具有独立于预训结构预测模型的排泄扩散网络的新型蛋白质设计
Yufeng Liu1,2, Sheng Wang1,2, Jixin Dong1,2
1Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, China.
Nature methods
|October 9, 2024
概括
潜水扩散 (SCUBA-D) 是一种新的蛋白质设计模型,可以产生新的蛋白质折叠. 这种新方法通过减少错误和增强规范化来改进现有模型,从而导致准确和实验验证的蛋白质结构.
科学领域:
- 计算生物学 计算生物学
- 蛋白质工程是指蛋白质工程.
- 人工智能在生物学中的应用
背景情况:
- 最近的蛋白质结构设计方法,如RF扩散,利用无声扩散概率模型.
- 这些方法往往依赖于微调现有的蛋白质结构预测网络,如RoseTTAFold,用于蛋白质骨干的破坏.
研究的目的:
- 引入SCUBA-扩散 (SCUBA-D),一种新的蛋白质骨干,消除扩散的概率模型.
- 通过对序列表示和对抗性损失的共传播,增强模型规范化并最大限度地减少数据分布失误.
主要方法:
- 从头开始训练了SCUBA-扩散 (SCUBA-D),包括序列表示的共扩散.
- 用对抗性损失来解决数据分布失误的问题.
- 该模型通过将其性能与射频扩散进行比较和通过实验验证来评估.
主要成果:
- 在生成实验可行的蛋白质结构方面,SCUBA-D与RF扩散相匹配.
- SCUBA-D产生了由RoseTTAFold无法预测的新型蛋白质折叠.
- 实验验证,包括16个设计蛋白和一个蛋白质复合物的X射线结晶学,证实了SCUBA-D的准确性.
结论:
- 深度生成模型可以扩展到设计复杂的物理物体,如蛋白质结构.
- 解决数据分布失误等问题对于在结构生物学中推进生成模型至关重要.
- SCUBA-D代表了新型蛋白质设计的重大进步,使得蛋白质能够产生前所未有的折叠.
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