巴格尔:通过探索能源景观来进行蛋白质工程
Jakub Lála1, Ayham Al-Saffar1, Stefano Angioletti-Uberti1,2,3
1Department of Materials, Imperial College London, London, United Kingdom.
PLoS computational biology
|December 3, 2025
概括
我们介绍BAGEL,一个灵活的,开源的蛋白质工程框架. 它允许对定制蛋白质设计的序列空间进行无梯度的探索,民主化生物技术和疗法.
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.
- 生物技术是生物技术.
背景情况:
- 目前的深度学习蛋白质设计工具是刚性的和有限的.
- 现有的方法与不可区分或多目标的设计目标作斗争.
研究的目的:
- 介绍BAGEL,一个可编程蛋白质工程的模块化,开源框架.
- 能够灵活,无模型,无梯度地探索蛋白质序列空间.
- 民主化蛋白质设计,以实现更广泛的科学可访问性和创新.
主要方法:
- 将蛋白质设计正式化为采样,用于优化或探索的能量功能.
- 用用户定义的术语 (几何约束,序列相似性,结构信心) 构建能量函数.
- 支持多状态优化和先进的蒙特卡洛技术.
- 整合多种深度学习蛋白模型,以快速采用改进.
主要成果:
- 证明BAGEL在四个应用领域的多功能性: de novo结剂,内在无序表位,物种特异性结合和酶变异.
- 展示框架处理定制设计目标和优化策略的能力.
- 为传统的固定骨干和反向折叠方法提供灵活的替代方案.
结论:
- BAGEL通过提供一个用户友好的平台来加速新的蛋白质设计.
- 该框架抽象了技术复杂性,使先进的蛋白质工程更容易获得.
- 通过民主化设计,释放生物技术和治疗方面的创新潜力.
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