Exploring TANK-Binding Kinase 1 in Amyotrophic Lateral Sclerosis: From Structural Mechanisms to Machine Learning-Guided Therapeutics

探索肌萎缩侧索硬化症中的 TANK 结合激酶 1:从结构机制到机器学习指导的治疗

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Abstract

TANK-binding kinase 1 (TBK1) has emerged as one of the most compelling genetic contributors to amyotrophic lateral sclerosis (ALS), with heterozygous loss-of-function and pathogenic missense variants identified in patients across the ALS-frontotemporal dementia (FTD) spectrum. TBK1 participates in various core cellular processes associated with motor neuron vulnerability, including autophagy, mitophagy, and innate immune regulation, indicating that TBK1 is likely a key determinant of ALS pathogenesis. Structurally, TBK1 exhibits a trimodular organization comprising a kinase domain, a ubiquitin-like domain, and a scaffold/dimerization domain. Multiple experimentally resolved conformations and inhibitor-bound complexes provide a foundation for structure-guided therapeutic design. Here, we synthesize current genetic and mechanistic evidence linking TBK1 dysfunction to ALS, emphasizing its dual roles in autophagy and neuroinflammation. We also summarize advances in structure-based and AI-assisted drug discovery approaches targeting TBK1. Finally, we outline key translational challenges, including isoform selectivity, biomarker validation, and central nervous system (CNS) delivery, highlighting TBK1 as a promising yet complex therapeutic target in ALS. By integrating computational modeling, machine learning frameworks, and experimental pharmacology, future research may accelerate the translation of TBK1 modulators into clinically effective therapies.

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