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Obesity and neurometabolic diseases have been linked to neurodegenerative diseases. Our hypothesis is that the endogenous estrogenic component of human astrocytes plays a critical role in cell response during lipotoxic damage, given that obesity can disrupt hormonal homeostasis and cause brain inflammation. Our findings showed that high concentrations of palmitic acid (PA) significantly reduced cell viability more in male astrocytes, indicating sex-specific vulnerabilities. PA induced a greater increase in cytosolic reactive oxygen species (ROS) production in males, while female astrocytes exhibited higher superoxide ion levels in mitochondria. In addition, female astrocytes treated with PA showed increased expression of antioxidant proteins, including catalase, Gpx-1 and Nrf2 suggesting a stronger cellular defence mechanism. Interestingly, there was a difference in the expression of estrogenic components, such as estrogen, androgens, and progesterone receptors, as well as aromatase and 5α-reductase enzymes, between males and females. PA induced their expression mainly in females, indicating a potential protective mechanism mediated by endogenous hormones. In summary, our findings highlight the impact of sex on the response of human astrocytes to lipotoxicity. Male astrocytes appear to be more susceptible to cellular damage when exposed to high concentrations of fatty acids.

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.

Neurodegenerative diseases (NDs) are characterized by a progressive deterioration of neuronal function, leading to motor and cognitive damage in patients. Astrocytes are essential for maintaining brain homeostasis, and their functional impairment is increasingly recognized as central to the etiology of various NDs. Such impairment can be induced by toxic insults with palmitic acid (PA), a common fatty acid, that disrupts autophagy, increases reactive oxygen species, and triggers inflammation. Although the effects of PA on astrocytes have been addressed, most aspects of the dynamics of this fatty acid remain unknown. Additionally, there is still no model that satisfactorily explains how astroglia goes from being neuroprotective to neurotoxic. Current incomplete knowledge needs to be improved by the growing field of non-coding RNAs (ncRNAs), which is proven to be related to NDs, where the complexity of the interactions among these molecules and how they control other RNA expressions need to be addressed. In the present study, we present an extensive competing endogenous RNA (ceRNA) network using transcriptomic data from normal human astrocyte (NHA) cells exposed to PA lipotoxic conditions and experimentally validated data on ncRNA interaction. The obtained network contains 7 lncRNA transcripts, 38 miRNAs, and 239 mRNAs that showed enrichment in ND-related processes, such as fatty acid metabolism and biosynthesis, FoxO and TGF-β signaling pathways, prion diseases, apoptosis, and immune-related pathways. In addition, the transcriptomic profile was used to propose 22 potential key controllers lncRNA/miRNA/mRNA axes in ND mechanisms. The relevance of five of these axes was corroborated by the miRNA expression data obtained in other studies. MEG3 (ENST00000398461)/hsa-let-7d-5p/ATF6B axis showed importance in Parkinson’s and late Alzheimer’s diseases, while AC092687.3/hsa-let-7e-5p/[SREBF2, FNIP1, PMAIP1] and SDCBP2-AS1 (ENST00000446423)/hsa-miR-101-3p/MAPK6 axes are probably related to Alzheimer’s disease development and pathology. The presented network and axes will help to understand the PA-induced mechanisms in astrocytes, leading to protection or injury in the CNS under lipotoxic conditions as part of the intricated cellular regulation influencing the pathology of different NDs. Furthermore, the five corroborated axes could be considered study targets for new pharmacologic treatments or as possible diagnostic molecules, contributing to improving the quality of life of millions worldwide.

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.

The coronavirus disease 2019 pandemic accelerated drug/vaccine development processes, integrating scientists all over the globe to create therapeutic alternatives against this virus. In this work, we have collected information regarding proteins from SARS-CoV-2 and humans and how these proteins interact. We have also collected information from public databases on protein–drug interactions. We represent this data as networks that allow us to gain insights into protein–protein interactions between both organisms. With the collected data, we have obtained statistical metrics of the networks. This data analysis has allowed us to find relevant information on which proteins and drugs are the most relevant from the network pharmacology perspective. This method not only allows us to focus on viral proteins as the main targets for COVID-19 but also reveals that some human proteins could be also important in drug repurposing campaigns. As a result of the analysis of the SARS-CoV-2–human interactome, we have identified some old drugs, such as disulfiram, auranofin, gefitinib, suloctidil, and bromhexine as potential therapies for the treatment of COVID-19 deciphering their potential complex mechanism of action.

Diagnosis of neurodegenerative disease (NDD) is complex, therefore simpler, less invasive, more accurate biomarkers are needed. small non-coding RNA (sncRNA) dysregulates in NDDs and sncRNA signatures have been explored for the diagnosis of NDDs, however, the performance of previous biomarkers is still better. Astrocyte dysfunction promotes neurodegeneration and thus derived scnRNA signatures could provide a more precise way to identify of changes related to NDD course and pathogenesis, and it could be useful for the dissection of mechanistic insights operating in NDD. Often sncRNA are transported outside the cell by the action of secreted particles such as extracellular vesicles (EV), which protect sncRNA from degradation. Furthermore, EV associated sncRNA can cross the BBB to be found in easier to obtain peripheral samples, EVs also inherit cell-specific surface markers that can be used for the identification of Astrocyte Derived Extracellular Vesicles (ADEVs) in a peripheral sample. By the study of the sncRNA transported in ADEVs it is possible to identify astrocyte specific sncRNA signatures that could show astrocyte dysfunction in a more simpler manner than previous methods. However, sncRNA signatures in ADEV are not a copy of intracellular transcriptome and methodological aspects such as the yield of sncRNA produced in ADEV or the variable amount of ADEV captured after separation protocols must be considered. Here we review the role as signaling molecules of ADEV derived sncRNA dysregulated in conditions associated with risk of neurodegeneration, providing an explanation of why to choose ADEV for the identification of astrocyte-specific transcriptome. Finally, we discuss possible limitations of this approach and the need to improve the detection limits of sncRNA for the use of ADEV derived sncRNA signatures.

The importance of miRNAs in cellular processes and their dysregulation has taken significant importance in understanding different pathologies. Due to the constant increase in the prevalence of neurodegenerative diseases (ND) worldwide and their economic impact, mild cognitive impairment (MCI), considered a prodromal phase, is a logical starting point to study this public health problem. Multiple studies have established the importance of miRNAs in MCI, including astrocyte regulation during stressful conditions. Additionally, the protection mechanisms exerted by astrocytes against some damage in the central nervous system (CNS) lead to astrocytic reactivation, in which a differential expression of miRNAs has been shown. Nevertheless, excessive reactivation can cause neurodegeneration, and a clear pattern defining the equilibrium point between a neuroprotective or detrimental astrocytic phenotype is unknown. Therefore, the miRNA expression has gained significant attention to understand the maintenance of brain balance and improve the diagnosis and treatment at earlier stages in the ND. Here, we provide a comprehensive review of the emerging role of miRNAs in cellular processes that contribute to the loss of cognitive function, including lipotoxicity, which can induce chronic inflammation, also considering the fundamental role of astrocytes in brain homeostasis.

Neurodegenerative diseases (NDD) have been of great interest to scientists for a long time due to their multifactorial character. Among these pathologies, Alzheimer’s disease (AD) is of special relevance, and despite the existence of approved drugs for its treatment, there is still no efficient pharmacological therapy to stop, slow, or repair neurodegeneration. Existing drugs have certain disadvantages, such as lack of efficacy and side effects. Therefore, there is a real need to discover new drugs that can deal with this problem. However, as AD is multifactorial in nature with so many physiological pathways involved, the most effective approach to modulate more than one of them in a relevant manner and without undesirable consequences is through polypharmacology. In this field, there has been significant progress in recent years in terms of pharmacoinformatics tools that allow the discovery of bioactive molecules with polypharmacological profiles without the need to spend a long time and excessive resources on complex experimental designs, making the drug design and development pipeline more efficient. In this review, we present from different perspectives how pharmacoinformatics tools can be useful when drug design programs are designed to tackle complex diseases such as AD, highlighting essential concepts, showing the relevance of artificial intelligence and new trends, as well as different databases and software with their main results, emphasizing the importance of coupling wet and dry approaches in drug design and development processes.

Metachromatic leukodystrophy (MLD) is a human neurodegenerative disorder characterized by progressive damage on the myelin band in the nervous system. MLD is caused by the impaired function of the lysosomal enzyme Arylsulphatase A (ARSA). The physiopathology mechanisms and the biochemical consequences in the brain of ARSA deficiency are not entirely understood. In recent years, the use of genome-scale metabolic (GEM) models has been explored as a tool for the study of the biochemical alterations in MLD. Previously, we modeled the metabolic consequences of different lysosomal storage diseases using single GEMs. In the case of MLD, using a glia GEM, we previously predicted that the metabolism of glycosphingolipids and neurotransmitters was altered. The results also suggested that mitochondrial metabolism and amino acid transport were the main reactions affected. In this study, we extended the modeling of the metabolic consequences of ARSA deficiency through the integration of neuron and glial cell metabolic models. Cell-specific models were generated from Recon2, and these were used to create a neuron-glial bi-cellular model. We propose a workflow for the integration of this type of model and its subsequent study. The results predicted the impairment pathways involved in the transport of amino acids, lipids metabolism, and catabolism of purines and pyrimidines. The use of this neuron-glial GEM metabolic reconstruction allowed to improve the prediction capacity of the metabolic consequences of ARSA deficiency, which might pave the way for the modeling of the biochemical alterations of other inborn errors of metabolism with central nervous system involvement.

The association between neurodegenerative diseases (NDs) and obesity has been well studied in recent years. Obesity is a syndrome of multifactorial etiology characterized by an excessive accumulation and release of fatty acids (FA) in adipose and non-adipose tissue. An excess of FA generates a metabolic condition known as lipotoxicity, which triggers pathological cellular and molecular responses, causing dysregulation of homeostasis and a decrease in cell viability. This condition is a hallmark of NDs, and astrocytes are particularly sensitive to it, given their crucial role in energy production and oxidative stress management in the brain. However, analyzing cellular mechanisms associated with these conditions represents a challenge. In this regard, metabolomics is an approach that allows biochemical analysis from the comprehensive perspective of cell physiology. This technique allows cellular metabolic profiles to be determined in different biological contexts, such as those of NDs and specific metabolic insults, including lipotoxicity. Since data provided by metabolomics can be complex and difficult to interpret, alternative data analysis techniques such as machine learning (ML) have grown exponentially in areas related to omics data. Here, we developed an ML model yielding a 93% area under the receiving operating characteristic (ROC) curve, with sensibility and specificity values of 80% and 93%, respectively. This study aimed to analyze the metabolomic profiles of human astrocytes under lipotoxic conditions to provide powerful insights, such as potential biomarkers for scenarios of lipotoxicity induced by palmitic acid (PA). In this work, we propose that dysregulation in seleno-amino acid metabolism, urea cycle, and glutamate metabolism pathways are major triggers in astrocyte lipotoxic scenarios, while increased metabolites such as alanine, adenosine, and glutamate are suggested as potential biomarkers, which, to our knowledge, have not been identified in human astrocytes and are proposed as candidates for further research and validation.

Excessive accumulation and release of fatty acids (FAs) in adipose and non-adipose tissue are characteristic of obesity and are associated with the leading causes of death worldwide. Chronic exposure to high concentrations of FAs such as palmitic acid (pal) is a risk factor for developing different neurodegenerative diseases (NDs) through several mechanisms. In the brain, astrocytic dysregulation plays an essential role in detrimental processes like metabolic inflammatory state, oxidative stress, endoplasmic reticulum stress, and autophagy impairment. Evidence shows that tibolone, a synthetic steroid, induces neuroprotective effects, but its molecular mechanisms upon exposure to pal remain largely unknown. Due to the capacity of identifying changes in the whole data-set of proteins and their interaction allowing a deeper understanding, we used a proteomic approach on normal human astrocytes under supraphysiological levels of pal as a model to induce cytotoxicity, finding changes of expression in proteins related to translation, transport, autophagy, and apoptosis. Additionally, tibolone pre-treatment showed protective effects by restoring those same pal-altered processes and increasing the expression of proteins from cell survival processes. Interestingly, ARF3 and IPO7 were identified as relevant proteins, presenting a high weight in the protein-protein interaction network and significant differences in expression levels. These proteins are related to transport and translation processes, and their expression was restored by tibolone. This work suggests that the damage caused by pal in astrocytes simultaneously involves different mechanisms that the tibolone can partially revert, making tibolone interesting for further research to understand how to modulate these damages.

One of the most common lipids in the human body is palmitic acid (PA), a saturated fatty acid with essential functions in brain cells. PA is used by cells as an energy source, besides being a precursor of signaling molecules and protein tilting across the membrane. Although PA plays physiological functions in the brain, its excessive accumulation leads to detrimental effects on brain cells, causing lipotoxicity. This mechanism involves the activation of toll-like receptors (TLR) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways, with the consequent release of pro-inflammatory cytokines, increased production of reactive oxygen species (ROS), endoplasmic reticulum (ER) stress, and autophagy impairment. Importantly, some of the cellular changes induced by PA lead to an augmented susceptibility to the development of Alzheimer’s and Parkinson´s diseases. Considering the complexity of the response to PA and the intrinsic differences of the brain, in this review, we provide an overview of the molecular and cellular effects of PA on different brain cells and their possible relationships with neurodegenerative diseases (NDs). Furthermore, we propose the use of other fatty acids, such as oleic acid or linoleic acid, as potential therapeutic approaches against NDs, as these fatty acids can counteract PA’s negative effects on cells.

Lipotoxicity is a metabolic condition resulting from the accumulation of free fatty acids in non-adipose tissues which involves a series of pathological responses triggered after chronic exposure to high levels of fatty acids, severely detrimental to cellular homeostasis and viability. In brain, lipotoxicity affects both neurons and other cell types, notably astrocytes, leading to neurodegenerative processes, such as Alzheimer (AD) and Parkinson diseases (PD). In this study, we performed for the first time, a whole lipidomic characterization of Normal Human Astrocytes cultures exposed to toxic concentrations of palmitic acid and the protective compound tibolone, to establish and identify the set of potential metabolites that are modulated under these experimental treatments. The study covered 3843 features involved in the exo- and endo-metabolome extracts obtained from astrocytes with the mentioned treatments. Through multivariate statistical analysis such as PCA (principal component analysis), partial least squares (PLS-DA), clustering analysis, and machine learning enrichment analysis, it was possible to determine the specific metabolites that were affected by palmitic acid insult, such as phosphoethanolamines, phosphoserines phosphocholines and glycerophosphocholines, with their respective metabolic pathways impact. Moreover, our results suggest the importance of tibolone in the generation of neuroprotective metabolites by astrocytes and may be relevant to the development of neurodegenerative processes.

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.

Inflammation is a complex biological response to injuries, metabolic disorders or infections. In the brain, astrocytes play an important role in the inflammatory processes during neurodegenerative diseases. Recent studies have shown that the increase of free saturated fatty acids such as palmitic acid produces a metabolic inflammatory response in astrocytes generally associated with damaging mechanisms such as oxidative stress, endoplasmic reticulum stress, and autophagic defects. In this aspect, the synthetic neurosteroid tibolone has shown to exert protective functions against inflammation in neuronal experimental models without the tumorigenic effects exerted by sexual hormones such as estradiol and progesterone. However, there is little information regarding the specific mechanisms of tibolone in astrocytes during inflammatory insults. In the present study, we performed a genome-scale metabolic reconstruction of astrocytes that was used to study astrocytic response during an inflammatory insult by palmitate through Flux Balance Analysis methods and data mining. In this aspect, we assessed the metabolic fluxes of human astrocytes under three different scenarios: healthy (normal conditions), induced inflammation by palmitate, and tibolone treatment under palmitate inflammation. Our results suggest that tibolone reduces the L-glutamate-mediated neurotoxicity in astrocytes through the modulation of several metabolic pathways involved in glutamate uptake. We also identified a set of reactions associated with the protective effects of tibolone, including the upregulation of taurine metabolism, gluconeogenesis, cPPAR and the modulation of calcium signaling pathways. In conclusion, the different scenarios studied in our model allowed us to identify several metabolic fluxes perturbed under an inflammatory response and the protective mechanisms exerted by tibolone.

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and discrimination of each neurodegenerative disorder a priority. Several investigations have revealed the importance of microRNAs and long non-coding RNAs in neurodevelopment, brain function, maturation, and neuronal activity, as well as its dysregulation involved in many types of neurological diseases. Therefore, the expression pattern of these molecules in the different NDs have gained significant attention to improve the diagnostic and treatment at earlier stages. In this sense, we gather the different microRNAs and long non-coding RNAs that have been reported as dysregulated in each disorder. Since there are a vast number of non-coding RNAs altered in NDs, some sort of synthesis, filtering and organization method should be applied to extract the most relevant information. Hence, machine learning is considered as an important tool for this purpose since it can classify expression profiles of non-coding RNAs between healthy and sick people. Therefore, we deepen in this branch of computer science, its different methods, and its meaningful application in the diagnosis of NDs from the dysregulated non-coding RNAs. In addition, we demonstrate the relevance of machine learning in NDs from the description of different investigations that showed an accuracy between 85% to 95% in the detection of the disease with this tool. All of these denote that artificial intelligence could be an excellent alternative to help the clinical diagnosis and facilitate the identification diseases in early stages based on non-coding RNAs.

The envelope glycoprotein 51 (gp51) is essential for bovine leukaemia virus (BLV) entry to bovine B-lymphocytes. Although the bovine adaptor protein 3 complex subunit delta-1 (boAP3D1) has been proposed as the potential receptor, the specific ligand-receptor interaction has not yet been completely defined and boAP3D1 receptor and gp51 3D structures have not been determined. This study was thus aimed at a functional annotation of boAP3D1 cellular adaptor protein and BLV gp51 and, proposing a reliable model for gp51-AP3D1 interaction using bioinformatics tools. The boAP3D1 receptor interaction patterns were calculated based on models of boAP3D1 receptor and gp51 complexes' 3D structures, which were constructed using homology techniques and data-driven docking strategy. The results showed that the participation of 6 key amino acids (aa) on gp51 (Asn170, Trp127, His115, Ala97, Ser98 and Glu128) and 4 aa on AP3D1 (Lys925, Asp807, Asp695 and Arg800) was highly probable in the interaction between gp51 and BLVR domains. Three gp51 recombinant peptides were expressed and purified to validate these results: the complete domain (rgp51), the N-terminal portion (rNgp51) and the C-terminal fragment (rCgp51); and binding assays to Madin-Darby bovine kidney (MDBK) cells were then carried out with each recombinant. It was found that rNgp51 preferentially bound to MDBK cells, suggesting this domain's functional role during invasion. The rNgp51-MDBK cell interaction was sensitive to trypsin (98% reduction) and chymotrypsin treatment (80% reduction). These results highlighted that the N-terminal portion of gp51 interacted in vitro with the AP3D1 receptor and provides a plausible in silico interaction model.

Abstract Background Replication factor A (RPA) is a single-strand DNA binding protein involved in DNA replication, recombination and repair processes. It is composed by the subunits RPA-1, RPA-2 and RPA-3; the major DNA-binding activity resides in the subunit 1 of the heterotrimeric RPA complex. In yeast and higher eukaryotes, besides the three basic structural DNA-binding domains, the RPA-1 subunit contains an N-terminal region involved in protein-protein interactions with a fourth DNA-binding domain. Remarkably, the N-terminal extension is absent in the RPA-1 of the pathogenic protozoan Leishmania (Leishmania) amazonensis; however, the protein maintains its ability to bind ssDNA. In a recent work, we identify Leishmania (Viannia) braziliensis RPA-1 by its specific binding to the untranslated regions of the HSP70 mRNAs, suggesting that this protein might be also an RNA-binding protein. Methods Both rLbRPA-1 purified by His-tag affinity chromatography as well as the in vitro transcribed L. braziliensis 3′ HSP70-II UTR were used to perform pull down assays to asses nucleic acid binding properties. Also, homology modeling was carried out to construct the LbRPA-1 tridimensional structure to search relevant amino acid residues to bind nucleic acids. Results In this work, after obtaining the recombinant L. braziliensis RPA-1 protein under native conditions, competitive and non-competitive pull-down assays confirmed the single-stranded DNA binding activity of this protein and demonstrated its interaction with the 3′ UTR from the HSP70-II mRNA. As expected, this protein exhibits a high affinity for ssDNA, but we have found that RPA-1 interacts also with RNA. Additionally, we carried out a structural analysis of L. braziliensis RPA-1 protein using the X-ray diffraction structure of Ustilago maydis homologous protein as a template. Our results indicate that, in spite of the evolutionary divergence between both organisms, the structure of these two RPA-1 proteins seems to be highly conserved. Conclusion The LbRPA-1 protein is a ssDNA binding protein, but also it shows affinity in vitro for the HSP70 mRNA; this finding supports a possible in vivo role in the HSP70 mRNA metabolism. On the other hand, the three dimensional model of Leishmania RPA-1 serves as a starting point for both functional analysis and its exploration as a chemotherapeutic target to combat leishmaniasis.

Protein LIC10494 of Leptospira interrogans serovar Copenhageni: structural model and associated functional regions. Objective.Predict by computational means the 3D structure of the antigenic protein LIC10494 and report associated important functional regionsfor its pathogenicity and immunogenicity. Materials and methods. We performed a computational analysis of the primary structure ofLIC10494 using the servers BLAST, PROTPARAM, PROTSCALE, DAS, SOSUI, TOPPRED, TMAP, TMpred, SPLIT4, PHDHTM,TMHMM2, HMMTOP2, GLOBPLOT and PROSITE. The secondary structure was obtained by consensus of the algorithms SOPM,PREDATOR GOR4, DPM and DSC. The approach to the tertiary structure was obtained using the algorithm MUSTER. The energyminimization was done using the AMBER94 force field of the Schrodinger suite of molecular analysis, and the stereochemistry andenergy model validation was performed by the RAMPAGE server. The final model was visualized using PyMol V.0,98. Results. Thisstudy proposes a computational model that describes the 3D structure of the hypothetical lipoprotein LIC10494 and agrees with previousexperimental reports; thus, our study demonstrates the existence of patterns that could play an important role in the pathogenicity andprotection of the bacteria against the host immune system; the presence of a disorganized region between amino acids 80 and 140, andof a transmembrane segment between amino acids 8 and 22. Conclusion. The coincidence between structural and functional segments suggests that our model can be used to predict certain aspects of the biological behaviour of the protein according to the pathogenic andimmunogenic characteristics of the bacteria.

Parkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with the major symptoms comprising loss of movement coordination (motor dysfunction) and non-motor dysfunction, including gastrointestinal symptoms. Alterations in the gut microbiota composition have been reported in PD patients vs. controls. However, it is still unclear how these compositional changes contribute to disease etiology and progression. Furthermore, most of the available studies have focused on European, Asian, and North American cohorts, but the microbiomes of PD patients in Latin America have not been characterized. To address this problem, we obtained fecal samples from Colombian participants (n = 25 controls, n = 25 PD idiopathic cases) to characterize the taxonomical community changes during disease via 16S rRNA gene sequencing. An analysis of differential composition, diversity, and personalized computational modeling was carried out, given the fecal bacterial composition and diet of each participant. We found three metabolites that differed in dietary habits between PD patients and controls: carbohydrates, trans fatty acids, and potassium. We identified six genera that changed significantly in their relative abundance between PD patients and controls, belonging to the families Lachnospiraceae, Lactobacillaceae, Verrucomicrobioaceae, Peptostreptococcaceae, and Streptococcaceae. Furthermore, personalized metabolic modeling of the gut microbiome revealed changes in the predicted production of seven metabolites (Indole, tryptophan, fructose, phenylacetic acid, myristic acid, 3-Methyl-2-oxovaleric acid, and N-Acetylneuraminic acid). These metabolites are associated with the metabolism of aromatic amino acids and their consumption in the diet. Therefore, this research suggests that each individual’s diet and intestinal composition could affect host metabolism. Furthermore, these findings open the door to the study of microbiome–host interactions and allow us to contribute to personalized medicine.

Traumatic brain injury (TBI) is a pathology of great social impact, affecting millions of people worldwide. Despite the scientific advances to improve the management of TBI in recent years, we still do not have a specific treatment that controls the inflammatory process after mechanical trauma. The discovery and implementation of new treatments is a long and expensive process, making the repurpose of approved drugs for other pathologies a clinical interest. Tibolone is a drug in use for the treatment of symptoms associated with menopause and has been shown to have a broad spectrum of actions by regulating estrogen, androgen and progesterone receptors, whose activation exerts potent anti-inflammatory and antioxidant effects. In the present study, we aimed to investigate the therapeutic potential of the tibolone metabolites 3α-Hydroxytibolone, 3β-Hydroxytibolone, and Δ4-Tibolone as a possible therapy in TBI using network pharmacology and network topology analysis. Our results demonstrate that the estrogenic component mediated by the α and β metabolites can regulate synaptic transmission and cell metabolism, while the Δ metabolite may be involved in modulating the post-TBI inflammatory process. We identified several molecular targets, including KDR, ESR2, AR, NR3C1, PPARD, and PPARA, which are known to play critical roles in the pathogenesis of TBI. Tibolone metabolites were predicted to regulate the expression of key genes involved in oxidative stress, inflammation, and apoptosis. Overall, the repurposing of tibolone as a neuroprotective treatment for TBI holds promise for future clinical trials. However, further studies are needed to confirm its efficacy and safety in TBI patients.

Abstract Background Bovine herpes virus (BoHV 1 and BoHV-5) are the causative agents of infectious bovine rhinotracheitis (IBR). IBR is responsible for important economic losses in the cattle industry. The envelope glycoprotein B (gB) is essential for BoHV infection of cattle's upper respiratory and genital tract. gB is one of the main candidate antigens for a potential recombinant vaccine since it induces a strong and persistent immune response. Results In this study, gB of BoHV-1 and BoHV-5 was characterized in terms of function, structure, and antigenicity through bioinformatics tools. gB showed conserved sequence and structure, so, both domains named PH Like 1 and 2 domains of each virus were selected for the design of a bivalent vaccine candidate. The immunoinformatic study showed that these two domains have epitopes recognizable by B and T lymphocytes, followed by this, the cDNA domains from BoHV-1/5 gB (Domains-gB) were transformed into the yeast Komagataella phaffii GS115 (previously known as Pichia pastoris). A recombinant protein with molecular weight of about 110 kDa was obtained from the culture media. The vaccine candidate protein (Domains-gB) was recognized by a monoclonal antibody from a commercial ELISA kit used for IBR diagnostic, which may suggest that the epitopes are conserved of the entire infectious virus. Conclusion Overall, it was shown that the recombinant domains of BoHV-1/5 gB have antigenic and immunogenic properties similar to the native gB. This vaccine candidate is promising to be used in future studies to assess its immunogenicity in an animal model.

Mucopolysaccharidosis type I (MPSI) is a rare autosomal recessive disorder caused by mutations in the gene encoding the lysosomal enzyme α-l-iduronidase (IDUA), which is instrumental in the hydrolysis of the glycosaminoglycans, dermatan and heparan sulfate. The accumulation of unhydrolyzed glycosaminoglycans leads to pathogenesis in multiple tissue types, especially those of skeletal, nervous, respiratory, cardiovascular, and gastrointestinal origin. Although molecular diagnostic tools for MPSI have been available since the identification and characterization of the IDUA gene in 1992, Colombia, Ecuador, and Peru have lacked such methodologies. Therefore, the mutational profile of the IDUA gene in these countries has largely been unknown. The goal of this study was to characterize genotypes in 14 patients with MPSI from Colombia, Ecuador, and Peru. The most common mutation found at a frequency of 42.8% was W402X. Six patients presented with seven novel mutations, a high novel mutational rate in this population (32%). These novel mutations were validated using bioinformatic techniques. A model of the IDUA protein resulting from three of the novel missense mutations (Y625C, P385L, R621L) revealed that these mutations alter accessible surface area values, thereby reducing the accessibility of the enzyme to its substrates. This is the first characterization of the mutational profile of the IDUA gene in patients with MPSI in Colombia, Ecuador, and Peru. The findings contribute to our understanding of IDUA gene expression and IDUA enzyme function, and may help facilitate early and improved diagnosis and management for patients with MPSI.