Expression analysis and mapping of Viral-Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox.

BACKGROUND: Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets. METHODS: GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein-protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules. RESULTS: Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development. RESULTS: MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

Emerging strategies and therapeutic innovations for combating drug resistance in Staphylococcus aureus strains: A comprehensive review.

In recent years, antibiotic therapy has encountered significant challenges due to the rapid emergence of multidrug resistance among bacteria responsible for life-threatening illnesses, creating uncertainty about the future management of infectious diseases. The escalation of antimicrobial resistance in the post-COVID era compared to the pre-COVID era has raised global concern. The prevalence of nosocomial-related infections, especially outbreaks of drug-resistant strains of Staphylococcus aureus, have been reported worldwide, with India being a notable hotspot for such occurrences. Various virulence factors and mutations characterize nosocomial infections involving S. aureus. The lack of proper alternative treatments leading to increased drug resistance emphasizes the need to investigate and examine recent research to combat future pandemics. In the current genomics era, the application of advanced technologies such as next-generation sequencing (NGS), machine learning (ML), and quantum computing (QC) for genomic analysis and resistance prediction has significantly increased the pace of diagnosing drug-resistant pathogens and insights into genetic intricacies. Despite prompt diagnosis, the elimination of drug-resistant infections remains unattainable in the absence of effective alternative therapies. Researchers are exploring various alternative therapeutic approaches, including phage therapy, antimicrobial peptides, photodynamic therapy, vaccines, host-directed therapies, and more. The proposed review mainly focuses on the resistance journey of S. aureus over the past decade, detailing its resistance mechanisms, prevalence in the subcontinent, innovations in rapid diagnosis of the drug-resistant strains, including the applicants of NGS and ML application along with QC, it helps to design alternative novel therapeutics approaches against S. aureus infection.

Determination of potential combination of non-ß-lactam, ß-lactam, and ß-lactamase inhibitors/ß-lactam enhancer against class D oxacillinases producing Acinetobacter baumannii: Evidence from in-vitro, molecular docking and dynamics simulation.

Carbapenem-resistant Acinetobacter baumannii, a predominant nosocomial pathogen in hospitals of intensive care units, is associated with bacteremia and ventilator-associated pneumonia with a high-risk mortality rate. To increase the effectiveness of the ß-lactam (BL) antibiotics, the use of ß-lactamase inhibitors (BLI) acts as a booster when given in combination with BL antibiotics. To this aspect, we selected BL antibiotics of cefiderocol, cefepime, non-BL antibiotic eravacycline, BLI of durlobactam, avibactam, and a ß-lactam enhancer (BLE) of zidebactam. To prove our hypothesis, we determined the minimum inhibitory concentration (MIC) of various BL or non-BL/BLI or BLE combinations using broth microdilution method followed by in silico analysis of molecular docking, molecular dynamics (MD) simulation, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) identifies the potential combination. In MIC testing, eravacycline, cefepime/zidebactam, cefiderocol/zidebactam, and eravacycline in combination with zidebactam or durlobactam were found to be effective against oxacillinases (OXAs) (OXA-23/24/58 like) expressing A. baumannii isolates. The docking results of the selected ligands toward OXA-23, OXA-24, and OXA-58 had an excellent binding score ranging from -5.8 to -9.3 kcal/mol. Further, the docked complexes were subjected and evaluated using gromacs for molecular dynamics simulation of 50 ns toward selected class D OXAs. The binding energies obtained from MM-PBSA shed light on the binding efficiencies of each non-BL, BL, and BLI/BLE, thereby helping us to propose the drug combinations. Based on the MD trajectories scoring acquired, we propose using eravacycline, cefepime/zidebactam, cefiderocol/zidebactam, and eravacycline in combination with durlobactam or zidebactam would be promising for treating OXA-23, OXA-24, and OXA-58 like expressing A. baumannii infections.

Therapeutic and diagnostic applications of exosomal circRNAs in breast cancer.

Circular RNAs (circRNAs) are regulatory elements that are involved in orchestrating gene expression and protein functions and are implicated in various biological processes including cancer. Notably, breast cancer has a significant mortality rate and is one of the most common malignancies in women. CircRNAs have been demonstrated to contribute to the pathogenesis of breast cancer including its initiation, progression, metastasis, and resistance to drugs. By acting as miRNA sponges, circRNAs can indirectly influence gene expression by disrupting miRNA regulation of their target genes, ultimately altering the course of cancer development and progression. Additionally, circRNAs can interact with proteins and modulate their functions including signaling pathways involved in the initiation and development of cancer. Recently, circRNAs can encode peptides that play a role in the pathophysiology of breast cancer and other diseases and their potential as diagnostic biomarkers and therapeutic targets for various cancers including breast cancer. CircRNAs possess biomarkers that differentiate, such as stability, specificity, and sensitivity, and can be detected in several biological specimens such as blood, saliva, and urine. Moreover, circRNAs play an important role in various cellular processes including cell proliferation, differentiation, and apoptosis, all of which are integral factors in the development and progression of cancer. This review synthesizes the functions of circRNAs in breast cancer, scrutinizing their contributions to the onset and evolution of the disease through their interactions with exosomes and cancer-related intracellular pathways. It also delves into the potential use of circRNA as a biomarker and therapeutic target against breast cancer. It discusses various databases and online tools that offer crucial circRNA information and regulatory networks. Lastly, the challenges and prospects of utilizing circRNAs in clinical settings associated with breast cancer are explored.

An integrated gene network analysis to decode the multi-drug resistance mechanism in Klebsiella pneumoniae.

Antimicrobial resistance (AMR) among microorganisms has become one of the worldwide concerns of this century and continues to challenge us. To properly understand this problem, it is essential to know the genes that cause AMR and their resistance mechanisms. Our present study focused on Klebsiella pneumoniae, which possesses AMR genes conferring resistance against multiple antibiotics. A gene interaction network of 42 functional partners was constructed and analyzed to broaden our understanding. Three closely related clusters (C1-C3) having an association with multi-drug resistance mechanisms were identified by clustering analysis. The enrichment analysis illustrated 30 genes in biological processes, 24 genes in molecular function, and 25 genes in cellular components having a significant role. The analysis of the gene interaction network revealed genes birA2, folP, pabC, folA, gyrB, glmM, gyrA, thyA_2 had maximum no. of interactions with their functional partners viz. 26, 25, 25, 24, 23, 23, 23, 23 respectively and can be considered as hub genes. Analyzing the enriched pathways and Gene Ontologies provides insight into AMR's molecular basis. In addition, the proposed study could aid the researchers in developing new treatment options to combat multi-drug resistant K. pneumoniae.

Deciphering the Role of Filamin B Calponin-Homology Domain in Causing the Larsen Syndrome, Boomerang Dysplasia, and Atelosteogenesis Type I Spectrum Disorders via a Computational Approach.

Filamins (FLN) are a family of actin-binding proteins involved in regulating the cytoskeleton and signaling phenomenon by developing a network with F-actin and FLN-binding partners. The FLN family comprises three conserved isoforms in mammals: FLNA, FLNB, and FLNC. FLNB is a multidomain monomer protein with domains containing an actin-binding N-terminal domain (ABD 1-242), encompassing two calponin-homology domains (assigned CH1 and CH2). Primary variants in FLNB mostly occur in the domain (CH2) and surrounding the hinge-1 region. The four autosomal dominant disorders that are associated with FLNB variants are Larsen syndrome, atelosteogenesis type I (AOI), atelosteogenesis type III (AOIII), and boomerang dysplasia (BD). Despite the intense clustering of FLNB variants contributing to the LS-AO-BD disorders, the genotype-phenotype correlation is still enigmatic. In silico prediction tools and molecular dynamics simulation (MDS) approaches have offered the potential for variant classification and pathogenicity predictions. We retrieved 285 FLNB missense variants from the UniProt, ClinVar, and HGMD databases in the current study. Of these, five and 39 variants were located in the CH1 and CH2 domains, respectively. These variants were subjected to various pathogenicity and stability prediction tools, evolutionary and conservation analyses, and biophysical and physicochemical properties analyses. Molecular dynamics simulation (MDS) was performed on the three candidate variants in the CH2 domain (W148R, F161C, and L171R) that were predicted to be the most pathogenic. The MDS analysis results showed that these three variants are highly compact compared to the native protein, suggesting that they could affect the protein on the structural and functional levels. The computational approach demonstrates the differences between the FLNB mutants and the wild type in a structural and functional context. Our findings expand our knowledge on the genotype-phenotype correlation in FLNB-related LS-AO-BD disorders on the molecular level, which may pave the way for optimizing drug therapy by integrating precision medicine.

An integrative bioinformatics pipeline to demonstrate the alteration of the interaction between the ALDH2*2 allele with NAD+ and Disulfiram.

Alcohol use disorder (AUD) is a multifactorial psychiatric behavior disorder. Disulfiram is the first approved drug by the Food and Drug Administration for alcohol-dependent patients, which targets the ALDH2 enzyme. Several genes are known to be involved in alcohol metabolism; mutations in any of these genes are known to be associated with AUD. The E504K mutation in the ALDH2 of the precursor protein or the E487K of the mature protein (E504K/E487K; ALDH2*2 allele) is carried by approximately 8% of the world population. In this study, we aimed to test the known inactive allele ALDH2*2, to validate the use of our extensive computational pipeline (in silico tools, molecular modeling, and molecular docking) for testing the interaction between the ALDH2*2 allele, NAD+, and Disulfiram. In silico predictions showed that the E504K variant of ALDH2 to be pathogenic and destabilizing with the maximum number of prediction in silico tools. Consequently, we studied the effect of this mutation mainly on the interaction between NAD+ -E504K and Disulfiram-E504K complexes using molecular docking technique, and molecular dynamics (MD) analysis. From the molecular docking analysis with NAD+ , we observed that the interaction affinity of the NAD+ decreases with the impact of E504K variant. On the other hand, the drug Disulfiram showed similar interaction in both the native and mutant ALDH2 proteins. Further, the comprehensive MD analysis predicted that the E504K destabilizes the protein and influences the NAD+ and Disulfiram interactions. Our findings reveal that the interaction of NAD+ to the protein is disturbed by the E504K/E487K variant whereas the drug Disulfiram has a similar effect as both native ALDH2 and ALDH2 bearing E504K/E487K variant. This study provides a platform to understand the effect of E504K/E487K on the molecular interaction with NAD+ and Disulfiram.

Substitution impact of highly conserved arginine residue at position 75 in GJB1 gene in association with X-linked Charcot-Marie-tooth disease: A computational study.

X-linked Charcot-Marie-Tooth type 1 X (CMTX1) disease is a subtype of Charcot-Marie-Tooth (CMT), which is mainly caused by mutations in the GJB1 gene. It is also known as connexin 32 (Cx32) that leads to Schwann cell abnormalities and peripheral neuropathy. CMTX1 is considered as the second most common form of CMT disease. The aim of this study is to computationally predict the potential impact of different single amino acid substitutions at position 75 of Cx32, from arginine (R) to proline (P), glutamine (Q) and tryptophan (W). This position is known to be highly conserved among the family of connexin. To understand the structural and functional changes due to these single amino acid substitutions, we employed a homology-modeling technique to build the three-dimensional structure models for the native and mutant proteins. The protein structures were further embedded into a POPC lipid bilayer, inserted into a water box, and subjected to molecular dynamics simulation for 50 ns. Our results show that the mutants R75P, R75Q and R75W display variable structural conformation and dynamic behavior compared to the native protein. Our data proves useful in predicting the potential pathogenicity of the mutant proteins and is expected to serve as a platform for drug discovery for patients with CMT.

A Computational Approach to Identify a Potential Alternative Drug With Its Positive Impact Toward PMP22.

Mutations in the Peripheral Myelin Protein 22 (PMP22) leads to Charcot Marie Tooth type 1A (CMT1A, a subtype of CMT1) disease which is the most common inherited neuropathy of peripheral nervous system. In the present study, we used series of in silico prediction methods to screen and identify the most deleterious non-synonymous SNPs (nsSNPs) in PMP22 gene. Out of 48 nsSNPs, five nsSNPs (L16P, L19P, T23R, W28R, and L147R) associated with PMP22 were predicted to be highly deleterious and destabilizing the protein. To explore the possible structure-function relationship, we employed abinitio modeling strategy using the CABS-fold server to predict the three-dimensional structure models in the absence of crystallized structures in PMP22 protein. We used Cytoscape 3.4.0 plugin Integrated Complex Traits Networks interface (iCTNet) to identify the probable drug-gene interactions in PMP22 gene. A total of 22 chemical compounds yielded from the aforementioned tool was subjected to Molinspiration and OSIRIS program to screen and identify the potent drug molecules for further analysis. Five chemical compounds with excellent bioavailability and drug relevant property were selected for molecular docking simulation study. We modeled five mutant structures at their corresponding positions and performed molecular docking simulation analysis using AutoDock Tools (ADT) version 1.5.6 and ArgusLab 4.0.1 tools to analyze their interaction patterns and binding efficacy. Based on the results obtained from the computational study, we predict that estradiol could be a potential drug of choice for treating patients with CMT1A which needs larger attention from biologists in the near future. J. Cell. Biochem. 118: 3730-3743, 2017. © 2017 Wiley Periodicals, Inc.

Structural Analysis of G1691S Variant in the Human Filamin B Gene Responsible for Larsen Syndrome: A Comparative Computational Approach.

Larsen syndrome (LRS) is a rare genetic disease associated with variable manifestations including skeletal malformations, dislocations of the large joints, and notable changes in facial and limb features. Genetic variants in the Filamin B (FLNB) gene are associated with the development of LRS. We searched two literature databases (OMIM and PubMed) and three gene variant databases (HGMD, UniProt, & dbSNP) to capture all the possible variants associated with LRS phenotype, which may have an impact on the FLNB function. Our search yielded 77 variants that might impact the FLNB protein function in patients with LRS. We performed rigorous computational analysis such as conservational, biochemical, pathogenicity, and structural computational analyses to understand the deleterious effect of the G1691S variant. Further, the structural changes of the G1691S variant was compared with a null variant (G1691A) and the native protein through a molecular dynamic simulation study of 50 ns. We found that the variant G1691S was highly deleterious and destabilize the protein when compared to the native and variant G1691A. This might be due to the physicochemical changes in the variant G1691S when compared to the native and variant G1691A. The destabilization was further supported by transformation of bend to coil in variant G1691S whereas bend was retained in native and variant G1691A through molecular dynamics analysis. Our study shed light on the importance of computational methods to understand the molecular nature of genetic variants and structural insights on the function of the FLNB protein. J. Cell. Biochem. 118: 1900-1910, 2017. © 2017 Wiley Periodicals, Inc.

Genotype-phenotype correlation in 18 Egyptian patients with glutaric acidemia type I.

Glutaric acidemia I (GAI) is an autosomal recessive metabolic disease caused by a deficiency of glutaryl-CoA dehydrogenase enzyme (GCDH). Patients with GAI are characterized by macrocephaly, acute encephalitis-like crises, dystonia and frontotemporal atrophy. In this study, we investigated 18 Egyptian patients that were diagnosed with GAI based on their clinical, neuroradiological, and biochemical profiles. Of the 18 patients, 16 had developmental delay and/or regression, dystonia was prominent in 75% of the cases, and three patients died. Molecular genetics analysis identified 14 different mutations in the GCDH gene in the 18 patients, of the 14 mutations, nine were missense, three were in the 3'-Untranslated Region (3'-UTR), one was nonsense, and one was a silent mutation. Four novel mutations were identified (c.148 T > A; p.Trp50Arg, c.158C > A; p.Pro53Gln, c.1284C > G; p.Ile428Met, and c.1189G > T; p.Glu397*) that were all absent in 300 normal chromosomes. The 3'-UTR mutation (c.*165A > G; rs8012), was the most frequent mutation observed (0.5; 18/36), followed by the most common mutation among Caucasian patients (p.Arg402Trp; rs121434369) with allele frequency of 0.36 (13/36), and the 3'-UTR mutation (c.*288G > T; rs9384, 0.22; 8/16). The p.Arg257Gln mutation was found with allele frequency of ~0.17 (6/36). The marked homozygosity observed in our patients is probably due to the high level of consanguinity that is observed in 100% of the cases. We used nine in silico prediction tools to predict the pathogenicity (SIFT, PhD-SNP, SNAP, Meta-SNP, PolyPhen2, and Align GVGD) and protein stability (I-Mutant2.0, Mupro, and istable) of the nine missense mutants. The mutant p.Arg402Trp was predicted to be most deleterious by all the six pathogenicity prediction tools and destabilizing by all the three-stability prediction tools, and highly conserved by the ConSurf server. Using the clinical, biochemical, family history of the 18 patients, and the in silico analysis of the missense mutations, our study showed a mix of conclusive and inconclusive genotype-phenotype correlations among our patient's cohort and suggests the usefulness of using various sophisticated computational analysis to be utilized for future variant classifications in the genetic clinics.

Interaction of eugenol-based anti-tuberculosis nanoemulsion with bovine serum albumin: A spectroscopic study including Rifampicin, Isoniazid, Pyrazinamide, and Ethambutol.

Tuberculosis (TB), a deadly infectious disease, is primarily caused by the bacterium Mycobacterium tuberculosis. The misuse of antibiotics has led to the development of drug resistance, prompting researchers to explore new technologies to combat multidrug-resistant Tuberculosis (MDR TB). Phospholipid-based nanotherapeutics, such as nanoemulsions, are gaining traction as they enhance drug solubility, stability, and bioavailability. Our study focuses on the interaction between Bovine Serum Albumin (BSA) and a drug-loaded nanoemulsion based on Eugenol. This nanoemulsion incorporates Eugenol, Clove, cinnamon oil, and first-line anti-tuberculosis drugs like Rifampicin, Isoniazid, Pyrazinamide, and Ethambutol. The primary objective is to assess the biosafety profile of the nanoemulsion upon interaction with BSA. We employed Fluorescence, UV-visible, and Fourier Transform Infrared Spectroscopy (FTIR) to analyze this interaction. UV-visible spectroscopy detected changes in hydrophobicity due to structural alterations in BSA near the tryptophan residue, leading to the formation of ground-state complexes. Fluorescence spectroscopy demonstrated that the nanoemulsion effectively quenched fluorescence originating from tryptophan and tyrosine residues. Studies using synchronous and three-dimensional spectroscopy point to a potential modification of the aromatic environment of BSA by the nanoemulsion. Resonance light scattering spectra indicated the formation of large aggregates due to the interaction with the nanoemulsion. The second derivative FTIR spectra showed an increase in the magnitude of secondary structure bands, suggesting a conformational shift. This research has significant pharmacological implications for developing safer, more targeted drug delivery systems. The information obtained from the interaction of the nanoemulsion with the blood carrier protein is vital for the future development of superior carriers with minimal adverse effects on patients. It is crucial to remember that conformational changes brought on by drug-ligand complexes attaching to carrier proteins may have negative consequences. Therefore, this study enhances the in vitro evaluation of potential adverse effects of the nanoemulsion on serum proteins.

Decoding genetic and pathophysiological mechanisms in amyotrophic lateral sclerosis and primary lateral sclerosis: A comparative study of differentially expressed genes and implicated pathways in motor neuron disorders.

Motor Neuron Disorders (MNDs), characterized by the degradation and loss of function of motor neurons, are recognized as fatal conditions with limited treatment options and no known cure. The present study aimed to identify the pathophysiological functions and affected genes in patients with MNDs, specifically Amyotrophic Lateral Sclerosis (ALS) and Primary Lateral Sclerosis (PLS). The GSE56808 dataset comprised three sample groups: six patients diagnosed with ALS (GSM1369650, GSM1369652, GSM1369654, GSM1369656, GSM1369657, GSM1369658), five patients diagnosed with PLS (GSM1369648, GSM1369649, GSM1369653, GSM1369655, GSM1369659), and six normal controls (GSM1369642, GSM1369643, GSM1369644, GSM1369645, GSM1369646, and GSM1369647). The application of computational analysis of microarray gene expression profiles enabled us to identify 346 significantly differentially expressed genes (DEGs), 169 genes for the ALS sample study, and 177 genes for the PLS sample study. Enrichment was carried out using MCODE, a Cytoscape plugin. Functional annotation of DEGs was carried out via ClueGO/CluePedia (v2.5.9) and further validated via the DAVID database. NRP2, SEMA3D, ROBO3 and, CACNB1, CACNG2 genes were identified as the gene of interest for ALS and PLS sample groups, respectively. Axonal guidance (GO:0007411) and calcium ion transmembrane transport (GO:0070588) were identified to be some of the significantly dysregulated gene ontology (GO) terms, with arrhythmogenic right ventricular cardiomyopathy (KEGG:05412) to be the top relevant KEGG pathway which is affected in MND patients. ROBO3 gene was observed to have distinctive roles in ALS and PLS-affected patients, hinting towards the differential progression of ALS from PLS. The insights derived from our comprehensive analysis accentuate the distinct variances in the underlying molecular pathogenesis of ALS and PLS. Further research should investigate the mechanistic roles of the identified DEGs and molecular pathways, leading to potential targeted therapies for ALS and PLS.

Rational design of a multivalent vaccine targeting arthropod-borne viruses using reverse vaccinology strategies.

Viruses transmitted by arthropods, such as Dengue, Zika, and Chikungunya, represent substantial worldwide health threats, particularly in countries like India. The lack of approved vaccines and effective antiviral therapies calls for developing innovative strategies to tackle these arboviruses. In this study, we employed immunoinformatics methodologies, incorporating reverse vaccinology, to design a multivalent vaccine targeting the predominant arboviruses. Epitopes of B and T cells were recognized within the non-structural proteins of Dengue, Zika, and Chikungunya viruses. The predicted epitopes were enhanced with adjuvants ß-defensin and RS-09 to boost the vaccine's immunogenicity. Sixteen distinct vaccine candidates were constructed, each incorporating epitopes from all three viruses. FUVAC-11 emerged as the most promising vaccine candidate through molecular docking and molecular dynamics simulations, demonstrating favorable binding interactions and stability. Its effectiveness was further evaluated using computational immunological studies confirming strong immune responses. The in silico cloning performed using the pET-28a(+) plasmid facilitates the future experimental implementation of this vaccine candidate, paving the way for potential advancements in combating these significant arboviral threats. However, further in vitro and in vivo studies are warranted to confirm the results obtained in this computational study, which highlights the effectiveness of immunoinformatics and reverse vaccinology in creating vaccines against major Arboviruses, offering a promising model for developing vaccines for other vector-borne diseases and enhancing global health security.

Exploring the effect of disease causing mutations in metal binding sites of human ARSA in metachromatic leukodystrophy.

The arylsulfatase A (ARSA) gene is observed to be deficient in patients with metachromatic leukodystrophy (MLD), a type of lysosomal storage disease. MLD is a severe neurodegenerative disorder characterized by an autosomal recessive inheritance pattern. This study aimed to map the most deleterious mutations at the metal binding sites of ARSA and the amino acids in proximity to the mutated positions. We utilized an array of computational tools, including PredictSNP, MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT, SNAP, and ConSurf, to identify the most detrimental mutations potentially implicated in MLD collected from UniProt, ClinVar, and HGMD. Two mutations, D29N and D30H, as being extremely deleterious based on assessments of pathogenicity, conservation, biophysical characteristics, and stability analysis. The D29 and D30 are located at the metal-interacting regions of ARSA and found to undergo post-translational modification, specifically phosphorylation. Henceforth, the in-depth effect of metal binding upon mutation was examined using molecular dynamics simulations (MDS) before and after phosphorylation. The MDS results exhibited high deviation for the D29N and D30H mutations in comparison to the native, and the same was confirmed by significant residue fluctuation and reduced compactness. These structural alterations suggest that such mutations may influence protein functionality, offering potential avenues for personalized therapeutic and providing a basis for potential mutation-specific treatments for severe MLD patients.

Transcriptomic analysis reveals zinc-mediated virulence and pathogenicity in multidrug-resistant Acinetobacter baumannii.

Acinetobacter baumannii is a gram-negative bacterium well known for its multidrug resistance and connection to nosocomial infections under ESKAPE pathogens. This opportunistic pathogen is ubiquitously associated with nosocomial infections, posing significant threats within healthcare environments. Its critical clinical symptoms, namely, meningitis, urinary tract infections, bloodstream infections, ventilator-associated pneumonia, and pneumonia, catalyze the imperative demand for innovative therapeutic interventions. The proposed research focuses on delineating the role of Zinc, a crucial metallo-binding protein and micronutrient integral to bacterial metabolism and virulence, to enhance understanding of the pathogenicity of A. baumannii. RNA sequencing and subsequent DESeq2 analytical methods were used to identify differential gene expressions influenced by zinc exposure. Exploiting the STRING database for functional enrichment analysis has demonstrated the complex molecular mechanisms underlying the enhancement of pathogenicity prompted by Zinc. Moreover, hub genes like gltB, ribD, AIL77834.1, sdhB, nuoI, acsA_1, acoC, accA, accD were predicted using the cytohubba tool in Cytoscape. This investigation underscores the pivotal role of Zinc in the virulence of A. baumannii elucidates the underlying molecular pathways responsible for its pathogenicity. The research further accentuates the need for innovative therapeutic strategies to combat A. baumannii infections, particularly those induced by multidrug-resistant strains.

In silico analysis revealed the potential circRNA-miRNA-mRNA regulative network of non-small cell lung cancer (NSCLC).

BACKGROUND: The primary source of death in the world is non-small cell lung cancer (NSCLC). However, NSCLCs pathophysiology is still not completely understood. The current work sought to study the differential expression of mRNAs involved in NSCLC and their interactions with miRNAs and circRNAs. METHODS: We utilized three microarray datasets (GSE21933, GSE27262, and GSE33532) from the GEO NCBI database to identify the differentially expressed genes (DEGs) in NSCLC. We employed DAVID Functional annotation tool to investigate the underlying GO biological process, molecular functions, and KEGG pathways involved in NSCLC. We performed the Protein-protein interaction (PPI) network, MCODE, and CytoHubba analysis from Cytoscape software to identify the significant DEGs in NSCLC. We utilized miRnet to anticipate and build interaction between miRNAs and mRNAs in NSCLC and ENCORI to predict the miRNA-circRNA relationships and build the ceRNA regulatory network. Finally, we executed the gene expression and Kaplan-Meier survival analysis to validate the significant DEGs in the ceRNA network utilizing TCGA NSCLC and GEPIA data. RESULTS: We revealed a total of 156 overlapped DEGs (47 upregulated and 109 downregulated genes) in NSCLC. The PPI network, MCODE, and CytoHubba analysis revealed 12 hub genes (cdkn3, rrm2, ccnb1, aurka, nuf2, tyms, kif11, hmmr, ccnb2, nek2, anln, and birc5) that are associated with NSCLC. We identified that these 12 genes encode 12 mRNAs that are strongly linked with 8 miRNAs, and further, we revealed that 1 circRNA was associated with this 5 miRNA. We constructed the ceRNAs network that contained 1circRNA-5miRNAs-7mRNAs. The expression of these seven significant genes in LUAD & LUSC (NSCLC) was considerably higher in the TCGA database than in normal tissues. Kaplan-Meier survival plot reveals that increased expression of these hub genes was related to a poor survival rate in LUAD. CONCLUSION: Overall, we developed a circRNA-miRNA-mRNA regulation network to study the probable mechanism of NSCLC.

Exploring natural products library to identify potential inhibitors targeting isoniazid-resistant tuberculosis.

Mycobacterium tuberculosis (MTB) causing tuberculosis (TB) infection is a leading source of illness and death in developing nations, and the emergence of drug-resistant TB remains a significant global threat and a challenge in treating the disease. Mutations in the inhA and katG genes are connected to the principal molecular mechanism of isoniazid (INH) resistance, and continuous treatment of INH for more than a decade led to the evolution of INH resistant-TB (inhR-TB). Structure-based drug discovery approaches on traditional natural compounds are the contemporary source to identify significant lead molecules. This work focuses on discovering effective small compounds from natural compound libraries and applying pharmacophore-based virtual screening to filter out the molecules. The best-identified hit complexes were used for molecular dynamics simulations (MDS) to observe their stability and compactness. A three-dimensional e-pharmacophore hypothesis and screening generated 62 hits based on phase fitness scores from the pharmacophore-based virtual screening. Molecular docking experiments in Maestro's GLIDE module indicated that ZINC000002383126 and ASN22022 may be potential inhibitors of inhA and katG (native, inhA mutants S94A, Y158A, Y158F and Y158S and D137S, Y229F, S315T, W321F, and R418L mutants of katG). In addition, MDS analysis indicated that the native and mutant docked complexes of inhA and katG had good stability and remained compact in the binding pocket of the targets. In vitro studies can further validate the compounds that can act as INH competitive inhibitors.Communicated by Ramaswamy H. Sarma.

Multi-drug loaded eugenol-based nanoemulsions for enhanced anti-mycobacterial activity.

Tuberculosis is one of the oldest bacterial infections known to mankind caused by Mycobacterium tuberculosis. The aim of this research is to optimize and formulate a multi-drug loaded eugenol based nanoemulsion system and to evaluate its ability as an antimycobacterial agent and its potential to be a low cost and effective drug delivery system. All the three eugenol based drug loaded nano-emulsion systems were optimized using response surface methodology (RSM)-central composite design (CCD) and were found stable at a ratio of 1 : 5 (oil : surfactant) when ultrasonicated for 8 minutes. The minimum inhibitory concentration (MIC) values against strains of Mycobacterium tuberculosis highly proved that these essential oil-based nano-emulsions showed more promising results and an even improved anti-mycobacterium activity on the addition of a combination of drugs. The absorbance of 1st line anti-tubercular drugs from release kinetics studies showed a controlled and sustained release in body fluids. Thus, we can conclude that this is a much more efficient and desirable method in treating infections caused by Mycobacterium tuberculosis and even its MDR/XDR strains. All these nano-emulsion systems were stable for more than 3 months.

Interaction of antidiabetic formulation with nanoplastics and its binary influence on plasma protein.

Nanoplastics exposure to humans becomes inevitable due to its prevalence and permanence. Adsorption of emerging pollutant metformin hydrochloride (Met-HCl) -antidiabetic drug, on polystyrene nanoplastics (PSNPs) and influence on plasma protein binding was investigated. Fluorescence studies were carried out for human serum albumin (HSA) binding. Adsorption follows pseudo-second-order kinetics, intraparticle-diffusion, and Langmuir isotherm, undergoing both physisorption and chemisorption which was validated by FE-SEM, FTIR, and HRMS measurements. Complex, experiences static quenching mechanism by hydrogen bonding and VanderWaals force of attraction to HSA. FTIR confirms the secondary structural alteration of HSA. Since Met-HCl covers the NPs' surface, NPs' affinity for HSA is reduced and they might reach the target organs of Met-HCl, disrupt antidiabetic mechanisms and cause far-reaching implications. Results from molecular docking and simulation studies backed up these results as hydrophobic and hydrogen bonds dominate the binding process of the HSA-Met-HCl-PSNPs complex. This work will aid in understanding of the toxico-kinetics/dynamics of binary contaminants.