Atomic Design Transformer: xTB-Validated 3D Molecule Generation from Scaffolds

Abstract

We present an SE(3)-invariant transformer for 3D-molecule generation, the Atomic Design Transformer (ADT). ADT places atoms one at a time, autoregressively. The SE(3) invariance is achieved by tokenization: each new atom's position is encoded in a local coordinate frame of a previously placed atom. The network is a plain causal transformer. For evaluation, we introduce xTB-Validated Rate (XVR), which checks whether the molecular topology is preserved after xTB GFN2 geometry relaxation. On QM9, ADT is competitive with state-of-the-art baselines. For GEOM-Drugs, we present a quantitative benchmark of scaffold-conditional 3D generation, evaluating seven scaffolds (benzene, pyridine, pyrimidine, pyrazine, furan, thiophene, cyclohexane) on the 30-atom-truncated ground-state GEOM-Drugs dataset. XVR ranges from 11.1% (pyrazine) to 29.7% (benzene), all from a single trained model. The generated molecules are chemically diverse, and generation is fast by virtue of the plain causal-transformer backbone. Application to the 50-atom-truncated GEOM-Drugs dataset yields lower XVR while the per-bond and per-angle quality is retained. These results position ADT as a practical proposer for in silico molecular design.