Journal of Cheminformatics (Mar 2024)

Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery

  • Lingling Shen,
  • Jian Fang,
  • Lulu Liu,
  • Fei Yang,
  • Jeremy L. Jenkins,
  • Peter S. Kutchukian,
  • He Wang

DOI
https://doi.org/10.1186/s13321-024-00829-w
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 17

Abstract

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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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