D4: Distance Diffusion for a Truly Equivariant Molecular Design

Recent years have witnessed an increase in interest in leveraging generative models for de novo molecular design in drug discovery. Many State-of-the-Art (SotA) models incorporate the 3D structural information of the molecule, particularly atomic spatial coordinates. However, such approaches face challenges integrating SE(3) equivariance when trained on coordinates. This work explores the use of the distance matrix for molecular structures, natively SE(3) invariant, avoiding whatever the issue. Experimental evaluation shows that our proposed approach significantly improves upon MiDi, a SotA 3D molecule generator.