Atomoxetine: toxicological aspects of a new treatment for Attention Deficit Hyperactivity Disorder in Brazil.

Atomoxetine is a drug widely used for the treatment of the attention deficit hyperactivity disorder (ADHD) with reduced risk of adverse motor reactions and chemical dependence. However, the pharmacokinetics characteristics as well as the toxicological risk of atomoxetine deserves further investigation to comprehensively analyze the therapeutic and safety aspects of this drug. This study aimed to predict the physicochemical profile and medicinal chemistry characteristics of atomoxetine, alongside its pharmacokinetic properties-namely absorption, distribution, metabolism, and excretion-as well as its toxicology (ADMET) potential through the utilization of web-based in silico tools. This research emphasizes predicted physicochemical, medicinal chemistry, and absorption parameters of atomoxetine that could influence the efficacy and safety of this drug for ADHD treatment. Additionally, atomoxetine also presents noteworthy predicted risks of hepatotoxicity, cardiotoxicity, neurotoxicity, nephrotoxicity, respiratory system toxicity, skin toxicity, and carcinogenicity. These findings underscore the necessity for further assessments of atomoxetine's safety profile, particularly considering different patient populations and durations of drug treatment. The data reported here from in silico predictions suggest that closer monitoring is warranted when atomoxetine is administered to patients with ADHD. Moreover, controlled studies detailing reliable protocols for personalized dosing, considering the multifactorial variability in metabolism efficiency and toxicological potential, would enable a more comprehensive assessment of atomoxetine's safety profile.

Advancing molecular modeling and reverse vaccinology in broad-spectrum yellow fever virus vaccine development.

Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant ( ß -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a( +) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus.

Identification of Helicobacter pylori-carcinogenic TNF-alpha-inducing protein inhibitors via daidzein derivatives through computational approaches.

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.

Computational antigenic insights into the novel NADC-34-like Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) isolate YC-2020.

In this computational study, we advanced the understanding of the antigenic properties of the NADC-34-like isolate of the Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), named YC-2020, relevant in veterinary pathology. We utilized sequence comparison analyses of the M and N proteins, comparing them with those of NADC34, identifying substantial amino acid homology that allowed us to highlight conserved epitopes and crucial variants. Through the application of Clustal Omega for multiple sequence alignment and platforms like Vaxijen and AllerTOP for predicting antigenic and allergenic potential, our analyses revealed important insights into the conservation and variation of epitopes essential for the development of effective diagnostic tools and vaccines. Our findings, aligned with initial experimental studies, underscore the importance of these epitopes in the development of targeted immunodiagnostic platforms and significantly contribute to the management and control of PRRSV. However, further studies are required to validate the computational predictions of antigenicity for this new viral isolate. This approach underscores the potential of computational models to enable ongoing monitoring and control of PRRSV evolution in swine. While this study provides valuable insights into the antigenic properties of the novel PRRSV isolate YC-2020 through computational analysis, it is important to acknowledge the limitations inherent to in silico predictions, specifically, the absence of laboratory validation.

A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide-resistant Mycobacterium tuberculosis.

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.

In silico design of an epitope-based vaccine against PspC in Streptococcus pneumoniae using reverse vaccinology.

BACKGROUND: Streptococcus pneumoniae is a major pathogen that poses a significant hazard to global health, causing a variety of infections including pneumonia, meningitis, and sepsis. The emergence of antibiotic-resistant strains has increased the difficulty of conventional antibiotic treatment, highlighting the need for alternative therapies such as multi-epitope vaccines. In this study, immunoinformatics algorithms were used to identify potential vaccine candidates based on the extracellular immunogenic protein Pneumococcal surface protein C (PspC). METHOD: The protein sequence of PspC was retrieved from NCBI for the development of the multi-epitope vaccine (MEV), and potential B cell and T cell epitopes were identified. Linkers including EAAAK, AAY, and CPGPG were used to connect the epitopes. Through molecular docking, molecular dynamics, and immunological simulation, the affinity between MEV and Toll-like receptors was determined. After cloning the MEV construct into the PET28a ( +) vector, SnapGene was used to achieve expression in Escherichia coli. RESULT: The constructed MEV was discovered to be stable, non-allergenic, and antigenic. Microscopic interactions between ligand and receptor are confirmed by molecular docking and molecular dynamics simulation. The use of an in-silico cloning approach guarantees the optimal expression and translation efficiency of the vaccine within an expression vector. CONCLUSION: Our study demonstrates the potential of in silico approaches for designing effective multi-epitope vaccines against S. pneumoniae. The designated vaccine exhibits the required physicochemical, structural, and immunological characteristics of a successful vaccine against SPN. However, laboratory validation is required to confirm the safety and immunogenicity of the proposed vaccine design.

Advances of Reverse Vaccinology for mRNA Vaccine Design against SARS-CoV-2: A Review of Methods and Tools.

mRNA vaccines are a new class of vaccine that can induce potent and specific immune responses against various pathogens. However, the design of mRNA vaccines requires the identification and optimization of suitable antigens, which can be challenging and time consuming. Reverse vaccinology is a computational approach that can accelerate the discovery and development of mRNA vaccines by using genomic and proteomic data of the target pathogen. In this article, we review the advances of reverse vaccinology for mRNA vaccine design against SARS-CoV-2, the causative agent of COVID-19. We describe the steps of reverse vaccinology and compare the in silico tools used by different studies to design mRNA vaccines against SARS-CoV-2. We also discuss the challenges and limitations of reverse vaccinology and suggest future directions for its improvement. We conclude that reverse vaccinology is a promising and powerful approach to designing mRNA vaccines against SARS-CoV-2 and other emerging pathogens.

Deciphering Interactions between Potential Inhibitors and the Plasmodium falciparum DHODH Enzyme: A Computational Perspective.

Malaria is a parasitic disease that, in its most severe form, can even lead to death. Insect-resistant vectors, insufficiently effective vaccines, and drugs that cannot stop parasitic infestations are making the fight against the disease increasingly difficult. It is known that the enzyme dihydroorotate dehydrogenase (DHODH) is of paramount importance for the synthesis of pyrimidine from the Plasmodium precursor, that is, for its growth and reproduction. Therefore, its blockade can lead to disruption of the parasite's life cycle in the vertebrate host. In this scenario, PfDHODH inhibitors have been considered candidates for a new therapy to stop the parasitic energy source. Given what is known, in this work, we applied molecular fractionation with conjugated caps (MFCC) in the framework of the quantum formalism of density functional theory (DFT) to evaluate the energies of the interactions between the enzyme and the different triazolopyrimidines (DSM483, DMS557, and DSM1), including a complex carrying the mutation C276F. From these results, it was possible to identify the main features of each system, focusing on the wild-type and mutant PfDHODH and examining the major amino acid residues that are part of the four complexes. Our analysis provides new information that can be used to develop new drugs that could prove to be more effective alternatives to present antimalarial drugs.

Smooth muscle contraction of the fundus of stomach, duodenum and bladder from mice exposed to a stress-based model of depression.

Several reports have demonstrated that depressive disorder is related to somatic symptoms including gastrointestinal or genitourinary alterations. The pathophysiological mechanisms underlying the gastrointestinal or genitourinary alterations associated with the depression are still not fully understood. Therefore, this study aimed to evaluate the motor activity of gastrointestinal (fundus of stomach and duodenum) and genitourinary tract (bladder) in a stress-based animal model of depression. Adult male mice were submitted to uncontrollable and unpredictable stress (learned helplessness model), controllable stress and non-stressful situations (control). Then, animals were euthanized and the fundus of stomach, duodenum segments or whole bladder were isolated and mounted in a standard organ bath preparation. We evaluated the contractile effects induced by KCl 80 mM for 5 min or carbachol (acetylcholine receptor agonist). The relaxant effects of isoproterenol (ß-adrenoceptor agonist) were also checked. Animals submitted to the learned helplessness model developed a helpless (depressive-like behavior) or resilient (does not exhibit depressive-like behavior) phenotype. The contractions induced by carbachol were diminished in fundus of stomach isolated from helpless and resilient animals. The isoproterenol-induced fundus of stomach relaxation was reduced in resilient but not helpless mice. The contractions/relaxation of duodenum segments isolated from helpless or resilient animals were not altered. Both helpless and resilient animals showed an increase in the bladder contractions induced by carbachol while the relaxant effects of isoproterenol were reduced when compared to control. Conversely, mice underwent a controllable stress situation did not exhibit alterations in the fundus of stomach or duodenum contraction/relaxation induced by pharmacological agents although a decrease in the bladder contraction induced by carbachol was found. In conclusion, incontrollable and unpredictable stress and not depressive phenotype (helpless animals) or controllable stress could be related to the alterations in motor activity of the fundus of stomach and bladder.

Spike protein mutations and structural insights of pangolin lineage B.1.1.25 with implications for viral pathogenicity and ACE2 binding affinity.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID -19, is constantly evolving, requiring continuous genomic surveillance. In this study, we used whole-genome sequencing to investigate the genetic epidemiology of SARS-CoV-2 in Bangladesh, with particular emphasis on identifying dominant variants and associated mutations. We used high-throughput next-generation sequencing (NGS) to obtain DNA sequences from COVID-19 patient samples and compared these sequences to the Wuhan SARS-CoV-2 reference genome using the Global Initiative for Sharing All Influenza Data (GISAID). Our phylogenetic and mutational analyzes revealed that the majority (88%) of the samples belonged to the pangolin lineage B.1.1.25, whereas the remaining 11% were assigned to the parental lineage B.1.1. Two main mutations, D614G and P681R, were identified in the spike protein sequences of the samples. The D614G mutation, which is the most common, decreases S1 domain flexibility, whereas the P681R mutation may increase the severity of viral infections by increasing the binding affinity between the spike protein and the ACE2 receptor. We employed molecular modeling techniques, including protein modeling, molecular docking, and quantum mechanics/molecular mechanics (QM/MM) geometry optimization, to build and validate three-dimensional models of the S_D614G-ACE2 and S_P681R-ACE2 complexes from the predominant strains. The description of the binding mode and intermolecular contacts of the referenced systems suggests that the P681R mutation may be associated with increased viral pathogenicity in Bangladeshi patients due to enhanced electrostatic interactions between the mutant spike protein and the human ACE2 receptor, underscoring the importance of continuous genomic surveillance in the fight against COVID -19. Finally, the binding profile of the S_D614G-ACE2 and S_P681R-ACE2 complexes offer valuable insights to deeply understand the binding site characteristics that could help to develop antiviral therapeutics that inhibit protein-protein interactions between SARS-CoV-2 spike protein and human ACE2 receptor.

In Silico Evaluation of the Binding Energies of Androgen Receptor Agonists in Wild-Type and Mutational Models.

Anabolic androgenic steroids (AAS) are substances with androgenic and anabolic characteristics. Among the many side effects of hormone therapy with AAS, the following stand out: heart problems, adrenal gland disorders, aggressive behavior, increased risk of prostate cancer, problems related to lack of libido and impotence. Such substances vary in the relationship between androgenic activity, and the activation of the androgen receptor (AR) is of fundamental importance for the singularity of the action of each AAS. In this sense, our study evaluates the aspects that comprise the interactions of testosterone agonists (TES), dihydrotestosterone (DHT) and tetrahydrogestrinone (THG) in complex with the AR. In addition, we also evaluated the impact of ligand-receptor affinity differences in a mutation model. We apply computational techniques based on density functional theory (DFT) and use, as methodology, Molecular Fractionation with Conjugate Caps (MFCC). The energetic specificities present in the interaction between the analyzed complexes attest that the highest affinity with the AR receptor is found for AR-THG, followed by AR-DHT, AR-TES and AR-T877A-DHT, respectively. Our results also show the differences and equivalences between the different agonists, in addition to evaluating the difference between the DHT ligand in complex with the wild-type and mutant receptor, presenting the main amino acid residues that involve the interaction with the ligands. The computational methodology used proves to be an operative and sophisticated choice to help in the search for pharmacological agents for various therapies that have androgen as a target.

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae.

BACKGROUND: Streptococcus pneumoniae (SPN) is the agent responsible for causing respiratory diseases, including pneumonia, which causes severe health hazards and child deaths globally. Antibiotics are used to treat SPN as a first-line treatment, but nowadays, SPN is showing resistance to several antibiotics. A vaccine can overcome this global problem by preventing this deadly pathogen. The conventional methods of wet-laboratory vaccine design and development are an intense, lengthy, and costly procedure. In contrast, epitope-based in silico vaccine designing can save time, money, and energy. In this study, pneumococcal surface protein A (PspA), one of the major virulence factors of SPN, is used to design a multi-epitope vaccine. METHODS: For designing the vaccine, the sequence of PspA was retrieved, and then, phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes of PspA were all predicted by using several bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for the vaccine construction, and then, physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking, molecular dynamic simulation, and immune simulation were performed to ensure the binding between HLA and TLR4. Finally, codon adaptation and in silico cloning were performed to transfer into a suitable vector. RESULTS: The constructed multi-epitope vaccine showed a strong binding affinity with the receptor molecule TLR4. Analysis of molecular dynamic simulation, C-immune simulation, codon adaptation, and in silico cloning validated that our designed vaccine is a suitable candidate against SPN. CONCLUSION: The in silico analysis has proven the vaccine as an alternative medication to combat against S. pneumoniae. The designated vaccine can be further tested in the wet lab, and a novel vaccine can be developed.

Effects of histamine on the contractility of the rat distal cauda epididymis.

The motor activity of the epididymis duct is an essential process for male fertility and it is regulated by hormonal, neuronal and epithelial mechanisms. However, although there is evidence for the presence of histamine in the epididymis, its effects on epididymal motor activity are unknown. This study sought to evaluate the contractile effects of histamine on the rat distal cauda epididymis duct. Segments of the distal cauda epididymis duct from male Wistar rats were isolated and used in isolated organ bath experiments to evaluate the contractile effects of histamine in the absence or presence of antagonists of histamine receptors, α1-adrenoceptors and muscarinic acetylcholine receptors. The effects of histamine on noradrenaline induced contractions were also investigated. Histamine was able to induce phasic contractions on rat distal cauda epididymis duct which were prevented by promethazine 10-1000 nM (H1 receptor antagonist), ranitidine 1-100 µM (H2 receptor antagonist), atropine 100 nM (muscarinic antagonist), and prazosin 100 nM (α1-adrenoceptor antagonist). In addition, histamine was also able to modify noradrenaline-induced contractions possibly via activation of H1 and H2 receptors. In conclusion, this study demonstrates that histamine can induce phasic contractions of rat distal cauda epididymis via H2 receptors and autonomic neurotransmitters. Histamine may also exert modulatory actions on contractions of rat distal cauda epididymis duct induced by adrenergic receptor agonists. Further studies are necessary to unveil the localization of histamine receptors within the epididymal duct and the consequences of manipulation of the histaminergic system on epididymal function and male fertility.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas.

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.

Investigation of protein-protein interactions and hotspot region on the NSP7-NSP8 binding site in NSP12 of SARS-CoV-2.

Background: The RNA-dependent RNA polymerase (RdRp) complex, essential in viral transcription and replication, is a key target for antiviral therapeutics. The core unit of RdRp comprises the nonstructural protein NSP12, with NSP7 and two copies of NSP8 (NSP81 and NSP82) binding to NSP12 to enhance its affinity for viral RNA and polymerase activity. Notably, the interfaces between these subunits are highly conserved, simplifying the design of molecules that can disrupt their interaction. Methods: We conducted a detailed quantum biochemical analysis to characterize the interactions within the NSP12-NSP7, NSP12-NSP81, and NSP12-NSP82 dimers. Our objective was to ascertain the contribution of individual amino acids to these protein-protein interactions, pinpointing hotspot regions crucial for complex stability. Results: The analysis revealed that the NSP12-NSP81 complex possessed the highest total interaction energy (TIE), with 14 pairs of residues demonstrating significant energetic contributions. In contrast, the NSP12-NSP7 complex exhibited substantial interactions in 8 residue pairs, while the NSP12-NSP82 complex had only one pair showing notable interaction. The study highlighted the importance of hydrogen bonds and π-alkyl interactions in maintaining these complexes. Intriguingly, introducing the RNA sequence with Remdesivir into the complex resulted in negligible alterations in both interaction energy and geometric configuration. Conclusion: Our comprehensive analysis of the RdRp complex at the protein-protein interface provides invaluable insights into interaction dynamics and energetics. These findings can guide the design of small molecules or peptide/peptidomimetic ligands to disrupt these critical interactions, offering a strategic pathway for developing effective antiviral drugs.

Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants.

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.