Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Image based annotation of Chemogenomic Libraries for Phenotypic Screening

Version 1 : Received: 7 January 2022 / Approved: 11 January 2022 / Online: 11 January 2022 (23:53:13 CET)

A peer-reviewed article of this Preprint also exists.

Tjaden, A.; Chaikuad, A.; Kowarz, E.; Marschalek, R.; Knapp, S.; Schröder, M.; Müller, S. Image-Based Annotation of Chemogenomic Libraries for Phenotypic Screening. Molecules 2022, 27, 1439. Tjaden, A.; Chaikuad, A.; Kowarz, E.; Marschalek, R.; Knapp, S.; Schröder, M.; Müller, S. Image-Based Annotation of Chemogenomic Libraries for Phenotypic Screening. Molecules 2022, 27, 1439.

Journal reference: Molecules 2022, 27, 1439
DOI: 10.3390/molecules27041439

Abstract

Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still poses a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.

Keywords

Phenotypic Screening; High Content Imaging; Chemogenomics; Machine Learning; Cell cycle

Subject

LIFE SCIENCES, Cell & Developmental Biology

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