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Kinked-β sheets are distinct peptide motifs involved in reversible amyloid fibril formation, which standard methods cannot identify. We present a machine learning-based framework to characterize these motifs, identify LARKS, and provide a repository for structural and kinetic studies.

弯折β-折叠（Kinked-β sheets）是参与可逆淀粉样纤维形成的独特肽基序，标准方法无法识别这类基序。我们提出一种基于机器学习的框架，用于表征这些基序、识别LARKS，并为结构与动力学研究提供资源库。