CHEML.IO: AN ONLINE DATABASE OF ML-GENERATED MOLECULES
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Zhumagambetov, Rustam
Kazbek, Daniyar
Shakipov, Mansur
Maksut, Daulet
Peshkov, Vsevolod A.
Fazli, Siamac
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Royal Society of Chemistry
Abstract
Several recent ML algorithms for de novo molecule generation have been utilized to create an open-access database of virtual molecules. The algorithms were trained on samples from ZINC, a free database of commercially available compounds. Generated molecules, stemming from 10 different ML frameworks, along with their calculated properties were merged into a database and coupled to a web interface, which allows users to browse the data in a user friendly and convenient manner. ML-generated molecules with desired structures and properties can be retrieved with the help of a drawing widget. For the case of a specific search leading to insufficient results, users are able to create new molecules on demand. These newly created molecules will be added to the existing database and as a result, the content as well as the diversity of the database keeps growing in line with the user's requirements.
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Zhumagambetov, R., Kazbek, D., Shakipov, M., Maksut, D., Peshkov, V. A., & Fazli, S. (2020). cheML.io: an online database of ML-generated molecules. RSC Advances, 10(73), 45189–45198. https://doi.org/10.1039/d0ra07820d
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Except where otherwised noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 United States
