ReviewACS omega2019
Evolving Concept of Activity Cliffs.
Review in ACS omega, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 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
85 citing papers in PubMed.
- Rational design of anticancer metallodrugs.Journal of computer-aided molecular design · 2026Article
- Article
- How effective are contrastive learning-based approaches for activity-cliff prediction?bioRxiv : the preprint server for biology · 2026Article
- Article
- Integrated AI-Driven Discovery of MAPK3 Inhibitors for Oral Inflammatory and Proliferative Diseases.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Reliable Apparent Permeability Prediction Through Benchmarking, Stability, Uncertainty Quantification, and Explainable Machine Learning.CPT: pharmacometrics & systems pharmacology · 2026Article
- Activity-cliff awareness enables robust graph learning for molecular property prediction.Nature communications · 2026Article
- Advances in Dendrimer-Based Anti-Infective Systems: In Vivo Insights and Perspectives.Pharmaceutics · 2026Review
- Improving hit discovery by integrating activity cliff sensitivity into active learning.Bioinformatics (Oxford, England) · 2026Article
- Deep learning speeds the search for new antibiotic scaffolds.Nature biotechnology · 2026Article
- Deep-learning-based virtual screening of antibacterial compounds.Nature biotechnology · 2026Article
- Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.Chemical biology & drug design · 2026Review
- Emerging Insights into the Distinct Pharmacological Mechanisms of Buprenorphine.Journal of chemical information and modeling · 2026Article
- Accurate prediction of activity cliff compounds based on bioactivity profiles depends on assay nearest neighbor relationships.Journal of cheminformatics · 2026Article
- Structure- and Ligand-Based Discovery of Novel 3-Chymotrypsin-Like Protease Nonpeptidomimetic Hits.ChemMedChem · 2026Article
- Computational chemistry methods based on MNDO and tools for improving their accuracy.Journal of molecular modeling · 2026Article
- SPARFlow: a KNIME workflow for integrated structure-activity or structure-property relationship analysis.Journal of cheminformatics · 2026Article
- AMPCliff: Quantitative definition and benchmarking of activity cliffs in antimicrobial peptides.Journal of advanced research · 2026Article
- Generative Chemistry Platform for Small Molecules Targeting RNA: A Case Study for Chemical Optimization.Computational and structural biotechnology journal · 2026Article
- Structure-Aware Compound-Protein Affinity Prediction via Graph Neural Networks with Group Lasso Regularization.Computational and structural biotechnology journal · 2026Article
25 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Activity cliffs (ACs) are generally defined as pairs or groups of structurally similar compounds that are active against the same target but have large differences in potency. Accordingly, ACs capture chemical modifications that strongly influence biological activity. Therefore, they are of particular interest in structure-activity relationship (SAR) analysis and compound optimization. The AC concept is much more complex than it may appear at a first glance, especially if one aims to represent ACs computationally and identify them systematically. To these ends, molecular similarity and potency difference criteria must be carefully considered for AC assessment. Furthermore, ACs are often perceived differently in medicinal and computational chemistry, depending on whether they are studied on a case-by-case basis or systematically. For practical applications, intuitive access to AC information plays a major role. Over the years, the AC concept has been further refined and extended. Herein, we review the evolution of the AC concept, emphasizing new analysis schemes and findings that help to better understand ACs and extract SAR knowledge from them.
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.