Bruno E. Correia

The work introduces LDDM (Large Drug Discovery Model), a unified 3D generative framework supporting constrained and unconstrained docking, fragment linking and growing, and de novo design, together with a programmable design algorithm that produces synthetically accessible compounds satisfying fine-grained objectives; the authors experimentally validated designed or optimised ligands for five therapeutically relevant protein targets, achieving high success rates and identifying molecules with confirmed binding affinity while synthesizing only a small number of generated compounds, with the best designs structurally characterised by NMR spectroscopy and X-ray crystallography indicating high prediction accuracy.

The work introduces LDDM (Large Drug Discovery Model), a unified 3D generative framework supporting constrained and unconstrained docking, fragment linking and growing, and de novo design, together with a programmable design algorithm that produces synthetically accessible compounds satisfying fine-grained objectives; the authors experimentally validated designed or optimised ligands for five therapeutically relevant protein targets, achieving high success rates and identifying molecules with confirmed binding affinity while synthesizing only a small number of generated compounds, with the best designs structurally characterised by NMR spectroscopy and X-ray crystallography indicating high prediction accuracy.