3 papers
cs.LG2026
NEAT-POCKET: Pocket-Conditioned Autoregressive 3D Molecular Generation with a Neighborhood-Guided Set Transformer
Roxane Axel Jacob, Daniel Rose, Thierry Langer +1
AI-driven de novo molecular design offers a promising route to accelerate early-stage drug discovery by generating novel ligands directly within target protein binding pockets. We…
cs.LG2025
NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation
Daniel Rose, Roxane Axel Jacob, Johannes Kirchmair +1
Transformer-based autoregressive models offer an efficient alternative to diffusion- and flow-matching-based approaches for generating 3D molecules. One challenge remains: standard…
cs.LG2024
PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching
Daniel Rose, Oliver Wieder, Thomas Seidel +1
The increasing size of screening libraries poses a significant challenge for the development of virtual screening methods for drug discovery, necessitating a re-evaluation of tradi…