基于扩散桥的药效团引导的药物从头设计
Pharmacophore-guided de novo drug design with diffusion bridge
AI总结:
提出PharmacoBridge,一种药效团引导的从头药物设计方法,利用扩散桥在SE(3)等变变换下将药效团空间排列转化为分子结构,实现对生化特征的精细控制,生成与靶点高亲和力的候选药物。
摘要:
从头设计具有治疗特定生物靶点潜力的生物活性药物分子,是药物发现过程中的一项重要任务。现有方法倾向于利用靶点蛋白的口袋结构来条件化分子生成。然而,即使是靶点蛋白的口袋区域也可能包含冗余信息,因为并非口袋中的所有原子都负责与配体相互作用。在本研究中,我们提出了PharmacoBridge,这是一种药效团引导的从头设计方法,旨在通过扩散桥生成诱导所需生物活性的候选药物。我们的方法采用扩散桥,在SE(3)等变变换的方式下,有效地将空间中的药效团排列转化为分子结构,从而对生成分子上的最佳生化特征排列提供精细控制。实验证明,PharmacoBridge能够生成与潜在蛋白靶点表现出高结合亲和力的命中候选物。
英文摘要:
De novo design of bioactive drug molecules with potential to treat desired biological targets is a profound task in the drug discovery process. Existing approaches tend to leverage the pocket structure of the target protein to condition the molecule generation. However, even the pocket area of the target protein may contain redundant information since not all atoms in the pocket is responsible for the interaction with the ligand. In this work, we propose PharmacoBridge, a phamacophore-guided de novo design approach to generate drug candidates inducing desired bioactivity via diffusion bridge. Our method adapts the diffusion bridge to effectively convert pharmacophore arrangements in the spatial space into molecular structures under the manner of SE(3)-equivariant transformation, providing sophisticated control over optimal biochemical feature arrangements on the generated molecules. PharmacoBridge is demonstrated to generate hit candidates that exhibit high binding affinity with potential protein targets.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。