Varicella-zoster virus-related neurological complications: From infection to immunomodulatory therapies.

The Varicella-zoster virus (VZV), classified as a neurotropic member of the Herpesviridae family, exhibits a characteristic pathogenicity, predominantly inducing varicella, commonly known as chickenpox, during the initial infectious phase, and triggering the reactivation of herpes zoster, more commonly recognized as shingles, following its emergence from a latent state. The pathogenesis of VZV-associated neuroinflammation involves a complex interplay between viral replication within sensory ganglia and immune-mediated responses that contribute to tissue damage and dysfunction. Upon primary infection, VZV gains access to sensory ganglia, establishing latent infection within neurons. During reactivation, the virus can spread along sensory nerves, triggering a cascade of inflammatory mediators, chemokines, and immune cell infiltration in the affected neural tissues. The role of both adaptive and innate immune reactions, including the contributions of T and B cells, macrophages, and dendritic cells, in orchestrating the immune-mediated damage in the central nervous system is elucidated. Furthermore, the aberrant activation of the natural defence mechanism, characterised by the dysregulated production of immunomodulatory proteins and chemokines, has been implicated in the pathogenesis of VZV-induced neurological disorders, such as encephalitis, myelitis, and vasculopathy. The intricate balance between protective and detrimental immune responses in the context of VZV infection emphasises the necessity for an exhaustive comprehension of the immunopathogenic mechanisms propelling neuroinflammatory processes. Despite the availability of vaccines and antiviral therapies, VZV-related neurological complications remain a significant concern, particularly in immunocompromised individuals and the elderly. Elucidating these mechanisms might facilitate the emergence of innovative immunomodulatory strategies and targeted therapies aimed at mitigating VZV-induced neuroinflammatory damage and improving clinical outcomes. This comprehensive understanding enhances our grasp of viral pathogenesis and holds promise for pioneering therapeutic strategies designed to mitigate the neurological ramifications of VZV infections.

Density Functional Theory Calculations and Molecular Docking Analyses of Flavonoids for Their Possible Application against the Acetylcholinesterase and Triose-Phosphate Isomerase Proteins of Rhipicephalus microplus.

Ticks and tick-borne diseases constitute a substantial hazard to the livestock industry. The rising costs and lack of availability of synthetic chemical acaricides for farmers with limited resources, tick resistance to current acaricides, and residual issues in meat and milk consumed by humans further aggravate the situation. Developing innovative, eco-friendly tick management techniques, such as natural products and commodities, is vital. Similarly, searching for effective and feasible treatments for tick-borne diseases is essential. Flavonoids are a class of natural chemicals with multiple bioactivities, including the inhibition of enzymes. We selected eighty flavonoids having enzyme inhibitory, insecticide, and pesticide properties. Flavonoids' inhibitory effects on the acetylcholinesterase (AChE1) and triose-phosphate isomerase (TIM) proteins of Rhipicephalus microplus were examined utilizing a molecular docking approach. Our research demonstrated that flavonoids interact with the active areas of proteins. Seven flavonoids (methylenebisphloridzin, thearubigin, fortunellin, quercetagetin-7-O-(6-O-caffeoyl-ß-d-glucopyranoside), quercetagetin-7-O-(6-O-p-coumaroyl-ß-glucopyranoside), rutin, and kaempferol 3-neohesperidoside) were the most potent AChE1 inhibitors, while the other three flavonoids (quercetagetin-7-O-(6-O-caffeoyl-ß-d-glucopyranoside), isorhamnetin, and liquiritin) were the potent inhibitors of TIM. These computationally-driven discoveries are beneficial and can be utilized in assessing drug bioavailability in both in vitro and in vivo settings. This knowledge can create new strategies for managing ticks and tick-borne diseases.

In silico identification of phytochemical inhibitors for multidrug-resistant tuberculosis based on novel pharmacophore generation and molecular dynamics simulation studies.

BACKGROUND: Multidrug-resistant tuberculosis (particularly resistant to pyrazinoic acid) is a life-threatening chronic pulmonary disease. Running a marketed regime specifically targets the ribosomal protein subunit-1 (RpsA) and stops trans-translation in the non-mutant bacterium, responsible for the lysis of bacterial cells. However, in the strains of mutant bacteria, this regime has failed in curing TB and killing pathogens, which may only because of the ala438 deletion, which inhibit the binding of pyrazinoic acid to the RpsA active site. Therefore, such cases of tuberculosis need an immediate and effective regime. OBJECTIVE: This study has tried to determine and design such chemotypes that are able to bind to the mutant RpsA protein. METHODS: For these purposes, two phytochemical databases, i.e., NPASS and SANCDB, were virtually screened by a pharmacophore model using an online virtual screening server Pharmit. RESULTS: The model of pharmacophore was developed using the potential inhibitor (zr115) for the mutant of RpsA. Pharmacophore-based virtual screening results into 154 hits from the NPASS database, and 22 hits from the SANCDB database. All the predicted hits were docked in the binding pocket of the mutant RpsA protein. Top-ranked five and two compounds were selected from the NPASS and SANCDB databases respectively. On the basis of binding energies and binding affinities of the compounds, three compounds were selected from the NPASS database and one from the SANCDB database. All compounds were found to be non-toxic and highly active against the mutant pathogen. To further validate the docking results and check the stability of hits, molecular dynamic simulation of three compounds were performed. The MD simulation results showed that all these finally selected compounds have stronger binding interactions, lesser deviation or fluctuations, with greater compactness compared to the reference compound. CONCLUSION: These findings indicate that these compounds could be effective inhibitors for mutant RpsA.

Investigating mechanistic insights of curcumin in blocking the Interleukin-8 signaling pathway associated with Breast Cancer: An in-silico approach.

Interleukin-8 (IL-8) is a chemokine, a type of signaling molecule that has a role in immunological responses and inflammation. In recent years, IL-8 is additionally related to cancer growth and recurrence. Breast cancer growth, progression, and metastatic development are all linked to IL-8. Breast cancer cells are known to develop faster when IL-8 stimulates their proliferation and survival. It can also cause angiogenesis, or the creation of new blood vessels, which is necessary for tumor nutrition and growth. IL-8 and curcumin have been subjects of interest in drug design, particularly in the context of inflammation-related disorders and cancer. This study aims to give an overview of the role of IL-8. Inhibitor-based treatment approaches were being used to target IL-8 with curcumin. Molecular docking method was employed to find a potential interaction to supress competitive inhibition of IL-8 with curcumin. PASS analysis and ADMET characteristics were also being carried out. In the end, IL-8 complexed with curcumin is chosen for MD simulations. Overall, our results showed that during the simulation, the complex stayed comparatively stable. It is also possible to investigate curcumin further as a possible treatment option. The combined results imply that IL-8 and their genetic alterations can be studied in precision cancer therapeutic treatments, utilizing target-driven therapy and early diagnosis.

Structure-based investigation of pyruvate dehydrogenase kinase-3 inhibitory potential of thymoquinone, targeting lung cancer therapy.

Protein kinases are an attractive therapeutic target for cardiovascular, cancer and neurodegenerative diseases. Cancer cells demand energy generation through aerobic glycolysis, surpassing "oxidative phosphorylation" (OXPHOS) in mitochondria. The pyruvate dehydrogenase kinases (PDKs) have many regulatory roles in energy generation balance by controlling the pyruvate dehydrogenase complex. Overexpression of PDKs is associated with the overall survival of cancer. PDK3, an isoform of PDK is highly expressed in various cancer types, is targeted for inhibition in this study. PDK3 has been shown to binds strongly with a natural compound, thymoquinone (TQ), which is known to exhibit anti-cancer potential. Detailed interaction between the PDK3 and TQ was carried out using spectroscopic and docking methods. The overall changes in the protein's structures after TQ binding were estimated by UV-Vis spectroscopy, circular dichroism and fluorescence binding studies. The kinase activity assay was also carried out to see the kinase inhibitory potential of TQ. The enzyme inhibition assay suggested an excellent inhibitory potential of TQ towards PDK3 (IC50 = 5.49 µM). We observed that TQ forms a stable complex with PDK3 without altering its structure and can be a potent PDK3 inhibitor which may be implicated in cancer therapy after desired clinical validation.

African swine fever; insights into genomic aspects, reservoirs and transmission patterns of virus.

African swine fever is a hemorrhagic disease of pigs with high mortality rates. Since its first characterization in 1921, there has been sufficient information about African swine fever virus (ASFV) and related diseases. The virus has been found and maintained in the sylvatic cycle involving ticks and domestic and wild boars in affected regions. The ASFV is spread through direct and indirect contact with infected pigs, their products and carrier vectors especially Ornithodoros ticks. Severe economic losses and a decline in pig production have been observed in ASFV affected countries, particularly in sub-Saharan Africa and Europe. At the end of 2018, the ASFV adversely affected China, the world's leading pork-producer. Control strategies for the disease remained challenging due to the unavailability of effective vaccines and the lack of successful therapeutic measures. However, considerable efforts have been made in recent years to understand the biology of the virus, surveillance and effective control measures. This review emphasizes and summarizes the current state of information regarding the knowledge of etiology, epidemiology, transmission, and vaccine-based control measures against ASFV.

Identification of potential inhibitors of tropomyosin receptor kinase B targeting CNS-related disorders and cancers.

Tropomyosin receptor kinase B (TrkB), also known as neurotrophic tyrosine kinase receptor type 2 (NTRK2), is a protein that belongs to the family of receptor tyrosine kinases (RTKs). NTRK2 plays a crucial role in regulating the development and maturation of the central nervous system (CNS) and peripheral nervous system (PNS). Elevated TrkB expression levels observed in different pathological conditions make it a potential target for therapeutic interventions against neurological disorders, including depression, anxiety, Alzheimer's disease, Parkinson's disease, and certain types of cancer. Targeting TrkB using small molecule inhibitors is a promising strategy for the treatment of a variety of neurological disorders. In this research, a systematic virtual screening was carried out on phytoconstituents found in the IMPPAT library to identify compounds potentially inhibiting TrkB. The retrieved compounds from the IMPPAT library were first filtered using Lipinski's rule of five. The compounds were then sorted based on their docking score and ligand efficiency. In addition, PAINS, ADMET, and PASS evaluations were carried out for selecting drug-like compounds. Finally, in interaction analysis, we found two phytoconstituents, Wedelolactone and 3,8-dihydroxy-1-methylanthraquinone-2-carboxylic acid (DMCA), which possessed considerable docking scores and specificity on the TrkB ATP-binding pocket. The selected compounds were further assessed employing molecular dynamics (MD) simulations and essential dynamics. The results revealed that the elucidated compounds bind well with the TrkB binding pocket and lead to fewer conformations fluctuations. This study highlighted using phytoconstituents, Wedelolactone and DMCA as starting leads in developing novel TrkB inhibitors.Communicated by Ramaswamy H. Sarma.

Rational design of multi-epitope-based vaccine by exploring all dengue virus serotypes proteome: an immunoinformatic approach.

Millions of people's lives are being devastated by dengue virus (DENV), a severe tropical and subtropical illness spread by mosquitoes and other vectors. Dengue fever may be self-limiting like a common cold or can rapidly progress to catastrophic dengue hemorrhagic fever or dengue shock syndrome. With four distinct dengue serotypes (DENV1-4), each with the potential to contain antibody-boosting complicated mechanisms, developing a dengue vaccine has been an ambitious challenge. Here, we used a computational pan-vaccinomics-based vaccine design strategy (reverse vaccinology) for all 4 DENV serotypes acquired from different regions of the world to develop a new and safe vaccine against DENV. Consequently, only five mapped epitopes from all the 4 serotypes were shown to be extremely effective for the construction of multi-epitope vaccine constructs. The suggested vaccine construct V5 from eight vaccine models was thus classified as an antigenic, non-allergenic, and stable vaccine model. Moreover, molecular docking and molecular dynamics simulation was performed for the V5 vaccine candidate against the HLAs and TRL2 and 4 immunological receptors. Later, the vaccine sequence was transcribed into the cDNA to generate an expression vector for the Escherichia coli K12 strain. Our research suggests that this vaccine design (V5) has promising potential as a dengue vaccine. However, further experimental analysis into the vaccine's efficacy might be required for the V5 proper validation to combat all DENV serotypes.

Designing a multiepitope mRNA-based vaccine against enterotoxigenic Escherichia coli infection in calves: Immunoinformatics and molecular modeling approach.

Background: Escherichia coli is one of the serious pathogens causing various infections in the animal field, such as neonatal calf diarrhea, which is responsible for mortality associated with diarrhea during the first days of life. Aim: Current work is aimed at designing an effective and safe multiepitope vaccine candidate against E. coli infection in calves based on the fimbrial protein K99 of Enterotoxigenic E. coli (ETEC) and Immuno-informatics. Methods: A conserved sequence of K99 protein was generated, and then highly antigenic, nonallergic, and overlapped epitopes were used to construct a multiepitope vaccine. Five THL, six MHC II, and four beta cell epitopes were targeted to create the candidate. The candidate vaccine was produced utilizing 15 epitopes and three types of linkers, two types of untranslated region (UTR) human hemoglobin subunit beta (HBB), UTR beta-globin (Rabb), and RpfE protein as an immunomodulation adjuvant. Results: Immuno-informatics analysis of the constructed protein showed that the protein was antigenic (antigenic score of 0.8841), stable, nonallergen, and soluble. Furthermore, the Immuno-informatics and physiochemical analysis of the constructed protein showed a stable, nonallergic, soluble, hydrophilic, and acidic PI (isoelectric point). of 9.34. Docking of the candidate vaccine with the toll-like receptor TLR3 was performed, and results showed a strong interaction between the immune receptor and the vaccine. Finally, the expression efficiency of the construct in E. coli was estimated via computational cloning of the vaccine sequence into Pet28a. Conclusion: Results of immunoinformatics and in silico approaches reveal that the designed vaccine is antigenic, stable, and able to bind to the immune cell receptors. Our results interpret the proposed multiepitope mRNA vaccine as a good preventive option against E. coli infection in calves.

Identification of Novel Antileishmanial Chemotypes By High-Throughput Virtual and In Vitro Screening.

BACKGROUND: Leishmaniasis is a deadly protozoan parasitic disease and a significant health problem in underdeveloped and developing countries. The global spread of the parasite, coupled with the emergence of drug resistance and severe side effects associated with existing treatments, has necessitated the identification of new and potential drugs. OBJECTIVE: This study aimed to identify promising compounds for the treatment of leishmaniasis by targeting two essential enzymes of Leishmania donovani: trypanothione reductase (Try-R) and trypanothione synthetase (Try-S). METHODS: High-throughput virtual and in vitro screening of in-house and commercial databases was conducted. A pharmacophore model with seven features was developed and validated using the Guner-Henery method. The pharmacophore-based virtual screening yielded 690 hits, which were further filtered through Lipinski's rule, ADMET analysis, and molecular docking against Try-R and Try-S. Molecular dynamics studies were performed on selected compounds, and in vitro experiments were conducted to evaluate their activity against the promastigote and amastigote forms of L. donovani. RESULTS: The virtual screening and subsequent analysis identified 33 promising compounds. Molecular dynamics studies of two compounds (comp-1 and comp-2) demonstrated stable binding interactions with the target enzymes and high affinity. In vitro experiments revealed that 13 compounds exhibited moderate activity against both the promastigote (IC50, 41 µM-76 µM) and the amastigote (IC50, 44 µM-72 µM) forms of L. donovani. Compounds 1 and 2 showed the highest percent inhibition and the lowest IC50 values. CONCLUSION: The identified compounds demonstrated significant inhibitory activity against Leishmania donovani and stable interactions with target enzymes. These findings suggest that the compounds could serve as promising leads for developing new treatments for leishmaniasis.

Prospective virtual screening combined with bio-molecular simulation enabled identification of new inhibitors for the KRAS drug target.

Lung cancer is a disease with a high mortality rate and it is the number one cause of cancer death globally. Approximately 12-14% of non-small cell lung cancers are caused by mutations in KRASG12C. The KRASG12C is one of the most prevalent mutants in lung cancer patients. KRAS was first considered undruggable. The sotorasib and adagrasib are the recently approved drugs that selectively target KRASG12C, and offer new treatment approaches to enhance patient outcomes however drug resistance frequently arises. Drug development is a challenging, expensive, and time-consuming process. Recently, machine-learning-based virtual screening are used for the development of new drugs. In this study, we performed machine-learning-based virtual screening followed by molecular docking, all atoms molecular dynamics simulation, and binding energy calculations for the identifications of new inhibitors against the KRASG12C mutant. In this study, four machine learning models including, random forest, k-nearest neighbors, Gaussian naïve Bayes, and support vector machine were used. By using an external dataset and 5-fold cross-validation, the developed models were validated. Among all the models the performance of the random forest (RF) model was best on the train/test dataset and external dataset. The random forest model was further used for the virtual screening of the ZINC15 database, in-house database, Pakistani phytochemicals, and South African Natural Products database. A total of 100 ns MD simulation was performed for the four best docking score complexes as well as the standard compound in complex with KRASG12C. Furthermore, the top four hits revealed greater stability and greater binding affinities for KRASG12C compared to the standard drug. These new hits have the potential to inhibit KRASG12C and may help to prevent KRAS-associated lung cancer. All the datasets used in this study can be freely available at ( https://github.com/Amar-Ajmal/Datasets-for-KRAS ).

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins.

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host-virus protein-protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection. Objective: This study aims to identify therapeutic target proteins in humans that could act as virus-host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors. Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 ("hCoV-2"), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient's mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein. Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein. Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention.

Exploring the promising potential of noscapine for cancer and neurodegenerative disease therapy through inhibition of integrin-linked kinase-1.

Integrin-linked kinase (ILK), a ß1-integrin cytoplasmic domain interacting protein, supports multi-protein complex formation. ILK-1 is involved in neurodegenerative diseases by promoting neuro-inflammation. On the other hand, its overexpression induces epithelial-mesenchymal transition (EMT), which is a major hallmark of cancer and activates various factors associated with a tumorigenic phenotype. Thus, ILK-1 is considered as an attractive therapeutic target. We investigated the binding affinity and ILK-1 inhibitory potential of noscapine (NP) using spectroscopic and docking approaches followed by enzyme inhibition activity. A strong binding affinity of NP was measured for the ILK-1 with estimated Ksv (M-1) values of 1.9 × 105, 3.6 × 105, and 4.0 × 105 and ∆G0 values (kcal/mol) -6.19554, -7.8557 and -8.51976 at 298 K, 303 K, and 305 K, respectively. NP binds to ILK-1 with a docking score of -6.6 kcal/mol and forms strong interactions with active-site pocket residues (Lys220, Arg323, and Asp339). The binding constant for the interaction of NP to ILK-1 was 1.04 × 105 M-1, suggesting strong affinity and excellent ILK-1 inhibitory potential (IC50 of ∼5.23µM). Conformational dynamics of ILK-1 were also studied in the presence of NP. We propose that NP presumably inhibits ILK-1-mediated phosphorylation of various downstream signalling pathways that are involved in cancer cell survival and neuroinflammation.

Structural and energetic analysis of NS5 protein inhibition by small molecules in Japanese encephalitis virus using machine learning and steered molecular dynamics approach.

One of the viral diseases that affect millions of people around the world, particularly in developing countries, is Japanese encephalitis (JE). In this study, the conserved protein of this virus, that is, non-structural protein 5 (NS5), was used as a target protein for this study, and a compound library of 749 antiviral molecules was screened against NS5. The current study employed machine learning-based virtual screening combined with molecular docking. Here, three hits (24360, 123519051 and 213039) had lower binding energies (< -8 kcal/mol) than the control, S-Adenosyl-L-homocysteine (SAH). All the compounds showed significant H-bond interactions with functional residues, which were also observed by the control. Molecular dynamics simulation, MM/GBSA for binding free energy analysis, principal component analysis and free energy landscape were also performed to study the stability of the complex formation. All three compounds had similar root mean square deviation trends, which were comparable to the control, SAH. Post-MD, the 123519051-receptor complex had the highest number of H-bonds (4 to 5) after the control, out of which three exhibited the highest percentage occupancy (50%, 24% and 79%). Both docking and MD, 123519051 showed an H-bond with the residue Gly111, which was also found for the control-protein complex. 123519051 showed the lowest binding free energy with ΔGbind of -89 kJ/mol. Steered molecular dynamics depicted that 123519051 had the maximum magnitude of dissociation (1436.43 kJ/mol/nm), which was more than the control, validating its stable complex formation. This study concluded that 123519051 is a binder and could inhibit the protein NS5 of JE.Communicated by Ramaswamy H. Sarma.

New drug target identification in Vibrio vulnificus by subtractive genome analysis and their inhibitors through molecular docking and molecular dynamics simulations.

Vibrio vulnificus is a rod shape, Gram-negative bacterium that causes sepsis (with a greater than 50% mortality rate), necrotizing fasciitis, gastroenteritis, skin, and soft tissue infection, wound infection, peritonitis, meningitis, pneumonia, keratitis, and arthritis. Based on pathogenicity V. vulnificus is categorized into three biotypes. Type 1 and type 3 cause diseases in humans while biotype 2 causes diseases in eel and fish. Due to indiscriminate use of antibiotics V. vulnificus has developed resistance to many antibiotics so curing is dramatically a challenge. V. vulnificus is resistant to cefazolin, streptomycin, tetracycline, aztreonam, tobramycin, cefepime, and gentamycin. Subtractive genome analysis is the most effective method for drug target identification. The method is based on the subtraction of homologous proteins from both pathogen and host. By this process set of proteins present only in the pathogen and perform essential functions in the pathogen can be identified. The entire proteome of Vibrio vulnificus strain ATCC 27562 was reduced step by step to a single protein predicted as the drug target. AlphaFold2 is one of the applications of deep learning algorithms in biomedicine and is correctly considered the game changer in the field of structural biology. Accuracy and speed are the major strength of AlphaFold2. In the PDB database, the crystal structure of the predicted drug target was not present, therefore the Colab notebook was used to predict the 3D structure by the AlphaFold2, and subsequently, the predicted model was validated. Potent inhibitors against the new target were predicted by virtual screening and molecular docking study. The most stable compound ZINC01318774 tightly attaches to the binding pocket of bisphosphoglycerate-independent phosphoglycerate mutase. The time-dependent molecular dynamics simulation revealed compound ZINC01318774 was superior as compared to the standard drug tetracycline in terms of stability. The availability of V. vulnificus strain ATCC 27562 has allowed in silico identification of drug target which will provide a base for the discovery of specific therapeutic targets against Vibrio vulnificus.

Identification of potential Escherichia coli DNA gyrase B inhibitors targeting antibacterial therapy: an integrated docking and molecular dynamics simulation study.

The alarming rise in the rate of antibiotic resistance is a matter of significant concern. DNA gyrase B (GyrB), a critical bacterial enzyme involved in DNA replication, transcription, and recombination, has emerged as a promising target for antibacterial agents. Inhibition of GyrB disrupts bacterial DNA replication, leading to cell death, making it an attractive candidate for antibiotic development. Although several classes of antibiotics targeting GyrB are currently in clinical use, the emergence of antibiotic resistance necessitates the exploration of novel inhibitors. In this study, we aimed to identify potential Escherichia coli GyrB inhibitors from a database of phytoconstituents sourced from Indian medicinal plants. Utilizing virtual screening, we performed a rigorous search to identify compounds with the most promising inhibitory properties against GyrB. Two compounds, namely Zizogenin and Cucurbitacin S, were identified based on their favorable drug likeliness and pharmacokinetic profiles. Employing advanced computational techniques, we analyzed the binding interactions of Zizogenin and Cucurbitacin S with the ATP-binding site of GyrB through molecular docking simulations. Both compounds exhibited robust binding interactions, evidenced by their high docking energy scores. To assess the stability of these interactions, we conducted extensive 100 ns molecular dynamics (MD) simulations, which confirmed the stability of Zizogenin and Cucurbitacin S when bound to GyrB. In conclusion, our study highlights Zizogenin and Cucurbitacin S as promising candidates for potential antibacterial agents targeting GyrB. Experimental validation of these compounds is warranted to further explore their efficacy and potential as novel antibiotics to combat antibiotic-resistant bacteria.Communicated by Ramaswamy H. Sarma.

Molecular Interactions of Zyesami with the SARS-CoV-2 nsp10/nsp16 Protein Complex.

BACKGROUND: SARS-CoV-2 emerged in late 2019 and caused COVID-19. Patients treated with Zyesami were found to have a 3-fold decrease in respiratory failure and improved clinical outcomes. It was reported that Zyesami inhibits RNA replication of SARS-CoV-2, including several non-structural proteins essential in viral RNA replication. SARS-CoV-2 is a distinctive virus that requires nsp10 and nsp16 for its methyltransferases activity which is crucial for RNA stability and protein synthesis. OBJECTIVE: We aimed the in silico determination of inhibitory consequences of Zyesami on the SARS-CoV-2 nsp10/nsp16 complex. Targeting SARS-CoV-2 nsp10/ nsp16 protein complex may be used to develop a drug against COVID-19. METHODS: I-TASSER was used for secondary structure prediction of Zyesami. CABS-dock was used to model Zyesami with SARS-CoV-2 nsp16 interaction. The docked complex was visualized using PyMol. The quality of the docking model was checked by using ProQdock. RESULTS: The 3D structure of SARS-CoV 2, nsp10/nsp16 showed that essential interactions exist between nsp10 and nsp16. Significant contact areas of Zyesami exist across amino acid residues of nsp10; Asn40-Thr47, Val57-Pro59, Gly69-Ser72, Cys77-Pro84, Lys93-Tyr96. In addition, polar contacts between nsp16 and Zyesami are Asn299-Ser440, Val297-Asn443, Gly149-Tyr437, Gln159-Lys430, Asn178- Arg429, Ser146-Arg429, Ser146-Arg429, Lys147-Arg429, Asr221-Thr422, Lys183-Asp423, Lys183-Asp423, and Gln219-Asp423 the residues are shown of nsp16 and Zyesami respectively. CONCLUSION: The structural bioinformatics analyses have indicated the potential binding specificity of Zyesami and nsp16. Data predict how the initial binding of Zyesami with nsp10 and nsp16 may occur. Moreover, this binding could significantly inhibit the 2 -O-MTase activity of the SARSCoV nsp10/16 complex.

Resistance Pattern in Mostly Gram-negative Bacteria Causing Urinary Tract Infections.

PURPOSE: The antimicrobial prescription in urinary tract infections (UTI) is driven by local data on its pathogenic spectrum and the resistance pattern exhibited by the disease-causing pathogens. We aimed to determine the bacteriological diversity of UTI causing pathogens and antimicrobial resistance in mostly gram-negative bacteria. METHODS: This retrospective hospital-based cross-sectional study analyzed the culture and sensitivity reports of urine samples from a referral centre in the Aljouf region of Saudi Arabia. All the antibiograms from January 1, 2020, to December 31st 2020, were included. The bacterial identification and antimicrobial testing were carried out by the BD Phoenix system (BD Diagnostics, Sparks, MD, USA). Antimicrobial testing was performed as per the Clinical and Laboratory Standard Institute recommendations. Frequencies of multidrug- and extensive drug resistance were calculated. RESULTS: Of the 1334 non-duplicate urine samples received, 422 (31.6%) bacterial growths were observed. Of these, 383 (90.8%) and 39 (9.2%) were gram-negative and gram-positive bacterial isolations, respectively. E. coli 161 (38.1%), K. pneumoniae 97 (23.0%), and E. faecalis 18 (4.3%) were frequent aetiologies of UTI. 309 (80.7%) of gram-negative bacteria were multidrug-resistant including 88 (23.0%) extensively drug-resistant. Overall, a resistance rate of > 55 % to 1st through 4th generation cephalosporins was observed except for cefoxitin (43.7%). A resistance rate of 37.6% was observed towards carbapenems, with the lowest rate (34.0%) to meropenem. CONCLUSION: Multi-drug resistant gram-negative bacteria dominate the pathogenic spectrum of UTI in the region. A high resistance rate to cephalosporins and carbapenems exists in gram-negative organisms, causing UTI.

Simultaneous Detection of Influenza A/B, Respiratory Syncytial Virus, and SARS-CoV-2 in Nasopharyngeal Swabs by One-Tube Multiplex Reverse Transcription Polymerase Chain Reaction.

The treatment and outcome of respiratory virus infections differ. SARS-CoV-2, as well as other respiratory viruses such as influenza virus (A and B) and respiratory syncytial virus (RSV), require simultaneous, cost-effective, and rapid differential detection. We used a gold standard five-target single-step RT-PCR to detect influenza viruses, RSV, and SARS-CoV-2, and this method can be extended to detect influenza virus subtypes. As a result, this five-target single-step RT-PCR method is ideal for differentiating respiratory viruses. The 5' nuclease activity of Taq DNA polymerase is used in the real-time reverse transcription PCR assay. The Taq man fast viral 1-step enzyme is a 4× Master mix and five-target primer probe mix that detects influenza A, influenza B, SARS-CoV-2 ORF1ab, respiratory syncytial viruses A/B and actin. When compared with TaqMan TM and Invitrogen superscript TM III Platinum and the Meril Kit for SARS-CoV-2, the assay demonstrated 100% sensitivity, specificity, and amplification efficiency of 90.1% for target genes. In conclusion, our one-tube multiplex RT-PCR assay offers a rapid and reliable method for the simultaneous detection of influenza A/B, RSV, and SARS-CoV-2 from nasopharyngeal swabs. This assay has the potential to enhance diagnostic capabilities and improve public health responses during respiratory outbreaks, enabling timely interventions and informed decision making.

Antidiarrheal Potential of Viola canescens: In Vivo and In Silico Approaches.

Viola canescens Wall. is an important medicinal plant with reported therapeutic benefits. The current work sought to investigate the antidiarrheal properties of V. canescens extracts both in vivo and in silico. This study applied molecular docking to unravel the molecular mechanism of V. canescens and to find the most effective phytocompounds with antidiarrheal effects. The antidiarrheal activity of V. canescens was assessed utilizing the castor oil-induced diarrhea assay and the charcoal meal assay. Antidiarrheal characteristics were evaluated by measuring parameters such as intestinal motility, fecal score, and hypersecretion. The V. canescens extract had a dose-dependent and statistically significant impact in the charcoal meal assay and castor oil-induced diarrhea assay. In the castor oil-induced diarrhea assay, the ethyl acetate fraction (65.96%) showed the highest percentage of defecation inhibition at the highest dose (300 mg/kg (bw)), followed by the uncorrected crystalline compound (63.83%), crude alkaloids (63.83%), chloroform fraction (63.83%), and crude flavonoids (55.32%), while the aqueous fraction (40.43%) and n-Hexane fraction (42.55%) revealed the lowest antidiarrheal potential. In addition, the molecular docking investigation showed emetine, quercetin, and violanthin, isolated chemicals of V. canescens, to have the highest binding affinity to the target µ and δ opioid receptors with significant inhibitory capacity. These pharmacologically active metabolites in V. canescens were effective in treating diarrhea. This study lends credence to the traditional usage of V. canescens in treating gastrointestinal disorders.