Time-Dependent Directional Guidance for Physics-Informed Molecular Diffusion Models

Diffusion models have become effective generators of 3D molecular structures, yet geometric plausibility alone does not ensure physical suitability for structure-based design. A common remedy is to add energy-based guidance during sampling. We argue that this naive intervention can behave like a forceful external correction rather than a compatible part of the reverse diffusion process, producing two critical failure modes: temporal misalignment, where a fixed physical signal ignores the coarse-to-fine denoising rhythm, and directional conflict, where raw energy gradients oppose chemically plausible generative motion. We propose TDGM, a Time-Dependent Directional Guidance Model that provides a plug-and-play, lightweight framework for aligning physical guidance with both denoising time and update direction. TDGM uses a temporal schedule to synchronize guidance strength with different generation stages, a directional projection to filter conflicting gradient components, and multi-scale physical priors to cover geometry, steric safety, pocket interaction, and global placement. On 100 CrossDock pockets with 10,000 generated molecules, TDGM obtains the best Vina docking score, QED, and Lipinski score among the compared methods, while MolPilot remains strongest on diversity and normalized SA. The results show that properly scheduled and directionally filtered physical guidance improves binding-oriented and drug-likeness endpoints while preserving explicit trade-offs across molecular statistics.