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cheML.io: an online database of ML-generated molecules
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9058596/ https://www.ncbi.nlm.nih.gov/pubmed/35516285 http://dx.doi.org/10.1039/d0ra07820d |
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author | Zhumagambetov, Rustam Kazbek, Daniyar Shakipov, Mansur Maksut, Daulet Peshkov, Vsevolod A. Fazli, Siamac |
author_facet | Zhumagambetov, Rustam Kazbek, Daniyar Shakipov, Mansur Maksut, Daulet Peshkov, Vsevolod A. Fazli, Siamac |
author_sort | Zhumagambetov, Rustam |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9058596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-90585962022-05-04 cheML.io: an online database of ML-generated molecules Zhumagambetov, Rustam Kazbek, Daniyar Shakipov, Mansur Maksut, Daulet Peshkov, Vsevolod A. Fazli, Siamac RSC Adv Chemistry 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. The Royal Society of Chemistry 2020-12-22 /pmc/articles/PMC9058596/ /pubmed/35516285 http://dx.doi.org/10.1039/d0ra07820d Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Zhumagambetov, Rustam Kazbek, Daniyar Shakipov, Mansur Maksut, Daulet Peshkov, Vsevolod A. Fazli, Siamac cheML.io: an online database of ML-generated molecules |
title | cheML.io: an online database of ML-generated molecules |
title_full | cheML.io: an online database of ML-generated molecules |
title_fullStr | cheML.io: an online database of ML-generated molecules |
title_full_unstemmed | cheML.io: an online database of ML-generated molecules |
title_short | cheML.io: an online database of ML-generated molecules |
title_sort | cheml.io: an online database of ml-generated molecules |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9058596/ https://www.ncbi.nlm.nih.gov/pubmed/35516285 http://dx.doi.org/10.1039/d0ra07820d |
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