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DOE OSTI · 2438161

Annual Report for Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery

Kim, H.
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Abstract

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we plan to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We also plan to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task to identify pan-coronavirus protease inhibitors such as SARS-CoV-2. While the overall goals and milestones remain consistent with the original proposal, certain technical details have been modified, which we will describe in this report.

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BibTeXRIS

Kim, H.. 2024-08-23. Annual Report for Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery. https://doi.org/10.2172/2438161

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