DiffBP: generative diffusion of 3D molecules for target protein binding.

ABSTRACT: Generating molecules that bind to specific proteins is an important but challenging task in drug discovery. Most previous works typically generate atoms autoregressively, with element types and 3D coordinates of atoms generated one by one. However, in real-world molecular systems, interactions among atoms are global, spanning the entire molecule, leading to pair-coupled energy function among atoms. With such energy-based consideration, modeling probability should rely on joint distributions rather than sequential conditional ones. Thus, the unnatural sequential auto-regressive approach to molecule generation is prone to violating physical rules, yielding molecules with unfavorable properties. In this study, we propose DiffBP, a generative diffusion model that generates molecular 3D structu

SUBMITTER: Lin H 

PROVIDER: S-EPMC11659876 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature