GlueFinder:一个数据驱动的框架,用于合理发现分子
Jeffrey Skolnick1, Bharath Srinivasan2,3,4,5, Hongyi Zhou1
1Center for the Study of Systems Biology, Georgia Institute of Technology, 950 Atlantic Dr NW, Atlanta, GA 30332, USA.
bioRxiv : the preprint server for biology
|November 24, 2025
概括
我们开发了GlueFinder,这是一个计算平台,用于发现能够实现向蛋白质降解的分子. 这种无偏见的方法扩大了E3结合酶和蛋白质标的范围,用于新的治疗策略.
科学领域:
- 生物化学 生物化学
- 结构生物信息学 结构生物信息学
- 药物发现 药物发现 药物发现
背景情况:
- 分子剂通过与标蛋白和E3无酸酶形成三元复合物来促进向蛋白质的降解.
- 分子的合理设计受到界面识别的有限理解和依赖VHL和Cereblon等特定结合酶的限制.
研究的目的:
- 推出GlueFinder,这是一个系统和公正的平台,用于发现分子.
- 为了利用结构生物信息学来识别蛋白质-蛋白质接口附近的新型可链接站点.
- 扩大E3结合酶和用于分子介导蛋白质降解的治疗标的谱.
主要方法:
- 利用结构生物信息学挖掘蛋白质数据库,寻找与蛋白质接口相邻的潜在粘合剂结合口袋.
- 验证的GlueFinder使用实验解决的二维结构与已知和预测的粘合剂的基准.
- 应用GlueFinder治疗相关的目标:EGFR,HER2和KRAS.
主要成果:
- 预测的候选粘合剂为EGFR (24),HER2 (111) 和KRAS (148) 招募大量不同的E3酶.
- 证明了GlueFinder诱导非本土EGFR复合物的能力,这表明可以形成新的三元组合.
- 建立了一个一般的,以计算为指导的分子发现策略,独立于特定的结合酶支架.
结论:
- GlueFinder为分子发现提供了可通用的策略,将设计与现有的支架和酶依赖性脱.
- 该平台通过扩大可用的E3连接酶库来扩大向蛋白质降解的范围和精度.
- 这种方法促进了分子的机制驱动的系统开发,用于各种治疗应用.
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