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Related Concept Videos

Genetic Screens02:46

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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High-Throughput Screening of Microbial Isolates with Impact on Caenorhabditis elegans Health
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Frequent hitters: nuisance artifacts in high-throughput screening.

Zi-Yi Yang1, Jun-Hong He1, Ai-Ping Lu2

  • 1Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, PR China.

Drug Discovery Today
|January 29, 2020
PubMed
Summary
This summary is machine-generated.

Frequent hitters (FHs) are compounds causing false positives in drug discovery. This review covers FH mechanisms, detection methods, and computational filters to improve early drug discovery efficiency.

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Area of Science:

  • Drug discovery and development
  • Medicinal chemistry
  • Computational toxicology

Background:

  • Frequent hitters (FHs) pose a significant challenge in early drug discovery.
  • FHs are compounds that exhibit non-specific binding or cause false positives due to assay interferences.

Purpose of the Study:

  • To review the mechanisms of various FH types.
  • To survey experimental and computational methods for FH identification.
  • To discuss the rational application of FH filters in drug discovery.

Main Methods:

  • Literature review of FH mechanisms.
  • Survey of experimental detection techniques.
  • Review of computational prediction models for FH identification.

Main Results:

  • Categorization of FHs into aggregators, spectroscopic interference compounds, chemical reactive compounds, and promiscuous compounds.
  • Overview of common experimental assays for FH detection.
  • Discussion of computational approaches for predicting and filtering FHs.

Conclusions:

  • Understanding FH mechanisms is crucial for mitigating false positives.
  • A combination of experimental and computational methods enhances FH identification.
  • Rational application of FH filters can significantly improve early drug discovery efficiency.