新模型DiffDecip通过结合保守残基信息，提升药物分子与靶点蛋白的高亲和力结合能力。
A 3D pocket-aware and evolutionary conserved interaction guided diffusion model for molecular optimization
- 在扩散生成过程中引入蛋白-配体相互作用与残基进化保守性信息
- 生成分子与保守残基形成更多非共价相互作用，亲和力显著提升
- 适合需要精准靶向功能关键位点的药物优化任务
基于扩散模型的分子生成在结构导向药物设计中展现出良好前景，尤其通过结合结合相互作用引导的模型可生成高亲和力分子。然而，现有方法生成的分子往往未能与关键功能残基形成有效相互作用。本文提出新型3D靶向感知扩散模型DiffDecip，将蛋白-配体结合相互作用及残基进化保守性信息同时融入扩散与采样过程，用于骨架修饰的分子优化。实验表明，相较于基线模型DiffDec，DiffDecip在提升亲和力方面表现更优，能与蛋白口袋中高度保守残基形成更多非共价相互作用。
原文摘要 · Abstract (English)
Generating molecules that bind to specific protein targets via diffusion models has shown good promise for structure-based drug design and molecule optimization. Especially, the diffusion models with binding interaction guidance enables molecule generation with high affinity through forming favorable interaction within protein pocket. However, the generated molecules may not form interactions with the highly conserved residues, which are important for protein functions and bioactivities of the ligands. Herein, we developed a new 3D target-aware diffusion model DiffDecip, which explicitly incorporates the protein-ligand binding interactions and evolutionary conservation information of protein residues into both diffusion and sampling process, for molecule optimization through scaffold decoration. The model performance revealed that DiffDecip outperforms baseline model DiffDec on molecule optimization towards higher affinity through forming more non-covalent interactions with highly conserved residues in the protein pocket.
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