超分子化学
纳米技术
构造(python库)
计算机科学
生物相容性材料
纳米材料
纳米结构
序列(生物学)
肽
材料科学
化学
核酸检测
自组装
纳米-
分子识别
肽核酸
作者
Li-Ying Wang,Z. H. Li,Ting Wang,Min Han,Hongwei An,Hao Wang
摘要
Programmable peptide self-assembly enables the precise construction of supramolecular materials, establishing it as a defining frontier in nanomaterials research. This review systematically explores the collective contribution of sequence design, secondary structure regulation (including α-helices, β-sheets, and cyclic conformations), and dynamic modulation, and hierarchical organization in facilitating the creation of well-defined nanostructures such as nanotubes, nanopores, and nanocages. Artificial intelligence and computational modeling have emerged as critical tools to guide peptide design and predict assembly pathways, thereby enabling a strategic shift from empirical screening to mechanism-driven design. The review further highlights nanopore-based detection applications, demonstrating the potential for highly accurate, biocompatible detection of ions, nucleic acids, and proteins at single-molecule resolution. By integrating molecular design with biological function, this "from sequence-design to ordered structures to advanced applications" paradigm establishes a foundational framework for the development of precisely constructed functional supramolecular materials.
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