Identification and Classification of Functional Split G‑Quadruplexes Using Machine Learning-Guided Activity Screening

Split G-quadruplexes are considered excellent tools for biosensing and diagnostics, but splitting G-quadruplexes may often lead to a loss of function, limiting their effectiveness. This study aims to identify and classify functional split G-quadruplexes based on the ability of the G-quadruplex motif to generate a fluorescence turn-on response and undergo phase separation. A series of split G-quadruplexes were designed, and their characterization was conducted using fluorescence spectroscopy, fluorescence microscopy, UV–vis spectroscopy, and circular dichroism to investigate their functional properties (fluorogenic response, phase separation, and DNAzyme activity). Multivariate analysis and machine learning-based pattern recognition revealed that structural changes due to the splitting of G4-forming sequences correlate with their ability to form phase-separated condensates, which enhance their fluorogenic and DNAzyme activity. The machine learning-based activity screening was used to identify split G-quadruplexes, which may have high, moderate, or low functional activity. This integrative approach provides a predictive framework for engineering functionally active split G-quadruplexes and establishes a platform for their application in molecular diagnostics.分裂型G-四链体（Split G-quadruplexes）被视为生物传感与诊断领域的优异工具，但对G-四链体进行拆分往往会引发功能丧失，限制了其应用效能。本研究旨在基于G-四链体基序（G-quadruplex motif）产生荧光开启响应（fluorescence turn-on response）并发生相分离（phase separation）的能力，对具备功能活性的分裂型G-四链体开展鉴定与分类工作。 本研究设计了一系列分裂型G-四链体，并通过荧光光谱法（fluorescence spectroscopy）、荧光显微镜术（fluorescence microscopy）、紫外-可见光谱法（UV–vis spectroscopy）以及圆二色谱法（circular dichroism）对其进行表征，以探究其功能特性，包括荧光响应、相分离能力与脱氧核酶活性（DNAzyme activity）。 多变量分析（Multivariate analysis）与基于机器学习的模式识别（machine learning-based pattern recognition）结果显示，G4形成序列拆分所诱导的结构变化，与其形成相分离凝聚体（phase-separated condensates）的能力显著相关，而此类凝聚体可增强其荧光响应与脱氧核酶活性。 本研究采用基于机器学习的活性筛选策略，以鉴定具备高、中、低不同功能活性的分裂型G-四链体。该整合性研究方法（integrative approach）为构建具有功能活性的分裂型G-四链体提供了预测框架（predictive framework），并为其在分子诊断（molecular diagnostics）领域的应用搭建了研究平台。