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Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery.
Shen, Lingling; Fang, Jian; Liu, Lulu; Yang, Fei; Jenkins, Jeremy L; Kutchukian, Peter S; Wang, He.
Afiliação
  • Shen L; Novartis Biomedical Research, Cambridge, MA, 02139, USA. lingling.shen@novartis.com.
  • Fang J; Novartis Biomedical Research, Cambridge, MA, 02139, USA.
  • Liu L; Novartis Biomedical Research, Cambridge, MA, 02139, USA.
  • Yang F; Novartis Biomedical Research, Cambridge, MA, 02139, USA.
  • Jenkins JL; Novartis Biomedical Research, Cambridge, MA, 02139, USA.
  • Kutchukian PS; Novartis Biomedical Research, Cambridge, MA, 02139, USA.
  • Wang H; Novartis Biomedical Research, Cambridge, MA, 02139, USA. he.wang@novartis.com.
J Cheminform ; 16(1): 33, 2024 Mar 21.
Article em En | MEDLINE | ID: mdl-38515171
ABSTRACT
We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug discovery process. This workflow utilized a three-dimensional (3D) generative modeling method Pocket2Mol, for the de novo design of molecules in spatial perspective for the targeted protein structures, followed by filters for chemical-physical properties and drug-likeness, structure-activity relationship analysis, and clustering to generate top virtual hit scaffolds. In our WDR5 case study, we acquired a focused set of 2029 compounds after a targeted searching within Novartis archived library based on the virtual scaffolds. Subsequently, we experimentally profiled these compounds, resulting in a novel chemical scaffold series that demonstrated activity in biochemical and biophysical assays. Pocket Crafter successfully prototyped an effective end-to-end 3D generative chemistry-based workflow for the exploration of new chemical scaffolds, which represents a promising approach in early drug discovery for hit identification.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article