Enzymatic Metabolic Switches of Astrocyte Response to Lipotoxicity as Potential Therapeutic Targets for Nervous System Diseases.

Astrocytes play a pivotal role in maintaining brain homeostasis. Recent research has highlighted the significance of palmitic acid (PA) in triggering pro-inflammatory pathways contributing to neurotoxicity. Furthermore, Genomic-scale metabolic models and control theory have revealed that metabolic switches (MSs) are metabolic pathway regulators by potentially exacerbating neurotoxicity, thereby offering promising therapeutic targets. Herein, we characterized these enzymatic MSs in silico as potential therapeutic targets, employing protein-protein and drug-protein interaction networks alongside structural characterization techniques. Our findings indicate that five MSs (P00558, P04406, Q08426, P09110, and O76062) were functionally linked to nervous system drug targets and may be indirectly regulated by specific neurological drugs, some of which exhibit polypharmacological potential (e.g., Trifluperidol, Trifluoperazine, Disulfiram, and Haloperidol). Furthermore, four MSs (P00558, P04406, Q08426, and P09110) feature ligand-binding or allosteric cavities with druggable potential. Our results advocate for a focused exploration of P00558 (phosphoglycerate kinase 1), P04406 (glyceraldehyde-3-phosphate dehydrogenase), Q08426 (peroxisomal bifunctional enzyme, enoyl-CoA hydratase, and 3-hydroxyacyl CoA dehydrogenase), P09110 (peroxisomal 3-ketoacyl-CoA thiolase), and O76062 (Delta(14)-sterol reductase) as promising targets for the development or repurposing of pharmacological compounds, which could have the potential to modulate lipotoxic-altered metabolic pathways, offering new avenues for the treatment of related human diseases such as neurological diseases.

Control Theory and Systems Biology: Potential Applications in Neurodegeneration and Search for Therapeutic Targets.

Control theory, a well-established discipline in engineering and mathematics, has found novel applications in systems biology. This interdisciplinary approach leverages the principles of feedback control and regulation to gain insights into the complex dynamics of cellular and molecular networks underlying chronic diseases, including neurodegeneration. By modeling and analyzing these intricate systems, control theory provides a framework to understand the pathophysiology and identify potential therapeutic targets. Therefore, this review examines the most widely used control methods in conjunction with genomic-scale metabolic models in the steady state of the multi-omics type. According to our research, this approach involves integrating experimental data, mathematical modeling, and computational analyses to simulate and control complex biological systems. In this review, we find that the most significant application of this methodology is associated with cancer, leaving a lack of knowledge in neurodegenerative models. However, this methodology, mainly associated with the Minimal Dominant Set (MDS), has provided a starting point for identifying therapeutic targets for drug development and personalized treatment strategies, paving the way for more effective therapies.

Advances in Astrocyte Computational Models: From Metabolic Reconstructions to Multi-omic Approaches.

The growing importance of astrocytes in the field of neuroscience has led to a greater number of computational models devoted to the study of astrocytic functions and their metabolic interactions with neurons. The modeling of these interactions demands a combined understanding of brain physiology and the development of computational frameworks based on genomic-scale reconstructions, system biology, and dynamic models. These computational approaches have helped to highlight the neuroprotective mechanisms triggered by astrocytes and other glial cells, both under normal conditions and during neurodegenerative processes. In the present review, we evaluate some of the most relevant models of astrocyte metabolism, including genome-scale reconstructions and astrocyte-neuron interactions developed in the last few years. Additionally, we discuss novel strategies from the multi-omics perspective and computational models of other glial cell types that will increase our knowledge in brain metabolism and its association with neurodegenerative diseases.

Indole-Containing Phytoalexin-Based Bioisosteres as Antifungals: In Vitro and In Silico Evaluation against Fusarium oxysporum.

There is a continuous search for more reliable and effective alternatives to control phytopathogens through different strategies. In this context, indole-containing phytoalexins are stimuli-induced compounds implicated in plant defense against plant pathogens. However, phytoalexins' efficacy have been limited by fungal detoxifying mechanisms, thus, the research on bioisosteres-based analogs can be a friendly alternative regarding the control of Fusarium phytopathogens, but there are currently few studies on it. Thus, as part of our research on antifungal agents, a set of 21 synthetic indole-containing phytoalexin analogs were evaluated as inhibitors against the phyopathogen Fusarium oxysporum. Results indicated that analogs of the N,N-dialkylthiourea, N,S-dialkyldithiocarbamate and substituted-1,3-thiazolidin-5-one groups exhibited the best docking scores and interaction profiles within the active site of Fusarium spp. enzymes. Vina scores exhibited correlation with experimental mycelial growth inhibition using supervised statistics, and this antifungal dataset correlated with molecular interaction fields after CoMFA. Compound 24 (tert-butyl (((3-oxo-1,3-diphenylpropyl)thio)carbonothioyl)-l-tryptophanate), a very active analog against F. oxysporum, exhibited the best interaction with lanosterol 14α-demethylase according to molecular docking, molecular dynamics and molecular mechanic/poisson-boltzmann surface area (MM/PBSA) binding energy performance. After data analyses, information on mycelial growth inhibitors, structural requirements and putative enzyme targets may be used in further antifungal development based on phytoalexin analogs for controlling phytopathogens.