使用RoseTTAFold All-Atom进行通用生物分子建模和设计
Rohith Krishna1,2, Jue Wang1,2, Woody Ahern1,2,3
1Department of Biochemistry, University of Washington, Seattle, WA 98105, USA.
Science (New York, N.Y.)
|March 7, 2024
概括
RoseTTAFold全原子模型复杂的生物组件,包括蛋白质,核酸和小分子. 这种新的深度学习方法可以设计出结合特定小分子的新型蛋白质.
科学领域:
- 计算生物学
- 结构生物学
- 生物化学
背景情况:
- 深度学习已经推进了蛋白质结构预测,但仅限于蛋白质系统.
- 模拟复杂的生物组件需要整合多种化学实体.
研究的目的:
- 开发一种能够模拟和设计超出蛋白质范围的复杂生物组件的深度学习框架.
- 为设计与非蛋白成分相互作用的蛋白质创建一个多功能工具.
主要方法:
- 引入了RoseTTAFold All-Atom (RFAA),使用混合残留和原子水平表示.
- 通过对特定设计的无声化任务进行微调,开发了RFdiffusionAll-Atom (RFdiffusionAA).
- 使用结晶学和结合测试进行实验验证.
主要成果:
- RFAA成功地模拟了蛋白质,核酸,小分子,金属和共价变异的组合.
- 通过RFdiffusionAA设计出新的蛋白质来结合特定的小分子.
- 已验证的设计包括蛋白质结合滴氧基因,血红素和比林.
结论:
- RoseTTAFold All-Atom和RFdiffusion All-Atom在复杂分子组件的建模和设计方面取得了重大进展.
- 这种方法为工程蛋白与所需的功能和相互作用开辟了新的途径.
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