A comprehensive DEGs analysis revealed a total of 19,036 genes exhibiting differential expression, of which a subset of 1913 genes demonstrated statistically significant expression levels (p < 0.05). Within this subset, 922 genes were down-regulated, while 991 were up-regulated. Further screening based on |log Fc|> 1 revealed 87 down-regulated genes and 205 up-regulated genes (Fig. 1). These genes (encompassing both upregulated and downregulated) were utilized to construct a GCL-associated neuronal protein network circuit identifying 53 interacting genes (p = 5.55e−15) corresponded to diverse neurophysiological processes, ascertained through scrutinizing their expression patterns, homology relationships, database annotations, and textual mining. Furthermore, the integrated score was obtained by correcting the probability associated with randomly observed interactions (Fig. 2), elucidating 5 pivotal genes in 4 interrelations that included c-Fos (FOS)- FosB (FOSB), c-Fos (FOS)- transcription factor c-Jun (JUN), FosB (FOSB)- JUN, and glial cell line-derived neurotrophic factor (GDNF)- glial cell line-derived neurotrophic factor receptor α (GFRA1).Figure 1Differential gene expression on induced pluripotent stem-cell-derived neural stem cells derived from Globoid cell leukodystrophy (GCL) patients using transcriptome profiling. (a) Volcano plot presenting differential expressed genes. A total of 87 genes were downregulated, 205 were upregulated and 1621 were non-significant. The absolute fold change criterion (|Fc|> 1) corresponds to a fold change greater than 2 or less than 0.5 on a linear scale. In log2 scale, this criterion translates to log2(Fold Change) greater than 1 or less than − 1 . The p-value threshold of 0.05, adjusted using the Benjamini & Hochberg method, ensures that the genes considered as differentially expressed meet the statistical significance required for multiple testing corrections. (b) GCL-associated neuronal protein network circuit of differentially expressed genes in the GCL with at least one interaction. The larger the node size, the more central the protein it represents.Figure 2Identification of physiologic-neurobiological process of differentially expressed genes. (a) Neurological processes involved in the brain development were significantly affected. 1 biological regulation, 2 system development, 3 cell differentiation, 4 nervous system development, 5 cell development, 6 neurogenesis, 7 neuron differentiation, 8 cell–cell signaling, 9 neuron development, 10 axon development, 11 axonogenesis, 12 nerve development, 13 neural crest cell differentiation. (b) Heat map presenting the protein node scores. ASPL average shortest path length, BC BetweennessCentrality, CC ClosenessCentrality, EC EdgeCount, ID Indegree, NC neighborhood connectivity, OD Outdegree, St stress, IC integrated centrality. (c) Heat map presenting the gene expression of differentially expressed genes based on fragments per kilobase of transcript per million mapped reads. Genes traced in the Search Tool for the Retrieval of Interacting Genes/Proteins with at least one interaction were evaluated.The GCL-associated DEGs network identifies potential druggable targetsIn our present investigation, we spotlight five potential targets (FOS, FOSB, GDNF, GFRA1, and JUN) for possible drug intervention against GCL by examining the network interactions of DEGs in GCL-associated protein network  at high confidence score (0.7)  with DEGs exhibiting statistical significance (p < 0.05) and a fold change (|Fc|> 1). In this network (Fig. 1b), our focus was directed towards protein nodes exhibiting at least one edge relation to calculate IC identifying the c-Jun protein (JUN node) which suggests its pivotal role in the GCL disease network. Furthermore, GFRA1, GDNF, FOS, and FOSB stand out as key nodes in the proteins interaction network ranking top five nodes (FOS, FOSB, GDNF, GFRA1, and JUN) due to their notably high interaction, and is presented by their substantial node sizes (Fig. 1b). Consequently, we highlight c-Jun (JUN) as a potential druggable target for GCL and screen potential small molecules for JUN, including other hub targets from the drug information related molecular atlas.The functional enrichment analysis revealed crucial biological processes to encompass nervous system development, axonogenesis, and signal transmission (Fig. 2a), all of which are directly affected by galactolipid accumulation-induced demyelination, axonal damage, neuronal death, and systemic toxic effects. Additionally, in the GCL-associated neuronal protein network, c-Jun (JUN) emerged as a central node and may exhibit hub role in signal transduction (Fig. 1b) and interestingly, all 5 genes (GFRA1, GDNF, FOS, FOSB, and JUN) were significantly down expressed in the GCL (Fig. 3, S1-S4). The pivotal role of GFRA1 in development and survival of nerve cells23, evidenced by its diminished expression in the GCL (Fig. S1) underscores its significance in neuronal function. So, it can be further assessed whether GFRA1 downregulation favors myelin maintenance, precipitating myelin loss and GCL onset highlighting the intricate interplay between GFRA1 signaling and myelin integrity. In this study, our assessment showed that GFRA1 also served as one of the central protein node in GCL-associated protein network, displaying a higher average shortest path length potentially influencing signal transmission to other proteins. Furthermore, the potential role of GFRA1-related growth factors has been investigated to maintain and promote nerve cell survival in myelin damage23. While preclinical studies on GDNF and associated factors promise for neurological disorder24, it is currently unclear how these factors affect GCL or how their regulators can be utilized against it. Furthermore, the FOS is a component of the AP-1 transcription factor complex contributing to several cellular functions, such as differentiation, growth, and responsiveness to varied stimuli, as well as gene control25, and was found to be down-expressed in GCL (Fig. S3). Similarly, FOSB is also involved in multiple cellular processes responsible for neuron growth, function, and plasticity26. As a transcription factor, FOSB exerts regulatory effects by selectively binding to DNA thereby modulating the transcriptional activity of target genes intricately linked with the complex process of neuronal development27. In GCL, its expression was observed to be significantly lower (p = 0.0002) (Fig. S4), and this manipulated expression may directly affect multiple cellular processes related to neuron growth and function. Furthermore, the c-Jun is critical for neuronal proliferation in the CNS and is decreased in the GCL. This significant decreased (p = 0.0004) expression of JUN (Fig. 3) could be a compensatory mechanism, as its overexpression may increase pro-inflammatory cytokines and chemokines production and trigger an immune response leading to demyelination28,29. Furthermore, c-Jun (JUN) is intricately integrated into the AP-1 complex under its active participation in GCL-associated neuronal protein network circuit with congaing for neuronal growth as functional enrichment analysis elucidated its involvement across broad neurofunctional process, encompassing response to lipids, transcriptional modulation, tissue morphogenesis, and oxidative stress mitigation. Noteworthy associations extend to nucleoplasmic dynamics, DNA binding affinities, integrated stress response pathways including regulatory functions in nuclear protein-containing complexes and chromosomal architecture. Furthermore, in the GCL pathogenesis, c-Jun emerges as a pivotal regulatory node, orchestrating neuroinflammatory cascades and neurodegenerative pathways in response to neurotoxic insult posed by psychosine accumulation. Its nuanced modulation of gene expression towards psychosine-induced stress underscores its potential as a key player warranting further exploration for therapeutic interventions in GCL (Fig. 4). Consequently, its aberrant upregulation has the potential to dysregulate critical signaling cascades indispensable for myelination, precipitate apoptosis in oligodendrocytes, and provoke oxidative stress, thereby directly compromising the integrity of myelin maintenance28,29.Figure 3Evaluation of interacting edges in Globoid cell leukodystrophy (GCL)-associated neuronal protein circuit. (a) Identification of central interacting nodes based on the combined score (CS). The combination score was based on phylogenetic co-occurrence (PCO), homology (HOMO), coexpression (COEXP), experimentally determined interaction (EDI), database annotated (DA), and automated text mining (ATM). (b) Fragments per kilobase of transcript per million mapped reads of JUN expression in induced pluripotent stem-cell-derived neural stem cells derived from GCL patients using transcriptome profiling. Data were analyzed using unpaired t-test with Welch’s correction assuming Gaussian distribution, *p = 0.0004 (c) JUN expression in each sample compared with control.Figure 4Assessment of Jun-associated proteins circuit. (a) Heat map presenting the edge (interaction) score for node(protein) pair. The edge score for each protein pair was based on phylogenetic co-occurrence (PCO), homology (HOMO), coexpression (COEXP), experimentally determined interaction (EDI), database annotated (DA), automated text mining (ATM), and combined score (CS). (b) Functional enrichment analysis of JUN-associated biological process (integrated stress response signaling, response to oxidative stress, tissue development, response to lipid), molecular function (transcription regulator activity, DNA binding, transcription coregulator binding), and cellular components (chromosome, nuclear protein-containing complex, nucleoplasm). (c) JUN was associated with 10 different genes. The red node is the query node (JUN) and the rest represent the interacting nodes. The surface dimer structure of JUN is presented.Insight into the JUN inhibitory activity by T-5224 as a therapeutic approach against GCLAssessment of fragments per kilobase of transcript per million mapped reads reveals suppressed JUN expression (p = 0.0004) in iPSC from GCL patients compared to normal (Fig. 3b) which could be one of the compensatory mechanisms against GCL. The aberrant activation of the c-Jun transcription factor has significant importance in GCL as it may parallel to disease progression with toxic lipids accumulation, thereby instigating cellular stress. This can initiate a complex series of interconnected processes including demyelination, neuroinflammation, and the demise of oligodendrocytes, thereby exacerbating the pathological conditions in the neural environment. Furthermore, it is noteworthy that the c-Jun transcription factor not only governs the gene expression linked to oxidative stress29, inflammation30, and apoptosis31 but also orchestrates these pivotal pathogenic mechanisms in GCL, thereby underscoring its multifaceted role in disease. Nevertheless, achieving a comprehensive understanding of the intricate mechanisms through which the c-Jun transcription factor contributes to GCL and identifying precise therapeutic interventions necessitate the undertaking additional investigative endeavors. Significantly, within the scope of this investigation, the JUN node emerged as the entity possessing the highest integrated central score (Fig. 1b) within the neuronal protein circuit associated with GCL, thereby indicating the potential efficacy of targeting the entirety of the pathogenic network inherent. Henceforth, our inquiry proceeded to put additional emphasis on the c-Jun (JUN) activity inhibition, although we listed distinct small molecules targeting GCL-related proteins (Table 1, Fig. 5), directing our interest towards a central protein node in the GCL-associated proteins , which profoundly influences the signals interplay among the network constituent proteins. Consequently, our scrutiny pinpointed c-Jun (JUN) as one of the pivotal hub nodes for neuronal demyelination synchronization with other proteins (Fig. 2b), thereby prompting subsequent comprehensive evaluations. Moreover, T-5224 exerts its inhibitory action on the JUN/AP-1 complex by targeting the c-Fos DNA-binding domain, thereby impeding the association of the AP-1 complex with DNA and disrupting the transcriptional activity of the JUN-FOS dimer without affecting other transcription factors, such as NF-Κβ32. However, to confirm T-5224 mediated c-Jun inhibition for potential therapeutic effects on GCL, experimental studies are needed to assess its efficacy in modulating c-Jun activity and subsequent downstream effects, with an expectation of preventing neuronal demyelination and reducing neuronal apoptosis, which may improve neuronal function and needs further investigation.
Table 1 Small molecules identified from molecular atlas of drugs as potential therapeutic moieties towards GCL.Figure 5Screening of small molecules for differentially expressed genes. (a) Targets were initially screened for a different class if successful, under trial, discontinued, or unclear activity in different conditions like cardiovascular, diabetes, cancer, etc. Targets were also screened for their drug availability. (b) 2D sketch of representative drugs availability from DrugMAP: molecular atlas and pharma-information of all drugs (http://drugmap.idrblab.net/) for different GCL-related targets.Structural insight into the T-5224 binding with Jun/CRE complexIn this study, we describe the T-5224 binding affinity with the Jun/CRE complex using molecular docking and assessing the complex for its stability using molecular dynamics simulation. Molecular docking is employed to assess the interaction between ligand(s) and protein(s) by predicting their binding modes which primarily emphasize on the binding energy estimation providing possible hydrophilic and hydrophobic interactions33. The interactions of T-5224 with the Jun/CRE complex involve DNA bases and amino acid residues that highlight the molecular intricacies of its binding (Fig. 6, Supplementary Movie 1). The DNA bases involved in these interactions include DG C:211, DA C:209, DC C:210, DC D:309, DC D:310, and DG D:308. Meanwhile, the Jun/CRE complex amino acid residues participating include Arg A:270, Lys B:271, and Leu B:274. T-5224 forming five hydrophilic interactions, specifically with Arg A:270 (4.0 Å), DG C:211 (5.46 Å), DA C:209 (6.43 Å), DC C:210 (6.08 Å), and DC D:309 (5.01 Å). These hydrophilic interactions suggest that T-5224 can establish bonds with both the DNA and protein elements of the complex in an aqueous environment, stabilizing its position. Additionally, nine hydrophobic interactions were also formed, which involve Arg A:270 (4.99 Å), Lys B:271 (6.92 Å), Leu B:274 (6.72 Å and 5.48 Å), Arg B:270 (5.11 Å, 5.59 Å, and 6.49 Å), DC D:310 (7.53 Å), and DG D:308 (4.42 Å). These hydrophobic interactions indicate regions where T-5224 interfaces with nonpolar parts of the Jun/CRE complex, further contributing to its binding affinity and specificity. Importantly T-5224-DNA interaction may also influence its structure and function by binding with DNA base pairs showing groove binding fitting into the grooves of the helix forming both hydrophilic and hydrophobic interactions which can affect replication and transcription affecting the Jun/CRE complex function. Together, these interactions underline the dual nature of T-5224’s binding mechanism, engaging both hydrophilic and hydrophobic elements to stabilize its association with the Jun/CRE complex, potentially affecting its biological activity and regulatory functions. Importantly, we also highlight all the binding energy (Fig. 6c) for all T-5224 docked poses which ranged from − 10.2 kcal/mol (pose 2) to − 9.4 kcal/mol (pose 9) including their hydrophilic and hydrophobic interactions (Fig. S6).Figure 6Illustration depicting the T-5224 docking with the Jun/CRE binding site. (a) Crystal Structure of the Jun/CRE Complex (PDB: IJNM). X-ray diffraction experimental data snapshot with 2.20 Å resolution, 0.286 free R-value, 0.228 work R-value, and 0.228 observed R-value. The surface region represents the Jun, and the cartoon with mesh represents the CRE. (b) Docked position of T-5224 with Jun/CRE Complex. The surface region represents the JUN and the mesh represents the CRE. (c) The binding energy of 9 different ligands poses with Jun/CRE Complex. Pose 1 was identified to have the lowest binding energy (− 11.6 kcal/mol) which was later subjected to molecular dynamics simulation. (d) Interaction of T-5224 pose 1 with Jun/CRE complex. Five hydrophilic interactions were observed between T-5224 and Jun/CRE Complex.RMSD is crucial in dynamics simulations as it measures the average distance between the atomic coordinates of a simulated structure and a reference structure, providing a quantitative assessment of structural accuracy and it serves as a key metric for evaluating the reliability of molecular dynamics simulations by indicating how well the simulated structure aligns with the expected conformation34. The all-atom explicit molecular dynamics simulation trajectory revealed stable dynamics during the 200 ns period (Fig. 7). The average RMSD difference of backbone atoms for Jun/CRE and in complex with T-5224 was observed to be ∼ 0.9 Ã… (Fig. 7a). Similarly, the average RMSD difference for Jun/CRE, both alone and in complex with T-5224 (Fig. 7b, Supplementary Movie 2), was observed to be ∼ 0.52 Ã…. The considerable disparity observed in the T-5224 bound complex stemmed from the alterations in Jun/CRE structural conformations occurring over the equilibration period, specifically characterized by the transformation of a helical structure into a loop within the Lys268 to Glu275 region and this may be attributed to the stable hydrogen bond formation with Arg270. Similarly, RMSF complements RMSD by highlighting the variability of atomic positions over time, offering insights into the flexibility and dynamic behavior of individual residues in a biomolecular system35. The structural conformational changes, therefore, were confirmed by observing the residual fluctuations, with the Jun/CRE and T-5224 complex exhibiting a larger fluctuation compared to the Jun/CRE apo form (Fig. 7c). The residues spanning from Lys268 to Glu275 displayed diminished fluctuations within the Jun/CRE apo form, yet manifested increased fluctuations, in the T-5224 bound complex, a consequence attributed to the helix-to-loop conversion. Furthermore, the solvent-accessible surface area (SASA) was analyzed to distinguish the protein solvent accessibility behavior. The Jun/CRE apo form area was stable throughout the simulation (~ 150 nm2) and the T-5224 bound complex showed a steady decrease in the surface area from ~ 270 nm2 to 220 nm2 during the 200 ns simulation (Fig. 7d). The radius of gyration in ligand–protein simulation is crucial as it assesses the compactness and structural stability of the complex, offering insights into the distribution of mass around the center and the overall conformational dynamics and flexibility of the ligand–protein interaction36. In the present study, analysis reveals that the JUN apo form exhibited consistent stability in its radius of gyration across 200 ns whereas the complexation of Jun/CRE with T-5224 demonstrated a gradual reduction in radius of gyration (Fig. 7e) indicating a sustained folding behavior throughout the simulation period. Moreover, T-5224 established a total of 8 hydrophilic bonds, 3 of which exhibited consistency across all simulation iterations (Fig. 7f), leading to the inference that the sustained formation of the stable complex primarily stemmed from enduring interactions of hydrophilic bonds.Figure 7Parameters describing Jun/CRE-T-5224 complex structural stabilities. (a) Backbone atoms RMSD for Jun/CRE apo (green), in complex with T-5224 (red), and ligand T-5224 (blue), (b) complex atoms RMSD for Jun/CRE apo (green) and in complex with T-5224 (red), (c) RMSF Jun/CRE C-alpha RMSF apo (green) and in complex with T-5224 (red), (d) Protein SASA for Jun/CRE apo (green) and in complex with T-5224 (red), (e) Protein radius of gyration for Jun/CRE apo (green) and in complex with T-5224 (red), (f) Number of hydrogen bond interactions formed between Jun/CRE and T-5224, (b) The first 50 eigenvectors were plotted versus eigenvalue for Jun/CRE apo (green) and T-5224 bound complex (red), (h) The collective motion of Jun/CRE apo (green) and in complex with T-5224 (red) using projections of molecular dynamics trajectories on two eigenvectors corresponding to the first two principal components.Likewise, PCA helps to identify the most significant motions and conformational changes in the ligand–protein complex and assess the dynamic interactions20,21. In the present study, the maximum collective motion of the complex was investigated using the first two principal components (PC1 and PC2) and captured by the first 50 eigenvectors. It was observed that the T-5224 – Jun/CRE complex exhibited higher conformational flexibility, i.e., − 6 nm to 6 nm (PC1) and − 5 nm to 5 nm (PC2), with a larger diversity of conformations (eigenvalue: 5.5 nm2) during the simulations (Fig. 7). However, the Jun/CRE apo form showed lower conformational flexibility, ranging from − 5 nm to 5 nm2 (PC1) and − 3 nm to 4 nm (PC2), with a smaller diversity of conformations (eigenvalue: 4 nm2) during simulation (Fig. 7). This evidence into complex evinces a superior degree of flexibility, manifesting through a spectrum of structural permutations that spans a broader landscape, juxtaposed with the Jun/CRE apo form comparatively subdued flexibility, marked by a discernibly diminished repertoire of sampled conformations. Furthermore, an analysis of the collective motion of the ligand-binding domains utilizing DCCM discerned that the amplitude of anti-correlation exhibited a notable elevation in the Jun/CRE apo form, whereas in the complex T-5224 – Jun/CRE, the degree of anti-correlation was considerably diminished (Fig. S5). Consequently, we posit that the T-5224 binding would incline towards facilitating the conformational transition, primarily spanning from Lys268 to Glu275, thereby fostering the stable complex formation through augmented non-bonded interactions.Furthermore, the molecular mechanics poisson-boltzmann surface area analysis identified the relative binding energy (− 448 ± 41.73 kJ/mol) of the T-5224 – Jun/CRE complex. Similarly, the estimated van der Waals, electrostatic, polar solvation, and SASA energies were -238.96 ± 22.81, − 444.39 ± 37.85, 258.28 ± 50.99, and − 23.69 ± 2.05 kJ/mol, respectively. These results demonstrate the stable T-5224-Jun/CRE-complex formation, as shown on different ligand-protein complexes in our previous study37. Importantly, the most energetically favorable structure (corresponding to global minima) of Jun/CRE apo and in complex with T-5224 (Fig. 6) was extracted from the free energy landscape. It was observed that the dynamics of the T-5224 binding was highly governed by the flexible dynamics of ligand-binding residues (Fig. 8). In the Jun/CRE apo form, the low energy conformation was discerned around 143 ns (coordinates near − 2.96 and 4.54) with a conspicuous absence of significant conformational alterations. Conversely, in the T-5224 bound form, the low energy conformation manifested around 112.11 ns (coordinates near − 25.63 and − 4.97) precipitating a substantial structural metamorphosis at the ligand-binding locale, concomitant with perceptible adjustments in the secondary structure, notably transitioning from helix to loop configuration.Figure 8Free energy landscape (a) Jun/CRE apo form and (b) Jun/CRE-T-5224 complex. The dark blue region represents the coordinate with the lowest energy state (visualized using Mathematica (https://www.wolfram.com/mathematica/) 13.2.1). The snapshot for the Jun/CRE apo form was presented around 143 ns and, in the complex, around 112.11 ns.Prospective of T-5224 mediated JUN inhibition against GCL using experimental evidenceAlthough our current investigation delineates c-Jun as a promising druggable target and proposes T-5224 as a plausible candidate against GCL, it is imperative to underscore the necessity of corroborating this conjecture through an experimental approach. This imperative arises from the fact that the present findings stem exclusively from computational models, which, despite their intricate nature, are predicated upon approximations and presumptions that may not comprehensively encapsulate the intricacies of biological systems. Experimental validation in the wet lab milieu furnishes empirical substantiation to either corroborate or rebut these models, thereby ensuring congruence between predictions and empirical reality. Consequently, it is imperative to ascertain the feasibility of T-5224-induced c-Jun inhibition in GCL treatment. Given the constraints of our study owing to limited resources, our delineation has been confined to spotlighting the potential of T-5224-mediated c-Jun inhibition in GCL treatment through a computational lens. Nonetheless, we endeavor to underscore the viability of this hypothesis by advocating for the integration of both in vitro and in vivo studies.The focal point of the cellular studies would entail an investigation into the effects of T-5224 on c-Jun inhibition within oligodendrocytes, Schwann cells, and assorted neuronal cell types (e.g. Neuro-2a (N2a) Cells, PC12, and SH-SY5Y), among others, with the overarching objective of elucidating the potential effect on cell viability, proliferation, myelination, and lysosomal function across these diverse cellular cohorts. It is imperative to ascertain the impact of T-5224 on Jun expression necessitating the assessment of T-5224’s influence on mRNA levels through varying concentrations over distinct temporal intervals, juxtaposed with untreated cells serving as experimental controls. If notable variation exists in mRNA levels, it would be prudent to validate Jun protein expression after T-5224 treatment. Given the specific focus of prior research on the attenuation of Jun activity by T-522432 rather than its impact on expression per se, it is plausible that there may be minimal discernible alteration in mRNA levels or expression patterns. Notably, an advantageous strategy could entail augmenting Jun expression and activity via transfection, subsequently mitigating the resultant effects through T-5224 treatment, with implications spanning cell viability, proliferation, apoptosis, as well as myelination, encompassing lysosomal function and psychosine quantification. Examination of cell lines could yield pivotal insights into the molecular and cellular ramifications of T-5224-induced Jun inhibition in the GCL, elucidating potential mechanistic pathways underlying the therapeutic efficacy of T-5224 in mitigating disease pathology. The attainment of favorable outcomes from these investigations (Fig. 9a), should they materialize, could warrant further exploration in animal models as presented.Figure 9Exploring T-5224 mediated c-Jun inhibition against Globoid cell leukodystrophy using experimental evidence. (a) The cellular studies can aim to investigate T-5224 effects on c-Jun activity and/or expression inhibition in various neuronal cells, focusing on cell viability, proliferation, myelination, and lysosomal function. The goal is to provide novel insights into T-5224 potential therapeutic mechanisms and justify further animal model studies. (b) The in vivo study may aim to evaluate T-5224 therapeutic potential in Twitcher mouse model with key goals to assess survival, and improvements in biochemical and histological markers. The study can use multiple doses of T-5224, assess motor functions, and analyze myelination, neuroinflammation, lysosomal function, and psychosine levels to determine treatment efficacy.If the aforementioned experiments prove successful, they could provide compelling grounds for progressing toward involving animal models (Fig. 9b). The principal objective of the in vivo investigation would be to evaluate the therapeutic efficacy of T-5224 in a murine model of GCL, aiming to ascertain its capacity to ameliorate motor function, prolong survival, and enhance various biochemical and histological indicators associated with the disease. The Twitcher mouse stands as a GCL model, distinguished by compromised GALC activity resulting psychosine accumulation. It would be crucial to select mice from early postnatal period (for example P10–P14) so that therapy can begin early in the course of the illness by dividing animals into different groups, including (a) Wild-type control group—non-Twitcher mice treated with the vehicle solution, (b) Vehicle group—Twitcher mice treated with the vehicle solution without T-5224, (c) Treatment group 1—Twitcher mice treated low dose of T-5224 and (d) Treatment group 2—Twitcher mice treated with high dose of T-5224. T-5224 can be administered p.o. as its oral administration has been shown to produce anti-arthritic activity in vivo38 (confirming the T-5224 blood brain barrier permeability is equally important) and assess the behavioral and motor functions periodically. In this study framework, use of rotarod and grip strength assessments emerges as a judicious strategy, given their capacity to comprehensively gauge motor coordination and balance, while concurrently quantifying forelimb and hindlimb strength. The administration of treatment protocols may persist until reaching either a predetermined experimental terminus or until the natural disease progression manifests. Decisions can be made from nuanced observations of behavioral adaptations, alongside vigilant monitoring to ascertain the threshold of mortality. Such observations not only serve to elucidate the progression of the ailment but also furnish invaluable data to construct Kaplan–Meier survival curves, facilitating comparative analyses of lifespan across distinct experimental cohorts. At the culmination of the investigative process, brain, spinal cord, and peripheral nerves dissection is imperative to conduct a thorough evaluation encompassing myelination using myelin basic protein staining, and neuroinflammation, discernible through markers like glial fibrillary acidic protein for astrocytes and ionized calcium-binding adaptor molecule 1 for microglia. Furthermore, an indispensable aspect pertains to assessing the lysosomal function that necessitates the scrutiny of β-galactosidase activity within the harvested tissue homogenates. Of equal significance is the meticulous quantification of psychosine and other pertinent metabolites present in tissue homogenates through suitable spectrometric methodologies, thereby augmenting comprehension regarding the impact of T-5224 intervention on GCL pathophysiology. The employment of suitable statistical analyses, including but not limited to Analysis of Variance and t-tests, is imperative to discern discernible trends and ascertain statistical significance in diverse experimental groups, while duly accounting for potential confounders through multiple comparison corrections. The culmination of this exhaustive animal model investigation (Fig. 9b) may hold promise in furnishing pivotal insights into both the therapeutic efficacy and mechanistic underpinnings of T-5224 as a prospective pharmacological intervention for GCL.
Exploring the globoid cell leukodystrophy protein network and therapeutic interventions
