Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis
Open accessAbstract
Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.
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Dose-dependent phenotypic trajectories can provide additional layers of information that assist in discriminating the activity of different compounds.
“While screening at multiple concentrations incurs additional experimental complexity and investment of time and resources, we found that dose-dependent phenotypic trajectories can provide additional layers of information that assist in discriminating the activity of different compounds, reinforcing observations from a previous study that sought to classify compound MOAs based on dose-dependent tra”
From A statistical framework for high-content phenotypic profiling using cellular feature distributions (2022) · cites this paper as [21]
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References 29 · Cited by 16
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- [21]Newman EM, Longmate J, Lenz H, Carroll M, Stalter S, Lim D, et al Phase I and clinical pharmacokinetic evaluation of the DNA methyltransferase inhibitor 5-fluoro-2'-deoxycytidine: a California Cancer Consortium Study. Proc Am Soc Clin Oncol. 2002; 21: 108a.
- Authors
- Twarog, N. R., Low, J. A., Currier, D. G., Miller, G., Chen, T., & Shelat, A. A.
- Affiliations
- St. Jude Children's Research Hospital (US)
- Corresponding author
- Shelat, Anang A.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2016-02-17
- Volume
- 11
- Issue
- 2
- Pages
- e0149439
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4757101
- OpenAlex
- W2276949837
- Cited by
- 16
- References
- 29
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 2 · 2018: 1 · 2017: 2 · 2016: 2
- FWCI
- 1.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- American Lebanese Syrian Associated Charities
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- small molecule drugs, high-content imaging, phenotypic screening, linear discriminant analysis, hierarchical clustering, compound clustering, off-target effects, rigosertib
- MeSH terms
- DNA Damage, HeLa Cells, Histones, Humans, Microscopy, Phenotype, Cluster Analysis, Discriminant Analysis, Principal Component Analysis, Small Molecule Libraries
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