对分子的基准测试对折叠方法进行基准测试,以预测三元结构
Yiyan Liao1, Jintao Zhu2, Juan Xie3
1School of Life Sciences, Peking University, Beijing 100871, China.
Journal of chemical information and modeling
|October 10, 2025
概括
开发用于向蛋白质降解的分子粘剂 (MGs) 需要精确的三元复合模型. 目前的计算模型在预测这些复杂结构方面存在局限性,突出了需要改进方法的需要.
科学领域:
- 计算生物学是一种计算生物学.
- 结构生物学是结构生物学.
- 药物发现 药物发现
背景情况:
- 分子剂 (MGs) 通过调节蛋白质-蛋白质相互作用 (PPIs) 来针对蛋白质降解提供了一种新的治疗方法.
- 合理的MGs设计受到精确建模三元复合体的挑战,特别是小分子诱导的de novo相互作用的阻碍.
研究的目的:
- 评估最先进的拼接模型在预测MG参与的三元复合体结构方面的表现.
- 为评估该领域的计算方法建立全面的基准数据集 (MG-PDB和MGBench).
主要方法:
- MG-PDB数据集的系统策划,包括221个非共价的MG-三元复合体.
- 创建使用基于时间的分区来排除培训数据的MGBench基准集.
- 在三元复合预测上对AlphaFold 3,Boltz-1,Chai-1,Protenix和RoseTTAFold All-Atom进行基准测试.
主要成果:
- 在PPI接口预测 (50.6%) 和MG-蛋白相互作用恢复 (32.9%) 中,AlphaFold 3在测试的共同折叠模型中表现最高.
- 模型性能在很大程度上归因于记忆而不是概括,在预测大型接口,域-域相互作用和MG降解器复合体方面存在重大挑战.
- 现有的模型与新型E3酶系统扎,这表明它们依赖已知的相互作用模式.
结论:
- 当前的共同折叠模型在精确建模MG参与的三元复合体内的原子级相互作用方面存在根本的局限性.
- 开发的MG-PDB和MGBench资源为推进分子三元复合模型中的计算方法提供了必要的基准.
- 进一步的进步对于分子的合理设计至关重要,特别是对于新的治疗点.
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