← 返回论文检索
ICML 2026PosterAccept (spotlight)

TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation

Hanqun CAO, Aastha Pal, Sophia Tang, Yinuo Zhang, Jingjie Zhang, Pheng Ann Heng, Pranam Chatterjee, PhD

The Chinese University of Hong Kong · University of Pennsylvania · national university of singaore, National University of Singapore · Department of Computer Science and Engineering, The Chinese University of Hong Kong

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。

摘要

Protein function is often controlled by ligands that bias the direction of state transitions, such as agonists and antagonists, rather than stabilizing a single conformation. This is especially important for clinically relevant G protein-coupled receptors (GPCRs), where therapeutic efficacy depends on functional directionality. Structure-based design methods optimize binding to static conformations and cannot represent non-reversible, directional effects or systematically distinguish agonist from antagonist behavior. To address this gap, we introduce **T**ransition-**D**irected **D**iscrete **D**iffusion for allosteric **B**inder design (**TD3B**), a sequence-based generative framework that designs binders with specified agonist or antagonist behavior via a directional transition control objective. TD3B combines a target-aware Direction Oracle, a soft binding-affinity gate, and amortized fine-tuning of a pre-trained discrete diffusion model, enabling targeted agonist and antagonist generation decoupled from binding affinity and unattainable by equilibrium-based or inference-only guidance baselines.