3D-EDiffMG: 3D equivariant diffusion-driven molecular generation to accelerate drug discovery.

ABSTRACT: Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular stru

SUBMITTER: Xu C 

PROVIDER: S-EPMC12268068 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature