新的蛋白质设计能够准难以处理的瘤基因接口
Varshika Ram Prakash1,2, Yusuf Najy1,2, Kalel Garrett1,2
1Department of Oncology, Wayne State University School of Medicine, Detroit, MI, USA.
bioRxiv : the preprint server for biology
|November 24, 2025
概括
一个新的AI平台DesignForge创建了新的微蛋白来准难以驱动癌症的蛋白质与蛋白质相互作用 (PPI). 这种方法为开发超越传统抗体和小分子的癌症疗法提供了新的途径.
科学领域:
- 计算生物学是一种计算生物学.
- 蛋白质工程是一种蛋白质工程.
- 药物发现 药物发现
背景情况:
- 涉及瘤驱动因素的蛋白质-蛋白质相互作用 (PPI) 由于其复杂性和对常规药物的耐药性,挑战了癌症点.
- 像抗体这样的现有疗法在组织透,细胞内传递和耐药性方面存在局限性,需要新的治疗方式.
研究的目的:
- 开发一个集成的计算框架,DesignForge,用于*de novo*设计针对难以处理的瘤性PPI的迷你蛋白质结合剂.
- 展示该平台在设计关键癌症标的结合剂方面的能力,包括PD-1/PD-L1,MYC/MAX和KRAS/RAF相互作用.
主要方法:
- 利用深度学习进行结构生成和序列优化.
- 集成的能量热点映射用于指导微型蛋白质设计.
- 采用AlphaFold2进行结构信心评估和基于MOE的热点参与分析.
主要成果:
- 成功设计PD-1模仿剂来破坏PD-1/PD-L1免疫检查点.
- 设计了针对MYC/MAX二元化接口的新型支架.
- 预计产生的KRAS结合剂会抑制RAF相互作用,具有高的结构信心和稳定性.
结论:
- DesignForge是一个可通用的*in silico*平台,用于合理设计治疗性蛋白质结合剂.
- 这种方法可以系统地针对以前难以治疗的瘤性PPI,超越抗体和小分子模式.
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