Detection of Frequent-Hitters Across Various HTS Technologies
Authors/Creators
- 1. Hit Discovery, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca,Gothenburg, Sweden
- 2. Hit Discovery, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca,Cambridge, UK
- 3. Department of Life Science Informatics, B-IT, LIMES ProgramUnit Chemical Biology and Medicinal Chemistry,Rheinische Friedrich-Wilhelms-Universit ̈at Bonn, Bonn, Germany
Description
A major conundrum in High-Throughput Screening stud-ies is the presence of frequent-hitters, which include non-selective com-pounds and molecules that are false positives in many screens. In ourstudy, we introduce a method to detect frequent-hitters specific to anassay technology using historical compounds’ structural information. Results from historic HTS campaigns, including artefact assays, arecurated on a cooperate database. Structural fingerprints are generatedfor each compound and used to train a machine-learning model able topredict the behavior of novel compounds.
Files
2019_Bookmatter_ArtificialNeuralNetworksAndMac.pdf
Files
(635.4 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:1072004fa2aec141ab670450fa774034
|
635.4 kB | Preview Download |