用生化反应网络统一蛋白与分子表示，让模型更好理解生物系统。
ReactEmbed: A Plug-and-Play Module for Unifying Protein-Molecule Representations Guided by Biochemical Reaction Networks
- 基于反应网络构建加权图，对齐蛋白和分子嵌入
- 在跨域任务上实现强性能，无需重新训练
- 轻量插件式设计，适合快速集成到现有模型
当前先进模型将蛋白和分子分别嵌入到独立的表示空间，限制了对系统性生物过程的建模。我们提出ReactEmbed，一个轻量级、可即插即用的模块，通过生化反应网络提供功能上下文，基于共参与反应定义共享功能范畴的原则，将ESM-3、MolFormer等模型的冻结嵌入，通过加权反应图和专用采样策略对齐至统一空间。该过程丰富了单模态嵌入，并在跨域基准测试中表现出色。ReactEmbed为统一生物表示提供了实用方案，无需昂贵的重新训练。代码与数据库已开源。
原文摘要 · Abstract (English)
State-of-the-art models represent proteins and molecules in separate embedding manifolds, limiting the modeling of systemic biological processes. We introduce ReactEmbed, a lightweight, plug-and-play module that bridges this gap. ReactEmbed leverages biochemical reaction networks as a source of functional context, based on the principle that co-participation in reactions defines a shared functional scope. The module aligns frozen embeddings from models like ESM-3 and MolFormer into a unified space using a weighted reaction graph and a specialized sampling strategy. This process enriches unimodal embeddings and enables strong performance on cross-domain benchmarks. ReactEmbed offers a practical method to unify biological representations without costly retraining. The code and database are available for open use\footnote{https://github.com/amitaysicherman/ReactEmbeded}.
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