蛋白质进化的深度模型在时间上产生现实的进化轨迹和功能性蛋白质
bioRxiv : the preprint server for biology
|February 27, 2026
概括
蛋白质进化在时间 (PEINT) 是一个深度学习框架,该框架模拟蛋白质进化与站点相互作用,改进模拟和生成功能新型序列. 这促进了蛋白质工程和遗传学推断的进步.
科学领域:
- 计算生物学 计算生物学
- 分子进化分子进化
- 生物信息学是一种生物信息学.
背景情况:
- 蛋白质进化模型对于生物技术至关重要,但通常假设独立的地点,限制现实主义.
- 现有的模型很难模拟复杂的进化轨迹,并纳入现场相互作用.
研究的目的:
- 介绍PEINT (蛋白质进化时间),这是一个深度学习框架,用于模拟蛋白质进化与复杂的站点相互作用.
- 能够实现蛋白质进化的真实模拟,捕捉保护模式和动态.
主要方法:
- 开发了一种灵活的深度学习框架 (PEINT) 来模拟蛋白质序列随时间的演变.
- 结合了网站之间的复杂相互作用,并从未对齐的序列中学习了indel动力学.
- 捕获了更高阶的表观相互作用和插入-删除过程.
主要成果:
- 从数以百万计的蛋白质序列中,PEINT学习了现实的进化模式.
- 模拟准确地复制了自然进化特征,包括保护和特定家族的动态.
- 生成新的功能性蛋白质序列 (例如,碳酸酶变体),保留酶活性.
结论:
- PEINT 可实现现实的蛋白质进化模拟,探索新的序列空间,同时尊重约束.
- 该框架通过提供强大的生成建模工具来推进遗传学推断和蛋白质工程.
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