ArticleNature protocols2018
Assessing protein-ligand interaction scoring functions with the CASF-2013 benchmark.
Article in Nature protocols, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed.
- Beyond the flat screen: evaluating virtual reality as a complementary tool for molecular docking in drug discovery.Journal of computer-aided molecular design · 2026Review
- GAMT-GINE: A Graph Isomorphism Network Integrating Continuous Spatial Awareness and Multi-Task Learning for Protein-Ligand Binding Affinity Prediction.International journal of molecular sciences · 2026Article
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- DVNDTA: a dual virtual node based heterogeneous interaction model for accurate prediction of drug-target affinity.BMC bioinformatics · 2026Article
- GraphTransDTA: Drug-Target Affinity Prediction with Graph Transformer for Multimodal Data Fusion.Interdisciplinary sciences, computational life sciences · 2026Article
- GRIPHIN: grids of pharmacophore interaction fields for affinity prediction.Journal of cheminformatics · 2026Article
- Discovery of potential RSV fusion protein inhibitors from benzimidazole derivatives using QSAR, molecular docking, and ADMET evaluation methods.Molecular diversity · 2026Article
- Article
- Applications of Artificial Intelligence in Drug Repurposing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Fast and Accurate Prediction of Tautomer Ratios in Aqueous Solution via a Siamese Neural Network.Journal of chemical theory and computation · 2025Article
- Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data.Communications chemistry · 2025Article
- Resolving data bias improves generalization in binding affinity prediction.Nature machine intelligence · 2025Article
- Edge-enhanced interaction graph network for protein-ligand binding affinity prediction.PloS one · 2025Article
- DTBind: A Mechanism-Driven Deep Learning Framework for Accurate Prediction of Drug-Target Molecular Recognition.Research (Washington, D.C.) · 2025Article
- DeepTGIN: a novel hybrid multimodal approach using transformers and graph isomorphism networks for protein-ligand binding affinity prediction.Journal of cheminformatics · 2024Article
- Conformational Space Profiling Enhances Generic Molecular Representation for AI-Powered Ligand-Based Drug Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs.BMC biology · 2024Article
- DEAttentionDTA: protein-ligand binding affinity prediction based on dynamic embedding and self-attention.Bioinformatics (Oxford, England) · 2024Article
- Advances in machine-learning approaches to RNA-targeted drug design.Artificial intelligence chemistry · 2024Article
- GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Scoring functions are a group of computational methods widely applied in structure-based drug design for fast evaluation of protein-ligand interactions. To date, a whole spectrum of scoring functions have been developed based on different assumptions or algorithms. Therefore, it is important to both the end users and the developers of scoring functions that their performance be objectively assessed. We have developed the comparative assessment of scoring functions (CASF) benchmark as an open-access solution for scoring function evaluation. The latest CASF-2013 benchmark enables evaluation of the so-called 'scoring power', 'ranking power', 'docking power', and 'screening power' of a given scoring function with a high-quality test set of 195 complexes formed between diverse protein molecules and their small-molecule ligands. Evaluation results of the standard scoring functions implemented in several mainstream software programs (including Schrödinger, MOE, Discovery Studio, SYBYL, and GOLD) are provided as reference. This benchmark has become popular among the scoring function community since its first release. In this protocol, we provide detailed descriptions of the data files included in the CASF-2013 package and step-by-step instructions on how to conduct the performance tests with the ready-to-use computer scripts included in the package. This protocol is expected to lower the technical hurdles in front of new and existing users of the CASF-2013 benchmark. On a standard desktop workstation, it takes roughly half an hour to complete the whole evaluation procedure for one scoring function, once the required inputs, i.e., the results computed on the test set, are ready to use.
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