ArticleCommunications chemistry2024
Benchmarking compound activity prediction for real-world drug discovery applications.
Article in Communications chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed.
- Pharmacological stratification of public bioactivity databases: a reusable, OECD-anchored curation and benchmarking framework demonstrated for opioid receptors.Digital discovery · 2026Article
- Technical review of artificial intelligence in TCR-T therapy.Journal of the National Cancer Center · 2026Review
- Artificial intelligence in impurity prediction: current landscape, challenges, and future directions.Journal of computer-aided molecular design · 2026Review
- Doing More with Less: Accurate and Scalable Ligand Free Energy Calculations by Focusing on the Binding Site.Journal of chemical information and modeling · 2026Article
- Reading between the Chains: Surface Mapping and Druggable Pockets on the Biological Assemblies of DENV-2's Protein E.ACS omega · 2026Article
- Applications of Metabolomics in the Development of Biomedicine and Biotechnology.Advances in experimental medicine and biology · 2026Review
- Structure-Property Associations: Breaking Paradigms for Linking Chemical Structures and Biological Properties in Drug Discovery.ChemMedChem · 2026Article
- Benchmarking Sequence-Based Compound-Protein Interaction Prediction through Constructing a Debiased Data Set CDPN.Journal of chemical information and modeling · 2025Article
- A Benchmark Set of Bioactive Molecules for Diversity Analysis of Compound Libraries and Combinatorial Chemical Spaces.Journal of chemical information and modeling · 2025Article
- From High Dimensions to Human Insight: Exploring Dimensionality Reduction for Chemical Space Visualization.Molecular informatics · 2025Article
- Artificial intelligence-, organoid-, and organ-on-chip-powered models to improve pre-clinical animal testing of vaccines and immunotherapeutics: potential, progress, and challenges.Frontiers in artificial intelligence · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Identifying active compounds for target proteins is fundamental in early drug discovery. Recently, data-driven computational methods have demonstrated promising potential in predicting compound activities. However, there lacks a well-designed benchmark to comprehensively evaluate these methods from a practical perspective. To fill this gap, we propose a Compound Activity benchmark for Real-world Applications (CARA). Through carefully distinguishing assay types, designing train-test splitting schemes and selecting evaluation metrics, CARA can consider the biased distribution of current real-world compound activity data and avoid overestimation of model performances. We observed that although current models can make successful predictions for certain proportions of assays, their performances varied across different assays. In addition, evaluation of several few-shot training strategies demonstrated different performances related to task types. Overall, we provide a high-quality dataset for developing and evaluating compound activity prediction models, and the analyses in this work may inspire better applications of data-driven models in drug discovery.
Identifiers
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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.