Published September 9, 2019 | Version v1
Conference paper Open

Analysis and Modelling of False Positivesin GPCR Assays

  • 1. Lead Discovery Center GmbH, Otto-Hahn-Straße 15,44227 Dortmund, Germany
  • 2. Institute of Structural Biology, Helmholtz Zentrum München−GermanResearch Center for Environmental Health (GmbH), Ingolstaedter Landstrasse 1,85764 Neuherberg, Germany

Description

G-Protein Coupled Receptors (GPCR) are involved in all the major signaling pathways. As a result, they often serve as potential target for therapeutic drugs. In this study we analyze publicly available assays involving different classes of GPCR to identify false positives. Using the latest developments in Machine Learning, we then build models that can predict such compound with high confidence. Given the ubiquity of GPCR assays, we believe such models will be very helpful in flagging potential false positives for further testing

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Ghosh2019_Chapter_AnalysisAndModellingOfFalsePos.pdf

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Additional details

Funding

BIGCHEM – Big Data in Chemistry 676434
European Commission