An Updated Evolutionary and Structural Study of TBK1 Reveals Highly Conserved Motifs as Potential Pharmacological Targets in Neurodegenerative Diseases

Papageorgiou, Louis; Mangana, Eleni; Papakonstantinou, Eleni; Diakou, Io; Pierouli, Katerina; Dragoumani, Konstantina; Bacopoulou, Flora; Chrousos, George P.; Exarchos, Themis P.; Vlamos, Panagiotis; Eliopoulos, Elias; Vlachakis, Dimitrios

doi:10.1007/978-3-031-31978-5_5

Advances in Experimental Medicine and Biology

2023

DOI: 10.1007/978-3-031-31978-5_5

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An Updated Evolutionary and Structural Study of TBK1 Reveals Highly Conserved Motifs as Potential Pharmacological Targets in Neurodegenerative Diseases

Louis Papageorgiou,

Eleni Mangana,

Eleni Papakonstantinou

et al.

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In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery

Ivanov,

Tenchov,

Ralhan

et al. 2024

J. Chem. Inf. Model.

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TBK1, or TANK-binding kinase 1, is an enzyme that functions as a serine/threonine protein kinase. It plays a crucial role in various cellular processes, including the innate immune response to viruses, cell proliferation, apoptosis, autophagy, and antitumor immunity. Dysregulation of TBK1 activity can lead to autoimmune diseases, neurodegenerative disorders, and cancer. Due to its central role in these critical pathways, TBK1 is a significant focus of research for therapeutic drug development. In this paper, we explore data from the CAS Content Collection regarding TBK1 and its implication in a large assortment of diseases and disorders. With the demand for developing efficient TBK1 inhibitors being outlined, we focus on utilizing a machine learning approach for developing predictive models for TBK1 inhibition, derived from the fragment-functional analysis descriptors. Using the extensive CAS Content Collection, we assembled a training set of TBK1 inhibitors with experimentally measured IC50 values. We explored several machine learning techniques combined with various molecular descriptors to derive and select the best TBK1 inhibitor QSAR models. Certain significant structural alerts that potentially contribute to inhibition of TBK1 are outlined and discussed. The merit of the article stems from identifying the most adequate TBK1 QSAR models and subsequent successful development of advanced positive training data to facilitate and enhance drug discovery for an important therapeutic target such as TBK1 inhibitors, based on an extensive, wide-ranging set of scientific information provided by the CAS Content Collection.

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In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery

Ivanov,

Tenchov,

Ralhan

et al. 2024

J. Chem. Inf. Model.

View full text Add to dashboard Cite

show abstract

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An Updated Evolutionary and Structural Study of TBK1 Reveals Highly Conserved Motifs as Potential Pharmacological Targets in Neurodegenerative Diseases

Cited by 1 publication

References 49 publications

In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery

In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery

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