暗能量：蛋白质进化中功能的代价
Dark energy: the cost of function in protein evolution
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中文总结 AI 辅助
本文综述相关计算与实验方法，通过蛋白质语言模型等技术量化蛋白质进化中的暗能量，揭示其组分并阐明生物信息在序列-结构-功能间的流动机制。
中文摘要 AI 辅助
蛋白质的进化命运由折叠稳定性和生物功能共同驱动，这两种约束常相互冲突，产生挫败感并施加超出稳定性的功能代价。这些代价可由“暗能量”捕捉：即蛋白质序列的进化能量与其物理折叠能量的差值。深度突变扫描、蛋白质语言模型和逆折叠模型的最新进展，已实现了在蛋白质组范围内对暗能量的量化。本文综述了可大规模分离折叠与功能的计算及实验方法，揭示了暗能量组分，并为生物信息如何从序列流向结构、功能再返回序列提供了新见解。
英文摘要
The evolutionary fate of proteins is driven by both folding stability and biological function, dual constraints that often conflict, creating frustration and imposing functional costs beyond stability. These costs can be captured by a "dark energy": the difference between the evolutionary energy of protein sequences and their physical folding energy. Recent advances in deep mutational scanning, protein language models, and inverse-folding models have enabled the quantification of dark energy across the protein universe. We review the computational and experimental approaches that disentangle folding and function at scale, revealing a dark energy component and providing new insights into how biological information flows from sequence to structure to function and back to sequence.
