用于双靶点分子设计的融合贝叶斯流网络
Fused Bayesian Flow Networks for Dual-Target Molecular Design
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- School of Computer Science, Shanghai Jiao Tong University（上海交通大学计算机科学学院）
- Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)（广东省人工智能与数字经济实验室（深圳））
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中文总结 AI 辅助
针对现有双靶点分子生成方法难以充分整合双靶标特征的问题，提出融合贝叶斯流网络FusedBFN，通过分布融合与乘积专家公式实现双靶点分子设计，实验证实其生成的分子兼具强结合亲和力与良好性质。
中文摘要 AI 辅助
双靶点药物设计旨在生成能同时与两种靶蛋白相互作用的三维分子，为发现针对复杂疾病的多药理学化合物提供了有前景的途径。尽管近期的生成模型在单靶点药物设计中展现出令人鼓舞的性能，但现有的双靶点方法要么聚焦于序列生成，要么在基于扩散的生成轨迹中引入额外的预测漂移项，这限制了其充分整合两个靶标特征信息的能力。我们提出FusedBFN，一种用于双靶点分子设计的融合贝叶斯流网络（Bayesian Flow Network，BFN）。FusedBFN将双靶点生成建模为统一连续参数空间中的分布融合，并采用乘积专家公式在整个生成过程中整合双靶点信息。为解决双靶点结构数据稀缺的问题，我们利用预训练的靶标感知BFN模型作为共享骨干。我们进一步引入基于化学感知先验的对齐方法和无先验的口袋对齐策略，以构建对齐的双靶点上下文。大量实验表明，FusedBFN生成的分子对双靶点具有强结合亲和力，同时保持了良好的分子性质。
英文摘要
Dual-target drug design aims to generate 3D molecules that can simultaneously interact with two target proteins, offering a promising route for discovering polypharmacological compounds against complex diseases. While recent generative models have shown encouraging performance in single-target drug design, existing dual-target approaches either focus on sequence generation or introduce an additional predictive drift term into the diffusion-based generative trajectory, which limits their ability to fully integrate feature information from both targets. We propose FusedBFN, a fused Bayesian flow network (BFN) for dual-target molecular design. FusedBFN formulates dual-target generation as distribution fusion in a unified continuous parameter space and employs a product-of-experts formulation to incorporate dual-target information throughout the generative process. To address the scarcity of dual-target structural data, we leverage a pretrained target-aware BFN model as the shared backbone. We further introduce a chemically aware prior-based alignment method and a prior-free pocket alignment strategy to construct aligned dual-target contexts. Extensive experiments demonstrate that FusedBFN generates molecules with strong binding affinity toward dual targets while maintaining favorable molecular properties.
