ArticleJournal of natural products2015
Phenotype-Guided Natural Products Discovery Using Cytological Profiling.
Article in Journal of natural products, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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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
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Multi-omics approaches: transforming the landscape of natural product isolation.Functional & integrative genomics · 2025Review
- Article
- Progress and challenges in exploring aquatic microbial communities using non-targeted metabolomics.The ISME journal · 2023Review
- Natural product fragment combination to performance-diverse pseudo-natural products.Nature communications · 2021Article
- Image-based profiling for drug discovery: due for a machine-learning upgrade?Nature reviews. Drug discovery · 2021Review
- Perspective on Improving the Relevance, Rigor, and Reproducibility of Botanical Clinical Trials: Lessons Learned From Turmeric Trials.Frontiers in nutrition · 2021Review
- Biologically active marine natural products and their molecular targets discovered using a chemical genetics approach.Natural product reports · 2020Review
- Improving natural product research translation: From source to clinical trial.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2020Article
- Advances in exploring the therapeutic potential of marine natural products.Pharmacological research · 2019Review
- Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning.Proceedings of machine learning research · 2019Article
- Macrophage Cytological Profiling and Anti-Inflammatory Drug Discovery.Assay and drug development technologies · 2019Article
- Systematic exploration of cell morphological phenotypes associated with a transcriptomic query.Nucleic acids research · 2018Article
- Machine learning and image-based profiling in drug discovery.Current opinion in systems biology · 2018Review
- Kalkipyrone B, a marine cyanobacterial γ-pyrone possessing cytotoxic and anti-fungal activities.Phytochemistry · 2016Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Phenotype-guided natural products discovery is emerging as a useful new discovery tool that addresses challenges in early, unbiased natural product biological annotation. These high-content approaches yield screening results that report directly on the impact of test compounds on cellular processes in target organisms and can be used to predict the modes of action of bioactive constituents from primary screening data. In this study we explored the use of our recently implemented cytological profiling platform for the isolation of compounds with a specific, predefined mode of action, namely, induction of mitotic arrest. Screening of a microbially derived extract library revealed six extracts whose cytological profiles clustered closely with those of known antimitotic agents from the pure compound training set. Subsequent examination of one of these extracts revealed the presence of two separate bioactive constituents, each of which possessed a unique cytological profile. The first, diketopiperazine XR334 (3), recapitulated the observed antimitotic phenotype of the original extract, demonstrating that cytological profiling can be used for the targeted isolation of compounds with specific modes of action. The second, nocapyrone L (6), possessed a cytological profile that clustered with known calcium channel modulators, in line with previous published activities for this compound class, indicating that cytological profiling is a flexible and powerful platform for the de novo characterization of compound modes of action.
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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.