MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space

Understand

Generative models for structure-based drug design (SBDD) have shown promising results in recent years.

• Existing works mainly focus on how to generate molecules with higher binding affinity, ignoring the feasibility prerequisites for generated 3D poses and resulting in false positives.
• We conduct thorough studies on key factors of ill-conformational problems when applying autoregressive methods and diffusion to SBDD, including mode collapse and hybrid continuous-discrete space.
• In this paper, we introduce MolCRAFT, the first SBDD model that operates in the continuous parameter space, together with a novel noise reduced sampling strategy.