| Literature DB >> 32722365 |
Sven Bulterijs1, Bart P Braeckman1.
Abstract
Population aging is one of the largest challenges of the 21st century. As more people live to advanced ages, the prevalence of age-related diseases and disabilities will increase placing an ever larger burden on our healthcare system. A potential solution to this conundrum is to develop treatments that prevent, delay or reduce the severity of age-related diseases by decreasing the rate of the aging process. This ambition has been accomplished in model organisms through dietary, genetic and pharmacological interventions. The pharmacological approaches hold the greatest opportunity for successful translation to the clinic. The discovery of such pharmacological interventions in aging requires high-throughput screening strategies. However, the majority of screens performed for geroprotective drugs in C. elegans so far are rather low throughput. Therefore, the development of high-throughput screening strategies is of utmost importance.Entities:
Keywords: aging; drug screening; geroprotective drug; longevity; phenotypic screen; target-based screen
Year: 2020 PMID: 32722365 PMCID: PMC7463874 DOI: 10.3390/ph13080164
Source DB: PubMed Journal: Pharmaceuticals (Basel) ISSN: 1424-8247
The strengths and weaknesses of target-based versus phenotypic screening in drug discovery. SAR, structure–activity relationship.
| Target-Based Screening | Phenotypic Screening in Cells | Phenotypic Screening in Small Organisms (e.g., | ||||
|---|---|---|---|---|---|---|
| Strengths | Weaknesses | Strengths | Weaknesses | Strengths | Weaknesses | |
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| Known target selected for screen. | Cannot find new targets. | Target agnostic. | Target identification can be cumbersome. | Target agnostic. | Target identification can be cumbersome. |
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| In vitro study on isolated targets. | In vitro but on whole cells. Cells used can be of human origin. Even patient-derived primary cells or in vitro reprogrammed cells from patient-derived fibroblasts. | Access to disease relevant cell types can be difficult. | In vivo, small organisms contain multiple cell types and even organ systems thus better capturing disease processes that depend on cell interactions and/or systemic factors. | Small model organisms may not fully capture human biology. | |
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| False positives due to nonspecific mechanisms (fluorescence quenching, aggregation). | False positives due to compounds that target generic mechanisms such as protein synthesis which affect the assayed phenotype but are not specific enough to be used as drug leads. | False positives due to compounds that target generic mechanisms such as protein synthesis which affect the assayed phenotype but are not specific enough to be used as drug leads. | |||
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| Will identify all hits that modify the target of interest. | Hits will include molecules that cannot be used as drug leads (such as cytotoxic compounds). | Initial screen may already inform about toxicity of compounds (cell viability). | If the library is screened at high concentrations, low-potency effects could cloud the interpretation of the results. | Initial screen already informs about toxicity of compounds (organism viability). | If the library is screened at high concentrations, low-potency effects could cloud the interpretation of the results. However, if too low concentrations are used, then no effect may be seen because drug concentrations in the organism tend to be much smaller than those in the medium. |
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| Very amendable for lead optimization (SAR). | Exclusion of hits that have poor pharmacokinetic and pharmacodynamic properties but that could still be amendable to medicinal chemistry optimization. In addition, lead optimization (SAR) can be more difficult. | Exclusion of hits that have poor pharmacokinetic and pharmacodynamic properties but that could still be amendable to medicinal chemistry optimization. In addition, lead optimization (SAR) can be more difficult. | |||
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| Low amounts of compound required. | Low amounts of compound required. | Large amounts of compound required. | |||
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| Very high throughput | High throughput | Low throughput | |||
Figure 1The influence of various biotic and abiotic factors on drug screening in C. elegans.
A comparison of the various automated lifespan machines for C. elegans. NGM, nematode growth medium; FUdR, 5-fluoro-2-deoxyuridine.
| Manual | Wormbot | Automated Lifespan Machines | WorMotel | Microfluidics | LFASS | |
|---|---|---|---|---|---|---|
|
| Liquid or NGM | NGM | Modified version of NGM | NGM | Liquid | See manual, assay in liquid |
|
| Optional | Needed | Needed | Needed | Not needed | Generally needed |
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| Very low | High (144 wells) | Moderate (16 Petri plates) | High (240 wells) | Low (depends on used chip) | Very high (96- or 384-well plates) |
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| Very low | High | High | High | High | Very high |
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| Both are possible | Population | Population | Individual | Both are possible | Population |
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| Very low | High | Moderate | Very high | Moderate | Moderate |
|
| No | Yes | Yes | Yes | Depends | Yes |