Life 2025, 15(11), 1665; https://doi.org/10.3390/life15111665 (registering DOI) - 24 Oct 2025
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
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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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(This article belongs to the Special Issue Role of Machine and Deep Learning in Drug Screening)
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