Machine Learning Assisted Hit Prioritization for High Throughput Screening in Drug Discovery-Reference-Cited by-同舟云学术

Machine Learning Assisted Hit Prioritization for High Throughput Screening in Drug Discovery

Published:2024-03-15 Issue: Volume: Page:
ISSN:2374-7943
Container-title:ACS Central Science
language:en
Short-container-title:ACS Cent. Sci.

Author:

Boldini Davide¹,Friedrich Lukas²,Kuhn Daniel²,Sieber Stephan A.¹^ORCID

Affiliation:

1. TUM School of Natural Sciences, Department of Bioscience, Center for Functional Protein Assemblies (CPA), Technical University of Munich, 85748 Garching bei München, Germany

2. The Healthcare business of Merck KGaA, 64293 Darmstadt, Germany

Funder

European Research Council

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acscentsci.3c01517

Reference50 articles.

1. High-Throughput Screening: today’s biochemical and cell-based approaches

2. PubChem in 2021: new data content and improved web interfaces

3. Impact of high-throughput screening in biomedical research

4. Rethinking drug design in the artificial intelligence era

5. PAINS in the Assay: Chemical Mechanisms of Assay Interference and Promiscuous Enzymatic Inhibition Observed during a Sulfhydryl-Scavenging HTS

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