Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 62, Issue 10, Pages 2280-2292Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.1c01311
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Funding
- Engineering and Physical Sciences Research Council (EPSRC)
- LifeArc
- UCB Pharma [EP/L016044/1]
- EPSRC [EP/N509711/1]
- F. Hoffmann-La Roche AG
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This paper proposes a novel method for fragment elaboration, STRIFE, which overcomes the limitations of previous methods and demonstrates excellent performance in a large-scale evaluation.
Despite recent interest in deep generative models for scaffold elaboration, their applicability to fragment-to-lead campaigns has so far been limited. This is primarily due to their inability to account for local protein structure or a user's design hypothesis. We propose a novel method for fragment elaboration, STRIFE, that overcomes these issues. STRIFE takes as input fragment hotspot maps (FHMs) extracted from a protein target and processes them to provide meaningful and interpretable structural information to its generative model, which in turn is able to rapidly generate elaborations with complementary pharmacophores to the protein. In a large-scale evaluation, STRIFE outperforms existing, structure-unaware, fragment elaboration methods in proposing highly ligand-efficient elaborations. In addition to automatically extracting phannacophoric information from a protein target's FHM, STRIFE optionally allows the user to specify their own design hypotheses.
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