AI 中文总结
本综述聚焦蛋白质结构预测领域的方法学演变，梳理了从进化约束到生成式建模的阶段与过渡，分析了模型能力的发展及局限。
AI 中文摘要
准确的蛋白质结构预测对结构生物学至关重要，因为蛋白质结构是分子功能的基础，也为机制解释提供依据。深度学习的最新进展已将该领域从多序列比对（MSA）驱动的单体折叠，转变为能够建模蛋白质复合物及日益异质的分子系统的更广泛框架。现有综述已从代表性模型、应用领域及蛋白质设计的角度总结了这些进展。在这些工作的基础上，本综述聚焦于该领域自身的方法学演变，通过三个密切相关的维度考察最新进展：表示与数据、架构与学习策略、置信度与评估。在此视角下，该领域被划分为四个方法学阶段和三个交叉过渡：从显式进化耦合特征与早期接触预测，到AlphaFold2、RoseTTAFold和ESMFold中的学习序列表示；从仅含蛋白质的单体折叠，到AlphaFold-Multimer、RoseTTAFoldNA和AlphaFold3中日益整合的异质分子系统建模；以及更近时期从预测导向的结构推理，到RFdiffusion及相关框架中设计导向的生成式建模。该框架有助于更清晰地理解方法学转变如何塑造了近期模型的能力、局限性及实际作用。
英文摘要
Accurate protein structure prediction is fundamental to structural biology because protein structure underlies molecular function and provides a basis for mechanistic interpretation. Recent advances in deep learning have transformed the field from multiple sequence alignment (MSA)-driven monomer folding into broader frameworks capable of modeling protein complexes and increasingly heterogeneous molecular systems. Existing reviews have summarized this progress from the perspectives of representative models, application domains, and protein design. Building on these efforts, this review focuses on the methodological evolution of the field itself. It examines recent developments through three closely related dimensions: representations and data, architectures and learning strategies, and confidence and evaluation. Within this perspective, the field is organized into four methodological phases and three cross-cutting transitions: from explicit evolutionary coupling features and early contact prediction to learned sequence representations in AlphaFold2, RoseTTAFold, and ESMFold; from protein-only monomer folding to increasingly integrated modeling of heterogeneous molecular systems in AlphaFold-Multimer, RoseTTAFoldNA, and AlphaFold3; and, more recently, from prediction-oriented structure inference to design-oriented generative modeling in RFdiffusion and related frameworks. This framework provides a clearer understanding of how methodological shifts have shaped the capabilities, limitations, and practical roles of recent models.
Comments15 pages, 4 figures, 4 tables. Preprint submitted to Elsevier
