Drug-likeness scoring based on unsupervised learning.
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ABSTRACT:
SUBMITTER: Lee K
PROVIDER: S-EPMC8729801 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
Publications
Drug-likeness scoring based on unsupervised learning.
Lee Kyunghoon K Jang Jinho J Seo Seonghwan S Lim Jaechang J Kim Woo Youn WY
Chemical science 20211214 2
Drug-likeness prediction is important for the virtual screening of drug candidates. It is challenging because the drug-likeness is presumably associated with the whole set of necessary properties to pass through clinical trials, and thus no definite data for regression is available. Recently, binary classification models based on graph neural networks have been proposed but with strong dependency of their performances on the choice of the negative set for training. Here we propose a novel unsupe ...[more]
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