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液体分子的结合记忆

Binding memory of liquid molecules.

作者信息

Qin Shiyi, Yang Zhi, Liu Huimin, Wang Xiaoli, Miao Bing, Hou Shangguo, Huang Kai

机构信息

Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.

Department of Chemistry, College of Sciences, Northeastern University, Shenyang, China.

出版信息

Nat Commun. 2025 Jul 16;16(1):6555. doi: 10.1038/s41467-025-61630-3.

Abstract

Understanding the binding dynamics of liquid molecules is of fundamental importance in physical and life sciences. However, nanoscale fast dynamics pose great challenges for experimental characterization. Conventionally, the binding dynamics have been assumed to be memoryless. Here, we integrate large scale computer simulation, scaling theory, and real-time single particle tracking microscopy with high spatiotemporal precision to unveil a universal memory effect in the binding dynamics of liquid molecules. This binding memory can be quantified by a binding time autocorrelation function, whose power-law decay depends on binding affinity, the topological and materials properties of the surrounding environment and the heterogeneity of the binding landscape. Context-dependent biomolecular binding memory is likely exploited by biological systems to regulate biochemical reactions and biophysical processes. Deciphering this binding memory offers a novel strategy to probe complex biological systems and advanced soft materials.

摘要

理解液体分子的结合动力学在物理和生命科学中具有至关重要的意义。然而,纳米尺度的快速动力学给实验表征带来了巨大挑战。传统上,人们认为结合动力学是无记忆的。在此,我们整合了大规模计算机模拟、标度理论以及具有高时空精度的实时单粒子追踪显微镜技术,以揭示液体分子结合动力学中的一种普遍记忆效应。这种结合记忆可以通过结合时间自相关函数来量化,其幂律衰减取决于结合亲和力、周围环境的拓扑和材料特性以及结合景观的异质性。生物系统可能利用这种依赖于上下文的生物分子结合记忆来调节生化反应和生物物理过程。解读这种结合记忆为探究复杂生物系统和先进软材料提供了一种新策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89d4/12267512/49bbce69b1f1/41467_2025_61630_Fig2_HTML.jpg

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