Neurodegenerative disorders are spreading worldwide and are one of the greatest threats to public health. There is currently no adequate therapy for these disorders, and therefore there is an urgent need to accelerate the discovery and development of effective treatments. Although neurodegenerative disorders are broad ranging and highly complex, they may share overlapping mechanisms, and thus potentially manifest common targets for therapeutic interventions. Glycogen synthase kinase-3 (GSK-3) is now acknowledged to be a central player in regulating mood behavior, cognitive functions, and neuron viability. Indeed, many targets controlled by GSK-3 are critically involved in progressing neuron deterioration and disease pathogenesis. In this review, we focus on three pathways that represent prominent mechanisms linking GSK-3 with neurodegenerative disorders: cytoskeleton organization, the mammalian target of rapamycin (mTOR)/autophagy axis, and mitochondria. We also consider the challenges and opportunities in the development of GSK-3 inhibitors for treating neurodegeneration.

The serine/threonine kinase, GSK-3, is a promising drug discovery target for treating multiple pathological disorders. Most GSK-3 inhibitors that were developed function as ATP competitive inhibitors, with typical limitations in specificity, safety and drug-induced resistance. In contrast, substrate competitive inhibitors (SCIs), are considered highly selective, and more suitable for clinical practice. The development of SCIs has been largely neglected in the past because the ambiguous, undefined nature of the substrate-binding site makes them difficult to design. In this study, we used our previously described structural models of GSK-3 bound to SCI peptides, to design a pharmacophore model and to virtually screen the “drug-like” Zinc database (~6.3 million compounds). We identified leading hits that interact with critical binding elements in the GSK-3 substrate binding site and are chemically distinct from known GSK-3 inhibitors. Accordingly, novel GSK-3 SCI compounds were designed and synthesized with IC₅₀ values of~1–4 μM. Biological activity of the SCI compound was confirmed in cells and in primary neurons that showed increased β-catenin levels and reduced tau phosphorylation in response to compound treatment. We have generated a new type of small molecule GSK-3 inhibitors and propose to use this strategy to further develop SCIs for other protein kinases.

Over the last decade, there has been continuous progress in our understanding of the biology of the protein kinase GSK-3

Recent research in the field of bioinformatics and molecular biology has revealed the immense complexity and uniqueness of microbiomes, while also showcasing the impact of the symbiosis between a microbiome and its host or environment. A core property influencing this process is horizontal gene transfer between members of the bacterial community used to maintain genetic variation. The essential effect of this mechanism is the exposure of genetic information to a wide array of members of the community, creating an additional “layer” of information in the microbiome named the “plasmidome”. From an engineering perspective, introduction of genetic information to an environment must be facilitated into chosen species which will be able to carry out the desired effect instead of competing and inhibiting it. Moreover, this process of information transfer imposes concerns for the biosafety of genetic engineering of microbiomes as exposure of genetic information into unwanted hosts can have unprecedented ecological impacts. Current technologies are usually experimentally developed for a specific host/environment, and only deal with the transformation process itself at best, ignoring the impact of horizontal gene transfer and gene-microbiome interactions that occur over larger periods of time in uncontrolled environments. The goal of this research was to design new microbiome-specific versions of engineered genetic information, providing an additional layer of compatibility to existing engineering techniques. The engineering framework is entirely computational and is agnostic to the selected microbiome or gene by reducing the problem into the following set up: microbiome species can be defined as wanted or unwanted hosts of the modification. Then, every element related to gene expression (e.g., promoters, coding regions, etc.) and regulation is individually examined and engineered by novel algorithms to provide the defined expression preferences. Additionally, the synergistic effect of the combination of engineered gene blocks facilitates robustness to random mutations that might occur over time. This method has been validated using both computational and experimental tools, stemming from the research done in the iGEM 2021 competition, by the TAU group.