What is it about?
This article describes a large screen for copper dependent inhibitors of S. Aureus. The data were used for modeling chemical properties, Bayesian machine learning using Biovia software and Assay Central. We also performed a prospective screen and identified a couple of anti-helminths that are copper dependent inhibitors.
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Why is it important?
The integration of HTS and machine learning with a large dataset.
Perspectives
This was a very nice collaboration with the University of Alabama that spanned approx a year. It also highlighted the importance of looking at as many statistics and external tests as possible..
Dr Sean Ekins
Collaborations in Chemistry
Read the Original
This page is a summary of: High-throughput screening and Bayesian machine learning for copper-dependent inhibitors of Staphylococcus aureus, Metallomics, January 2019, Oxford University Press (OUP),
DOI: 10.1039/c8mt00342d.
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