Ligand and structure-based virtual screening approaches in drug discovery: minireview.

The compilation of ligand and structure-based molecular modeling methods has become an important practice in virtual screening applied to drug discovery. This systematic review addresses and ranks various virtual screening strategies to drive the selection of the optimal method for studies that have as their starting point a multi-ligand investigation and investigation based on the protein structure of a therapeutic target. This study shows examples of applications and an evaluation based on the objective and problematic of a series of virtual screening studies present in the ScienceDirect® database. The results showed that the molecular docking technique is widely used in scientific production, indicating that approaches that use protein structure as a starting point are the most promising strategy for drug discovery that relies on virtual screening-based research.

Review and Current Perspectives on DNA Topoisomerase I and II Enzymes of Fungi as Study Models for the Development of New Antifungal Drugs.

Fungal infections represent a growing public health problem, mainly stemming from two phenomena. Firstly, certain diseases (e.g., AIDS and COVID-19) have emerged that weaken the immune system, leaving patients susceptible to opportunistic pathogens. Secondly, an increasing number of pathogenic fungi are developing multi-drug resistance. Consequently, there is a need for new antifungal drugs with novel therapeutic targets, such as type I and II DNA topoisomerase enzymes of fungal organisms. This contribution summarizes the available information in the literature on the biology, topology, structural characteristics, and genes of topoisomerase (Topo) I and II enzymes in humans, two other mammals, and 29 fungi (including Basidiomycetes and Ascomycetes). The evidence of these enzymes as alternative targets for antifungal therapy is presented, as is a broad spectrum of Topo I and II inhibitors. Research has revealed the genes responsible for encoding the Topo I and II enzymes of fungal organisms and the amino acid residues and nucleotide residues at the active sites of the enzymes that are involved in the binding mode of topoisomerase inhibitors. Such residues are highly conserved. According to molecular docking studies, antifungal Topo I and II inhibitors have good affinity for the active site of the respective enzymes. The evidence presented in the current review supports the proposal of the suitability of Topo I and II enzymes as molecular targets for new antifungal drugs, which may be used in the future in combined therapies for the treatment of infections caused by fungal organisms.

TYRO3 and EPHA2 Expression Are Dysregulated in Breast Cancer.

Receptor tyrosine kinases (RTKs) are involved in cell growth, motility, and differentiation. Deregulation of RTKs signaling is associated with tumor development and therapy resistance. Potential RTKs like TAM (TYRO3, AXL, MERTK), RON, EPH, and MET have been evaluated in many cancers like lung, prostate, and colorectal, but little is known in breast tumors. In this study, 51 luminal breast cancer tissue and 8 triple negative breast cancer (TNBC) subtypes were evaluated by qPCR for the expression of TAM, RON, EPHA2, and MET genes. Statistical analysis was performed to determine the correlation to clinical data. TYRO3 is related to tumor subtype and stage, patient's age, smoking habits, and obesity. MET expression is correlated to EPHA2 and TAM gene expression. EPHA2 expression is also related to aging and smoking habits. The expression levels of the TAM and EPHA2 genes seem to play an important role in breast cancer, being also influenced by the patient's lifestyle.

Tackling Neuroinflammation in Cognitive Disorders with Single-Targeted and Multi-Targeted Histamine H3 Receptor Modulators.

Neuroinflammation is a process involved in a variety of central nervous system (CNS) diseases and is being increasingly recognized as a key mediator of cognitive impairments. Neuroinflammatory responses including glial activation, increased production of proinflammatory cytokines, and aberrant neuronal signaling, contribute to cognitive dysfunctions. Histamine is a key peripheral inflammatory mediator, but plays an important role in neuroinflammatory processes as well. The unique localization of histamine H3 receptor (H3R) in the CNS along with the modulation of the release of other neurotransmitters via its action on heteroreceptors on non-histaminergic neurons have led to the development of several H3R ligands for various brain diseases. H3R antagonists/ inverse agonists have revealed potential to treat diverse neuroinflammatory CNS disorders, including neurodegenerative diseases, attention-deficit hyperactivity syndrome and schizophrenia. In this mini review, we provide a brief overview on the crucial involvement of the histaminergic transmission in the neuroinflammatory processes underlying these cognitive disorders, with a special focus on H3R involvement. The anti-neuroinflammatory potential of single-targeted and multi-targeted H3R antagonists/inverse agonists for the treatment of these conditions is discussed here.

Challenges in implementing treat-to-target in rheumatoid arthritis: a perspective from Brazilian rheumatologists.

BACKGROUND: Patient management in rheumatoid arthritis (RA) has evolved to a "treat-to-target" (T2T) approach, which entails intensive treatment and regular follow-up with the goal of achieving low levels of disease activity or clinical remission. Even though a T2T approach is endorsed by professional organizations and yields superior outcomes, its implementation remains incomplete. EVEREST (EleVatE care in RhEumatoid arthritiS with Treat-to-target) is a quality-improvement initiative designed to improve the widespread implementation of a personalized T2T strategy and enable patients with RA to reach their full potential for remission. We describe the Brazilian results from the Global T2T Survey, first part of the EVEREST program. METHODS: Between June and September 2022, we conducted an online survey targeting rheumatologists in Brazil. Our objective was to evaluate the barriers and knowledge gaps hindering the effective implementation of T2T strategies. To achieve this, we employed a set of multiple-choice questions specifically crafted to elicit responses categorized in a structured order. RESULTS: 166 rheumatologists participated in the survey, 51% of them with more than 21 years of experience in rheumatology. Regarding the perceived challenges in the management of RA in clinical practice, the highest percentage of agreement/strong agreement among the participants was related to the contradictory results of disease activity measures (60%). In terms of the main barriers to assess the disease activity in clinical practice, the lack of adherence to treatment and contradictory assessments between patient-reported outcomes and composite measures were indicated by 75% and 59% of the participants, respectively, as a moderate/serious barrier. The most frequently knowledge and skill gaps related to the management of RA pointed out by the participants were on the difficulty to assess patients' health literacy (54% stated to have no more than intermediate knowledge on standardized methods to assess it and 43% no more than intermediate skills on determining the level of health literacy of the patients). In general, the use of tools to support the management of RA patients in clinical practice was indicated to be unusual by the participants. Self-reflection questionnaires, patient education materials and treatment consideration checklists were pointed out as the least frequently used tools (85%, 64% and 62% of the participants stated to use them never, rarely, or only sometimes, respectively). CONCLUSIONS: Our findings indicate a greater need for design, selection, and uptake of practical strategies to further improve communication between healthcare providers and patients with RA, as well as for promoting well-informed, collaborative decision-making in their care.

Immunohistochemistry Screening of Different Tyrosine Kinase Receptors in Canine Solid Tumors-Part I: Proposal of a Receptor Panel to Predict Therapies.

The use of tyrosine kinase inhibitors (TKI) has been growing in veterinary oncology and in the past few years several TKI have been tested in dogs. However, different from human medicine, we lack strategies to select patients to be treated with each TKI. Therefore, this study aimed to screen different tumor subtypes regarding TKI target immunoexpression as a predictor strategy to personalize the canine cancer treatment. It included 18 prostatic carcinomas, 36 soft tissue sarcomas, 20 mammary gland tumors, 6 urothelial bladder carcinomas, and 7 tumors from the endocrine system. A total of 87 patients with paraffin blocks were used to perform immunohistochemistry (IHC) of human epidermal growth factor receptor 2 (HER-2), epidermal growth factor receptors 1 (EGFR1), vascular endothelial growth factor receptor 2 (VEGFR-2), platelet derived growth factor receptor beta (PDGFR-ß), c-KIT, and extracellular signal-regulated kinase 1/2 (ERK1/ERK2). The immunohistochemical screening revealed a heterogeneous protein expression among histological types with mesenchymal tumors showing the lowest expression level and carcinomas the highest expression. We have demonstrated by IHC screening that HER2, EGFR1, VEGFR-2, PDGFR-ß and ERK1/ERK2 are commonly overexpressed in dogs with different carcinomas, and KIT expression is considered relatively low in the analyzed samples.

Advancing glioblastoma treatment through iron metabolism: A focus on TfR1 and Ferroptosis innovations.

Glioblastoma (GBM) represents a formidable challenge in oncology, characterized by aggressive proliferation and poor prognosis. Iron metabolism plays a critical player in GBM progression, with dysregulated iron uptake and utilization contributing to tumor growth and therapeutic resistance. Iron's pivotal role in DNA synthesis, oxidative stress, and angiogenesis underscores its significance in GBM pathogenesis. Elevated expression of iron transporters, such as transferrin receptor 1 (TfR1), highlights the tumor's reliance on iron for survival. Innovative treatment strategies targeting iron dysregulation hold promise for overcoming therapeutic challenges in GBM management. Approaches such as iron chelation therapies, induction of ferroptosis to nanoparticle-based drug delivery systems exploit iron-dependent vulnerabilities, offering avenues for enhance treatment efficacy and improve patient outcomes. As research advances, understanding the complexities of iron-mediated carcinogenesis provides a foundation for developing precision medicine approaches tailored to combat GBM effectively. This review explores the intricate relationship between iron metabolism and GBM, elucidating its multifaceted implications and therapeutic opportunities. By consolidating the latest insights into iron metabolism in GBM, this review underscores its potential as a therapeutic target for improving patient care in combination with the standard of care approach.

Mirtazapine decreased cocaine-induced c-fos expression and dopamine release in rats.

Introduction: Chronic cocaine exposure induces an increase in dopamine release and an increase in the expression of the Fos protein in the rat striatum. It has been suggested that both are necessary for the expression of cocaine-induced alterations in behavior and neural circuitry. Mirtazapine dosing attenuated the cocaine-induced psychomotor and reinforcer effects. Methods: The study evaluates the effect of chronic dosing of mirtazapine on cocaine-induced extracellular dopamine levels and Fos protein expression in rats. Male Wistar rats received cocaine (10 mg/Kg; i.p.) during the induction and expression of locomotor sensitization. The mirtazapine (30 mg/Kg; MIR), was administered 30 minutes before cocaine during the cocaine withdrawal. After each treatment, the locomotor activity was recorded for 30 minutes. Animals were sacrificed after treatment administration. Dopamine levels were determined by high-performance liquid chromatographic (HPLC) in the ventral striatum, the prefrontal cortex (PFC), and the ventral tegmental area (VTA) in animals treated with mirtazapine and cocaine. The quantification of c-fos immunoreactive cells was carried out by stereology analysis. Results: Mirtazapine generated a decrease in cocaine-induced locomotor activity. In addition, mirtazapine decreased the amount of cocaine-induced dopamine and the number of cells immunoreactive to the Fos protein in the striatum, PFC, and VTA. Discussion: These data suggest that mirtazapine could prevent the consolidation of changes in behavior and the cocaine-induced reorganization of neuronal circuits. It would explain the mirtazapine-induced effects on cocaine behavioral sensitization. Thus, these data together could support its possible use for the treatment of patients with cocaine use disorder.

Comparative Effectiveness of Switching to Bictegravir From Dolutegravir-, Efavirenz-, or Raltegravir-Based Antiretroviral Therapy Among Individuals With HIV Who are Virologically Suppressed.

Background: We aimed to determine the effectiveness of switching to bictegravir in maintaining an undetectable viral load (<50 copies/mL) among people with HIV (PWH) as compared with continuing dolutegravir-, efavirenz-, or raltegravir-based antiretroviral therapy using nationwide observational data from Mexico. Methods: We emulated 3 target trials comparing switching to bictegravir vs continuing with dolutegravir, efavirenz, or raltegravir. Eligibility criteria were PWH aged ≥16 years with a viral load <50 copies/mL and at least 3 months of current antiretroviral therapy (dolutegravir, efavirenz, or raltegravir) between July 2019 and September 2021. Weekly target trials were emulated during the study period, and individuals were included in every emulation if they continued to be eligible. The main outcome was the probability of an undetectable viral load at 3 months, which was estimated via an adjusted logistic regression model. Estimated probabilities were compared via differences, and 95% CIs were calculated via bootstrap. Outcomes were also ascertained at 12 months, and sensitivity analyses were performed to test our analytic choices. Results: We analyzed data from 3 028 619 PWH (63 581 unique individuals). The probability of an undetectable viral load at 3 months was 2.9% (95% CI, 1.9%-3.8%), 1.3% (95% CI, .9%-1.6%), and 1.2% (95% CI, .8%-1.7%) higher when switching to bictegravir vs continuing with dolutegravir, efavirenz, and raltegravir, respectively. Similar results were observed at 12 months and in other sensitivity analyses. Conclusions: Our findings suggest that switching to bictegravir could be more effective in maintaining viral suppression than continuing with dolutegravir, efavirenz, or raltegravir.

Preliminary dataset of emerging contaminants in surface water, bottom water, porewater, and sediment: Urban and aquaculture impacts in Coliumo bay and Caucahue Channel in the central and southern coast of Chile.

Synthetic organic chemicals, including pesticides, pharmaceuticals, and industrial compounds, pose a growing threat to marine ecosystems. Despite their potential impact, data on the co-occurrence of these contaminants in multiple compartments, including surface water, bottom water, porewater, and sediment in the marine environment remains limited. Such information is critical for assessing coastal chemical status, establishing environmental quality benchmarks, and conducting comprehensive environmental risk assessments. In this study, we describe a multifaceted monitoring campaign targeting pesticides, pharmaceuticals, surfactants, additives, and plasticizers among other synthetic chemicals in four sampling sites. One site was located in the small Coliumo bay affected by urban settlements and tourism in central-south and additionally, we sampled three sites, Caucahue Channel, affected by urban settlements and salmon farming in northern Patagonia in Chile. Surface water, bottom water, porewater, and adjacent sediment samples were collected for target screening analysis in LC- and GC-HRMS platforms. Our results show the detection of up to 83 chemicals in surface water, 71 in bottom water, 101 in porewater, and 244 in sediments. To enhance data utility and reuse potential, we provide valuable information on the mode of action and molecular targets of the identified chemicals. This comprehensive dataset contributes to defining pollution fingerprints in coastal areas of the Global South, including remote regions in Patagonia. It serves as a critical resource for future research including marine chemical risk assessment, policymaking, and the advancement of environmental protection in these regions.

De Novo Design of Inhibitors of DNA Methyltransferase 1: A Critical Comparison of Ligand- and Structure-Based Approaches.

Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in combination with similarity searching to identify a novel DNMT inhibitor with a novel chemical scaffold and warrants further exploration. This study aimed to continue exploring the potential of de novo design to build epigenetic-focused libraries targeted toward DNMT1. Herein, we report the results of an in-depth and critical comparison of ligand- and structure-based de novo design of screening libraries focused on DNMT1. The newly designed chemical libraries focused on DNMT1 are freely available on GitHub.

Bayesian Networks for Prescreening in Depression: Algorithm Development and Validation.

BACKGROUND: Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area; however, studies often fall short in demonstrating the practical benefits of using these models and fail to provide tangible real-world applications. OBJECTIVE: This study aims to establish a novel methodology for identifying individuals likely to exhibit DS, identify the most influential features in a more explainable way via probabilistic measures, and propose tools that can be used in real-world applications. METHODS: The study used 3 data sets: PROACTIVE, the Brazilian National Health Survey (Pesquisa Nacional de Saúde [PNS]) 2013, and PNS 2019, comprising sociodemographic and health-related features. A Bayesian network was used for feature selection. Selected features were then used to train machine learning models to predict DS, operationalized as a score of ≥10 on the 9-item Patient Health Questionnaire. The study also analyzed the impact of varying sensitivity rates on the reduction of screening interviews compared to a random approach. RESULTS: The methodology allows the users to make an informed trade-off among sensitivity, specificity, and a reduction in the number of interviews. At the thresholds of 0.444, 0.412, and 0.472, determined by maximizing the Youden index, the models achieved sensitivities of 0.717, 0.741, and 0.718, and specificities of 0.644, 0.737, and 0.766 for PROACTIVE, PNS 2013, and PNS 2019, respectively. The area under the receiver operating characteristic curve was 0.736, 0.801, and 0.809 for these 3 data sets, respectively. For the PROACTIVE data set, the most influential features identified were postural balance, shortness of breath, and how old people feel they are. In the PNS 2013 data set, the features were the ability to do usual activities, chest pain, sleep problems, and chronic back problems. The PNS 2019 data set shared 3 of the most influential features with the PNS 2013 data set. However, the difference was the replacement of chronic back problems with verbal abuse. It is important to note that the features contained in the PNS data sets differ from those found in the PROACTIVE data set. An empirical analysis demonstrated that using the proposed model led to a potential reduction in screening interviews of up to 52% while maintaining a sensitivity of 0.80. CONCLUSIONS: This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most significant features. Moreover, this approach has the potential to substantially reduce the number of screening interviews while maintaining high sensitivity, thereby facilitating improved early identification and intervention strategies for individuals experiencing DS.

Integrating plasma proteome with genome reveals novel protein biomarkers in colorectal cancer.

BACKGROUND: Biomarkers for colorectal cancer (CRC) can complement population screening methods, but so far, few plasma proteins have been identified as biomarkers for CRC. This study aims to identify potential protein biomarkers and therapeutic targets for CRC within the proteome range. METHODS: We extracted summary-level data of circulating protein from 7 published genome-wide association studies (GWASs) of plasma proteome for Mendelian randomization (MR), summary-data-based MR (SMR), and co-localization analyses to screen and validate proteins with causal effects in CRC. In addition, we further conducted druggability evaluation, prognosis analysis at the transcriptional level, and enrichment expression at the single-cell level, highlighting the important role of these plasma protein biomarkers in CRC. RESULTS: We identified 117 plasma protein biomarkers associated with CRC risk, with 9 proteins showing stronger genetic correlations in Bayesian co-localization (PP.H4 > 0.70). Further, we found 26 protein-coding genes already used in targeted drug development and may potentially become therapeutic targets for CRC. In prognosis analysis, the encoding genes of plasma proteins exhibited consistent effects with MR analysis and can serve as prognostic biomarkers for CRC. Additionally, we also found that the differentially expressed proteins are mainly expressed in fibroblasts, endothelial cells, macrophages, and T cells. CONCLUSION: Our study has identified plasma protein biomarkers associated with CRC risk, which may complement population screening methods for CRC and achieve more precise treatment for patients.

Sustained attention can be measured using a brief computerized attention task.

The Continuous Visual Attention Test (CVAT) is a test that detects visuomotor reaction time (RT, alertness), variability of reaction time (VRT, sustained attention), omission errors (OE, focused attention), and commission errors (CE, response inhibition). The standard test takes 15 min, while the ultrafast version only 90 s. Besides overall task length, the two versions differ by target probability (20% and 80% in the 15-min vs. only 80% in the 90-s test) and stimulus-onset asynchrony (SOA) (1, 2, and 4 s in the 15-min vs. only 1 s in the 90-s test. We aimed to analyze the effect of target probability, SOA, and time length on the CVAT variables across the 15-min task and to verify correlations and agreements between the 15-min and the 90-s CVATs. 205 healthy participants performed the two CVATs on the same day. Considering the 15-min task, RT and CE were strongly affected by target probability. Conversely, VRT was not affected. When the 15-min task was compared to the 90-s task, we found no significant difference in the VRT variable. Additionally, a significant agreement between the two tasks was found for the VRT variable. We concluded that sustained attention can be measured with the 90-s CVAT.

Multi-target Compounds against Trypanosomatid Parasites and Mycobacterium tuberculosis.

Multi-target drug treatment has become popular as a substitute for traditional monotherapy. Monotherapy can lead to resistance and side effects. Multi-target drug discovery is gaining importance as data on bioactivity becomes more abundant. The design of multi-target drugs is expected to be an important development in the pharmaceutical industry in the near future. This review presents multi-target compounds against trypanosomatid parasites (Trypanosoma cruzi, T. brucei, and Leishmania sp.) and tuberculosis (Mycobacterium tuberculosis), which mainly affect populations in socioeconomically unfavorable conditions. The article analyzes the studies, including their chemical structures, viral strains, and molecular docking studies, when available. The objective of this review is to establish a foundation for designing new multi-target inhibitors for these diseases.

Histological biomarkers and microbiological parameters of an estuarine fish from the Brazilian Amazon coast as potential indicators of risk to human health.

This study aimed to isolate and identify pathogenic bacteria in the intestinal tract, skin, and muscles of Sciades herzbergii; detect histopathological changes in the gill and liver; and use these biomarkers for the assessment of potential risks to human health. Fish were sampled during the rainy and dry seasons at two points in São Marcos Bay, Maranhão, Brazil: Ilha dos Caranguejos (IC) and Porto Grande (PG). Isolation and quantification were carried out using COLItest®. Colonies were subjected to identification and phenotypic investigation of antimicrobial resistance using Vitek®. Gill and liver samples were subjected to routine histological examination. The results indicated the presence of Klebsiella pneumoniae and Escherichia coli, the latter of which showed phenotypic resistance to norfloxacin and gentamicin. Fish caught at PG exhibited more extensive gill and liver damage than fish caught at IC. The findings suggest that histological changes in target organs of S. herzbergii may be influenced by infection with pathogenic bacteria.

Influence of antipsychotic drugs on microRNA expression in schizophrenia patients - A systematic review.

Schizophrenia (SCZ) is a severe psychiatric disorder with unclear pathophysiology. Moreover, there is no specific biological marker to help clinicians to define a diagnosis, and medication is decided according to the psychiatrist's experience. In this scenario, microRNAs (miRNAs), which are small noncoding RNA molecules that regulate several genes, emerge as potential peripheral biomarkers to help not only the evaluation of the disease state but also the treatment response. Here, we systematically reviewed indexed literature and evaluated follow-up studies investigating the changes in miRNA expression due to antipsychotic treatment. We also assessed target genes and performed pathway enrichment analysis of miRNAs listed in this systematic review. A total of 11 studies were selected according to research criteria, and we observed that 28 miRNAs play a relevant role in schizophrenia pathogenesis or response to antipsychotic treatment, seven of those of extreme interest as possible biomarkers either for condition or treatment. Predicted targets of the miRNAs reviewed here were previously associated with schizophrenia in genome-wide studies, and pathway analysis showed enrichment for genes related to neural processes. With this review, we expect to highlight the importance of miRNAs in schizophrenia pathogenesis and its treatment and point out interesting miRNAs to future studies.

Multi-target Phenylpropanoids Against Epilepsy.

Epilepsy is a neurological disease with no defined cause, characterized by recurrent epileptic seizures. These occur due to the dysregulation of excitatory and inhibitory neurotransmitters in the central nervous system (CNS). Psychopharmaceuticals have undesirable side effects; many patients require more than one pharmacotherapy to control crises. With this in mind, this work emphasizes the discovery of new substances from natural products that can combat epileptic seizures. Using in silico techniques, this review aims to evaluate the antiepileptic and multi-target activity of phenylpropanoid derivatives. Initially, ligand-based virtual screening models (LBVS) were performed with 468 phenylpropanoid compounds to predict biological activities. The LBVS were developed for the targets alpha- amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), voltage-gated calcium channel Ttype (CaV), gamma-aminobutyric acid A (GABAA), gamma-aminobutyric acid transporter type 1 (GAT-1), voltage-gated potassium channel of the Q family (KCNQ), voltage-gated sodium channel (NaV), and N-methyl D-aspartate (NMDA). The compounds that had good results in the LBVS were analyzed for the absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and later, the best molecules were evaluated in the molecular docking consensus. The TR430 compound showed the best results in pharmacokinetic parameters; its oral absorption was 99.03%, it did not violate any Lipinski rule, it showed good bioavailability, and no cytotoxicity was observed either from the molecule or from the metabolites in the evaluated parameters. TR430 was able to bind with GABAA (activation) and AMPA (inhibition) targets and demonstrated good binding energy and significant interactions with both targets. The studied compound showed to be a promising molecule with a possible multi-target activity in both fundamental pharmacological targets for the treatment of epilepsy.

The potential of five c-miRNAs as serum biomarkers for Late-Onset Alzheimer's disease diagnosis: miR-10a-5p, miR-29b-2-5p, miR-125a-5p, miR-342-3p, and miR-708-5p.

The nervous system is rich in miRNAs, indicating an important role of these molecules in regulating processes associated with cognition, memory, and others. Therefore, qualitative and quantitative imbalances involving such miRNAs may be involved in dementia contexts, including Late-Onset Alzheimer's Disease (LOAD). To test the viability of circulating miRNAs (c-miRNAs) as biomarkers for LOAD, we proceed accordingly to the following reasoning. The first stage was to discover and identify profile of c-miRNAs by RNA sequencing (RNA-Seq). For this purpose, blood serum samples were used from LOAD patients (n = 5) and cognitively healthy elderly control group (CTRL_CH) (n = 5), all over 70 years old. We identified seven c-miRNAs differentially expressed (p ≤ 0.05) in the serum of LOAD patients compared to CTRL_CH (miR-10a-5p; miR-29b-2-5p; miR-125a-5p; miR-342-3p, miR-708-5p, miR-380-5p and miR-340-3p). Of these, five (p ≤ 0.01) were selected for in silico analysis (miR-10a-5p; miR-29b-2-5p; miR-125a-5p; miR-342-3p, miR-708-5p), for which 44 relevant target genes were found regulated by these c-miRNAs and related to LOAD. Through the analysis of these target genes in databases, it was possible to observe that they have functions related to the development and progress of LOAD, directly or indirectly connecting the different Alzheimer's pathways. Thus, this work found five promising serum c-miRNAs as options for biomarkers contributing to LOAD diagnosis. Our study shows the complex network between these molecules and LOAD, supporting the relevance of studies using c-miRNAs in dementia contexts.