A pharmacophore-guided deep learning approach for bioactive molecular generation
A pharmacophore-guided deep learning approach for bioactive molecular generation
About this item
Full title
Author / Creator
Zhu, Huimin , Zhou, Renyi , Cao, Dongsheng , Tang, Jing and Li, Min
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
The rational design of novel molecules with the desired bioactivity is a critical but challenging task in drug discovery, especially when treating a novel target family or understudied targets. We propose a Pharmacophore-Guided deep learning approach for bioactive Molecule Generation (PGMG). Through the guidance of pharmacophore, PGMG provides a fl...
Alternative Titles
Full title
A pharmacophore-guided deep learning approach for bioactive molecular generation
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_f5e57503f22b4116b2ef75bc2ed788dd
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f5e57503f22b4116b2ef75bc2ed788dd
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-023-41454-9
