Current Medicinal Chemistry - Volume 29, Issue 27, 2022

Background: GSK-3β activity has been strictly related to neuroinflammation and neurodegeneration. Alzheimer’s disease is the most studied neurodegenerative disease, but GSK-3β seems to be involved in almost all neurodegenerative diseases, including Parkinson’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, Huntington’s disease, and the autoimmune disease multiple sclerosis. Objective: This review aims to help researchers both working on this research topic or not to have a comprehensive overview of GSK-3β in the context of neuroinflammation and neurodegeneration. Methods: Literature has been searched using PubMed and SciFinder databases by inserting specific keywords. A total of more than 500 articles have been discussed. Results: First of all, the structure and regulation of the kinase were briefly discussed, and then, specific GSK-3β implications in neuroinflammation and neurodegenerative diseases were illustrated with the help of figures, to conclude with a comprehensive overview on the most important GSK-3β and multitarget inhibitors. The structure and IC50 values at the target kinase have been reported for all the discussed compounds. Conclusion: GSK-3β is involved in several signaling pathways in neurons, glial cells and immune cells. The fine regulation and interconnection of all these pathways are at the base of the rationale use of GSK-β inhibitors in neuroinflammation and neurodegeneration. Some compounds are now under clinical trials. Despite this, the compounds’ pharmacodynamic and ADME/Tox profiles were often not fully characterized which is deleterious in such a complex system.

Casein kinase 1 (CK1) belongs to the serine-threonine kinase family and is expressed in all eukaryotic organisms. At least six human isoforms of CK1 (termed α, γ1-3, δ and ) have been cloned and characterized. CK1δ isoform modulates several physiological processes, including DNA damage repair, circadian rhythm, cellular proliferation and apoptosis. Therefore, CK1δ dysfunction may trigger diverse pathologies, such as cancer, inflammation and central nervous system disorders. Overexpression and aberrant activity of CK1δ have been connected to hyperphosphorylation of key proteins implicated in the development of neurodegenerative disorders, such as Parkinson’s and Alzheimer’s diseases and Amyotrophic Lateral Sclerosis. Thus, CK1δ inhibitors have attracted attention as potential drugs for these pathologies and several compounds have been synthesized or isolated from natural sources to be evaluated for their CK1δ inhibitory activity. Here we report a comprehensive review on the development of CK1δ inhibitors, with a particular emphasis on structure-activity relationships and computational studies, which provide useful insight for the design of novel inhibitors.

Fyn kinase is a member of the Src non-receptor tyrosine kinase family. Fyn is involved in multiple signaling pathways extending from cell proliferation and differentiation to cell adhesion and cell motility, and it has been found to be overexpressed in various types of cancers. In the central nervous system, Fyn exerts several different functions such as axon–glial signal transduction, oligodendrocyte maturation, and myelination, and it is implicated in neuroinflammatory processes. Based on these premises, Fyn emerges as an attractive target in cancer and neurodegenerative disease therapy, particularly Alzheimer’s disease (AD), based on its activation by Aβ via cellular prion protein and its interaction with tau protein. However, Fyn is also a challenging target since the Fyn inhibitors discovered so far, due to the relevant homology of Fyn with other kinases, suffer from off-target effects. This review covers the efforts performed in the last decade to identify and optimize small molecules that effectively inhibit Fyn, both in enzymatic and in cell assays, including drug repositioning practices, as an opportunity for therapeutic intervention in neurodegeneration.

Increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier make it mandatory to finely tune the candidates’ physicochemical properties from the early stages of the discovery pipeline. The aim of this review is, therefore, to provide a general overview of neuroinflammation to the readers, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be discussed, highlighting their advantages and limitations. Finally, we report several case studies in which computational methods have been applied to drug discovery for neuroinflammation, focusing on the research conducted in the last decade.