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.

The search for an antiviral lead molecule to combat the neglected emerging Oropouche virus.

Oropouche virus (OROV) is a member of the Peribunyaviridae family and the causative agent of a dengue-like febrile illness transmitted by mosquitoes. Although mild symptoms generally occur, complications such as encephalitis and meningitis may develop. A lack of proper diagnosis, makes it a potential candidate for new epidemics and outbreaks like other known arboviruses such as Dengue, Yellow Fever and Zika virus. The study of natural molecules as potential antiviral compounds is a promising alternative for antiviral therapies. Wedelolactone (WDL) has been demonstrated to inhibit some viral proteins and virus replication, making it useful to target a wide range of viruses. In this study, we report the in silico effects of WDL on the OROV N-terminal polymerase and its potential inhibitory effects on several steps of viral infection in mammalian cells in vitro, which revealed that WDL indeed acts as a potential inhibitor molecule against OROV infection.

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.

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.

Acridones as promising drug candidates against Oropouche virus.

Oropouche virus (OROV) is an emerging vector-borne arbovirus found in South America that causes Oropouche fever, a febrile infection similar to dengue fever. It has a high epidemic potential, causing illness in over 500,000 cases diagnosed since the virus was first discovered in 1955. Currently, the prevention of human viral infection depends on vaccination, but availability for many viruses is limited, and they are classified as neglected viruses. At present, there are no vaccines or antiviral treatments available. An alternative approach to limiting the spread of the virus is to selectively disrupt viral replication mechanisms. Here, we demonstrate the inhibitory effect of acridones, which efficiently inhibited viral replication by 99.9 % in vitro. To evaluate possible mechanisms of action, we conducted tests with dsRNA, an intermediate in virus replication, as well as MD simulations, docking, and binding free energy analysis. The results showed a strong interaction between FAC21 and the OROV endonuclease, which possibly limits the interaction of viral RNA with other proteins. Therefore, our results suggest a dual mechanism of antiviral action, possibly caused by ds-RNA intercalation. In summary, our findings demonstrate that a new generation of antiviral drugs could be developed based on the selective optimization of molecules.

Antiviral Activity and Molecular Dynamics Simulation of Hops Compounds against Oropouche Virus (Peribunyaviridae).

The Oropouche virus (OROV) is a member of the family Peribunyaviridae (order Bunyavirales) and the cause of a dengue-like febrile illness transmitted mainly by biting midges and mosquitoes. In this study, we aimed to explore acylphloroglucinols and xanthohumol from hops (Humulus lupulus L.) as a promising alternative for antiviral therapies. The evaluation of the inhibitory potential of hops compounds on the viral cycle of OROV was performed through two complementary approaches. The first approach applies cell-based assay post-inoculation experiments to explore the inhibitory potential on the latest steps of the viral cycle, such as genome translation, replication, virion assembly, and virion release from the cells. The second part covers in silico methods evaluating the ability of those compounds to inhibit the activity of the endonuclease domain, which is essential for transcription, binding, and cleaving RNA. In conclusion, the beta acids showed strongest inhibitory potential in post-treatment assay (EC50 = 26.7 µg/mL). Xanthohumol had the highest affinity for OROV endonuclease followed by colupulone and cohumulone. This result contrasts with that observed for docking and MM/PBSA analysis, where cohumulone was found to have a higher affinity. Finally, among the three tested ligands, Lys92 and Arg33 exhibited the highest affinity with the protein.

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.

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.

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.

Exploring the Spike-hACE 2 Residue-Residue Interaction in Human Coronaviruses SARS-CoV-2, SARS-CoV, and HCoV-NL63.

Coronaviruses (CoVs) have been responsible for three major outbreaks since the beginning of the 21st century, and the emergence of the recent COVID-19 pandemic has resulted in considerable efforts to design new therapies against coronaviruses. Thus, it is crucial to understand the structural features of their major proteins related to the virus-host interaction. Several studies have shown that from the seven known CoV human pathogens, three of them use the human Angiotensin-Converting Enzyme 2 (hACE-2) to mediate their host's cell entry: SARS-CoV-2, SARS-CoV, and HCoV-NL63. Therefore, we employed quantum biochemistry techniques within the density function theory (DFT) framework and the molecular fragmentation with conjugate caps (MFCC) approach to analyze the interactions between the hACE-2 and the spike protein-RBD of the three CoVs in order to map the hot-spot residues that form the recognition surface for these complexes and define the similarities and differences in the interaction scenario. The total interaction energy evaluated showed a good agreement with the experimental binding affinity order: SARS-2 > SARS > NL63. A detailed investigation revealed the energetically most relevant regions of hACE-2 and the spike protein for each complex, as well as the key residue-residue interactions. Our results provide valuable information to deeply understand the structural behavior and binding site characteristics that could help to develop antiviral therapeutics that inhibit protein-protein interactions between CoVs S protein and hACE-2.

A quantum biochemistry investigation of the protein-protein interactions for the description of allosteric modulation on biomass-degrading chimera.

The worldwide dependence of population on fossil fuels continues to have several harmful implications for the environment. Bioethanol is an excellent option for renewable fuel to replace the current greenhouse gas emitters. In addition, its production by enzymatic route has gained space among the industrial processes because it replaces the traditional acid treatment. Due to its high versatility, the xylanase family is used in this process as an accessory enzyme for degrading the lignocellulosic substrate of biomass. A chimera built by a xylanolytic domain (Xyl) and a xylose-binding protein (XBP) showed an experimentally improved catalytic efficiency and interdomain allosteric modulation after xylose binding. In this context, we performed a quantum biochemistry characterization of the interactions between these domains and dynamic cross-correlation (DCC) analysis after performing molecular dynamics (DM) simulations of the systems in the presence and absence of xylose in the XBP active site. We used the density functional theory (DFT) within the molecular fractionation with the conjugated caps (MFCC) approach to describe the pair energies, and the corresponding energy difference between the chimera domains responsible for the allosteric effect and amino acid DCC to evaluate the interdomain coupling differences between the energy states. The detailed energetic investigation together with the related structural and dynamics counterparts revealed the molecular mechanisms of chimeric improvement of the xylanase activity observed experimentally. This mechanism was correlated with greater stability and high connectivity at the interdomain interface in the xylose bound relative to the free chimera. We identify the contributions of hydrogen bonds, hydrophobic interactions and water-mediated interactions in the interdomain region responsible for stability together with the structural and dynamical elements related to the allosteric effect. Taken together, these observations led to a comprehensive understanding of the chimera's modulatory action that occurs through the formation of a highly connected interface that makes the essential movements related to xylanolytic activity in xylanase correlated to those of the xylose-binding protein.