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Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with <i>in vivo</i> efficacy

2025-09-25

Abstract excerpt

Deep learning shows promise in structure-based drug discovery, yet challenges persist in generating pharmacologically plausible molecules with valid 3D conformation and decent binding mode in the pocket. We introduce SE3-BiLingoMol, an SE(3)-equivariant Transformer for pocket-based 3D molecule generation, addressing two key limitations of existing language-model approaches. First, it uses Geometric Algebra Transfo...

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Identifiers and source

Literature Corpus work
02b3c040-66b4-5889-a381-ab7c7fe590ff
DOI
10.1101/2025.09.23.678079
Open publication

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Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with <i>in vivo</i> efficacyDOI 10.1101/2025.09.23.678079
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