In this study, a molecular module assembly strategy was employed for the structural optimization of pynegabine (HN37), a clinical candidate targeting the potassium voltage-gated channel subfamily Q (KCNQ). First, an activity prediction model was established based on multi-conformation molecular docking and multiple linear regression. Simultaneously, a virtual compound library with high synthetic accessibility and structural novelty was constructed via modular assembly based on the Buchwald-Hartwig reaction, utilizing diverse building blocks acquired through substructure searches. Subsequently, a hierarchical virtual screening workflow—combining drug-likeness evaluation and established activity prediction model—was applied to identify a set of prioritized structures. On this basis, 24 target compounds were synthesized and evaluated using whole-cell patch-clamp electrophysiology. Experimental results demonstrated that 6 compounds exhibited significant agonistic activity against the KCNQ2 channel at 100 nM, with the structure-activity relationships (SAR) preliminary elucidated. Among them, compounds 3 and 4 showed favorable KCNQ2 agonistic activity, subtype selectivity for KCNQ channels, and metabolic stability. By integrating module-assembly-based molecular design, hierarchical virtual screening, and experimental validation, this work identifies a series of promising KCNQ2 agonists and paves the way for subsequent optimization.
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