TriGlue：一种受生物学启发的生成模型，用于生成分子胶诱导的三元复合物

摘要

分子胶降解剂已成为一种前景广阔的靶向蛋白降解策略，其通过诱导E3泛素连接酶与靶蛋白之间形成三元复合物来发挥作用。尽管具有巨大的治疗潜力，分子胶的计算设计仍 largely 未被探索。与传统的基于结构的药物设计不同，分子胶设计受制于未知的蛋白质-蛋白质相互作用界面，需要同时模拟配体生成、蛋白质-蛋白质对接以及三元复合物组装。在本研究中，我们将分子胶设计形式化为一个三元复合物生成问题，并提出了一种受生物学启发的生成框架——TriGlue。受分子胶作用机制的启发，我们将三元复合物生成分解为两个耦合阶段：界面估计和界面条件下的复合物生成。首先，我们开发了一个SE(3)等变的界面估计模块，该模块能够从未结合的单体结构中预测具有几何约束的蛋白质-蛋白质相互作用界面。其次，我们引入了一个界面条件下的三元流匹配网络，该网络能够联合生成分子胶并预测组装三元复合物所需的刚体变换。大量实验表明，TriGlue能够生成化学上有效的分子并产生合理的三元复合物，这凸显了受生物学启发的生成建模在加速分子胶发现方面的潜力。我们的代码可在 https://github.com/yuliangyan0807/molecular-glue-design 获取。

English

Molecular glue degraders have emerged as a promising strategy for targeted protein degradation by inducing ternary complex formation between an E3 ubiquitin ligase and a target protein. Despite their therapeutic potential, computational design of molecular glues remains largely unexplored. Unlike conventional structure-based drug design, molecular glue design is governed by the unknown protein-protein interface and requires the simultaneous modeling of ligand generation, protein-protein docking, and ternary complex assembly. In this work, we formulate molecular glue design as a ternary complex generation problem and propose a biology-inspired generative framework, TriGlue. Motivated by the mechanism of molecular glue action, we decompose ternary complex generation into two coupled stages: interface estimation and interface-conditioned complex generation. First, we develop an SE(3)-equivariant interface estimation module that predicts a geometrically constrained protein-protein interface from unbound monomer structures. Second, we introduce an interface-conditioned ternary flow matching network that jointly generates the molecular glue and predicts the rigid-body transformation required to assemble the ternary complex. Extensive experiments demonstrate that TriGlue generates chemically valid molecules and produces plausible ternary complexes, which highlight the potential of biology-inspired generative modeling for accelerating molecular glue discovery. Our code is available at https://github.com/yuliangyan0807/molecular-glue-design.