内在无序蛋白质的计算设计
Computational design of intrinsically disordered proteins
AI总结：
本综述探讨了内在无序蛋白质的计算从头设计，总结了在定制构象系综、分子识别和相行为方面的最新进展，并概述了整合知识、物理与机器学习方法的可扩展设计策略。
摘要：
蛋白质设计有望彻底改变生物技术和医学。尽管大多数研究集中在结构明确的蛋白质上，但随着对内在无序区域功能重要性的认识不断提高，加上其建模技术的改进，为其计算从头设计铺平了道路。本综述总结了在工程化具有定制构象系综、分子识别和相行为的内在无序区域方面的最新进展。我们讨论了将具有预测精度的模型与可扩展设计工作流程相结合所面临的挑战，并概述了整合基于知识、基于物理和机器学习方法的 emerging 策略。
英文摘要：
Protein design has the potential to revolutionize biotechnology and medicine. While most efforts have focused on proteins with well-defined structures, increased recognition of the functional significance of intrinsically disordered regions, together with improvements in their modeling, has paved the way to their computational de novo design. This review summarizes recent advances in engineering intrinsically disordered regions with tailored conformational ensembles, molecular recognition, and phase behavior. We discuss challenges in combining models with predictive accuracy with scalable design workflows and outline emerging strategies that integrate knowledge-based, physics-based, and machine-learning approaches.
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