properties of the complexes and methods that appear to hinder scoring. A total of 19 different methods were submitted with numerous parameter variations for a total of 64 sets of scores from 16 participating groups. Linear regression and nonparametric tests were used to correlate scores to the experimental values. Correlation to experiment for the various methods ranged R(2) = 0.58-0.12, Spearman ρ = 0.74-0.37, Kendall τ = 0.55-0.25, and median unsigned error = 1.00-1.68 pK(d) units. All types of scoring functions-force field based, knowledge based, and empirical-had examples with high and low correlation, showing no bias/advantage for any particular approach. The data across all the participants were combined to identify 63 complexes that were poorly scored across the majority of the scoring methods and 123 complexes that were scored well across the majority. The two sets were compared using a Wilcoxon rank-sum test to assess any significant difference in the distributions of >400 physicochemical properties of the ligands and the proteins. Poorly scored complexes were found to have ligands that were the same size as those in well-scored complexes, but hydrogen bonding and torsional strain were significantly different. These comparisons point to a need for CSAR to develop data sets of congeneric series with a range of hydrogen-bonding and hydrophobic characteristics and a range of rotatable bonds.
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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.