Conditional Synthesis of 3D Molecules with Time Correction Sampler

TL;DR

This paper introduces TACS, a novel diffusion-based method with a Time Correction Sampler for improved conditional 3D molecular generation, balancing property targeting with sample validity.

Contribution

It presents a new time-aware guidance technique and a diffusion sampler that together enhance conditional molecular synthesis while maintaining molecular validity.

Findings

Significant improvement in conditional 3D molecule generation quality

Effective control of molecular properties during synthesis

Potential applications in drug discovery and materials science

Abstract

Diffusion models have demonstrated remarkable success in various domains, including molecular generation. However, conditional molecular generation remains a fundamental challenge due to an intrinsic trade-off between targeting specific chemical properties and generating meaningful samples from the data distribution. In this work, we present Time-Aware Conditional Synthesis (TACS), a novel approach to conditional generation on diffusion models. It integrates adaptively controlled plug-and-play "online" guidance into a diffusion model, driving samples toward the desired properties while maintaining validity and stability. A key component of our algorithm is our new type of diffusion sampler, Time Correction Sampler (TCS), which is used to control guidance and ensure that the generated molecules remain on the correct manifold at each reverse step of the diffusion process at the same time. Our proposed method demonstrates significant performance in conditional 3D molecular generation and offers a promising approach towards inverse molecular design, potentially facilitating advancements in drug discovery, materials science, and other related fields.