Network metrics, structural dynamics and density functional theory calculations identified a novel Ursodeoxycholic Acid derivative against therapeutic target Parkin for Parkinson's disease

Marine Compound-Carpatamide D as a Potential Inhibitor Against TOP2A and Its Mutant D1021Y in Colorectal Cancer: Insights from DFT, MEP and Molecular Dynamics Simulation

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, hence there is an urgent need for new and effective therapeutic options. DNA topoisomerase 2A (TOP2A) plays a crucial role in the cell cycle and is involved in CRC progression, making it essential to identify structural and functional relevant alterations. Among the 24 mutations, our findings indicated that mutation D1021Y has the most deleterious effect on the TOP2A protein. Based on virtual screening of 31,561 compounds, we identified three lead candidates: 17683 (nigrospoxydon C), 28461 (carpatamide D), and 28853 (6'-O-acetyl-isohomaarbutin), which showed promising inhibitory effect against TOP2A and its mutant form. These compounds were assessed for their stability using density functional theory (DFT) analysis, where carpatamide D possessed the least energy gap of 4.398 eV showing its high reactivity among all. Further, molecular docking also shows the carpatamide D as the top candidate, which exhibited favourable docking energy against the TOP2A wild type (- 7.47 kcal/mol) and with D1021Y mutant (- 7.62 kcal/mol) as compared to reference compound PK1, which showed - 6.11 kcal/mol TOP2A wild type and - 6.24 kcal/mol against mutant type. The molecular dynamics simulation was performed to analyse the dynamics and stability of complex, which revealed TOP2A_28641 and D1021Y_28641 complexes to be stable with least root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF). Molecular mechanics/Poisson-Boltzmann surface area calculations indicated that TOP2A_28641 and D1021Y_28641 complexes exhibited the lowest binding energy of - 23.55 kcal/mol and - 25.03 kcal/mol, respectively. Our findings suggest carpatamide D as a promising lead compound for the TOP2A_D1021Y targeted cancer therapies, which needs further experimental validation.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

Unravelling the molecular mechanistic pathway underlying the anticancer effects of kaempferol in colorectal cancer: a reverse pharmacology network approach

Colorectal cancer (CRC) is the third most diagnosed and highly fatal malignancy, presenting serious health concerns worldwide. The search for an effective cure for CRC is challenging and poses a serious concern. Kaempferol is a potent anti-cancerous bioactive compound often suggested for treating various cancers, including CRC. However, its underlying molecular mechanism against CRC remains unclear. The present study delves into kaempferol's molecular pathways and underlying molecular mechanisms against CRC targets. The target protein-coding genes for kaempferol were retrieved, and the CRC-associated genes were curated. Twelve common targets with a disease specificity index of > 0.6 were validated for their protein expression at different stages of CRC. Over-expressed USP1, SETD7, POLH, TDP1 and RACGAP1 were selected for further studies. The binding affinities of kaempferol to the corresponding proteins were evaluated using molecular docking and Molecular Dynamics (MD) simulations. SETD7 exhibited the highest binding affinity with the lowest binding energy (- 8.06 kcal/mol). Additionally, the MD simulation, and MM-PBSA conferred SETD7-kaempferol complex had the least root-mean-square deviation with lower interaction energy and higher conformational stability. The protein-protein interaction of SETD7 constructed revealed direct interactors, namely, DNMT1, FOXO1, FOXO3, FOXO4, H3-3B, H3-4, H3C12, H3C13, SETD7, SIRT1 and TP53, have a potential role in cancer progression through FOXO signalling. In summary, our study revealed kaempferol's multi-target and synergistic effect on multiple CRC targets and its underlying mechanisms. Finally, the study recommends in-vitro and in-vivo trials for validation of anti-cancerous drugs for CRC.

Novel Antimicrobial Peptide SAAP Mutant as a Better Adjuvant to Sulbactam-Based Treatments Against Clinical Strains of XDR Acinetobacter baumannii

The production of extended spectrum β-lactamases (ESBLs) in extensively drug-resistant (XDR) strains of Acinetobacter baumannii has created havoc amongst clinicians making the treatment procedure challenging. Carbapenem-resistant strains have displayed total ineffectiveness towards newer combinations of β-lactam-β-lactamase inhibitors (βL-βLI) in tertiary healthcare settings. Therefore, the present study was aimed to design potential β-lactamase antimicrobial peptide (AMP) inhibitors against ESBLs produced by the strains. We have constructed an AMP mutant library with higher antimicrobial efficacy (range: ~ 15 to 27%) than their parent peptides. The mutants were thoroughly screened based on different physicochemical and immunogenic properties revealing three peptides, namely SAAP-148, HFIAP-1, myticalin-C6 and their mutants with safe pharmacokinetics profile. Molecular docking highlighted SAAP-148_M15 displaying maximum inhibitory potential with lowest binding energies against NDM1 (- 1148.7 kcal/mol), followed by OXA23 (- 1032.5 kcal/mol) and OXA58 (- 925.3 kcal/mol). The intermolecular interaction profiles displayed SAAP-148_M15 exhibiting hydrogen bonds and van der Waals hydrophobic interactions with the crucial residues of metallo β-lactamase [IPR001279] and penicillin-binding transpeptidase [IPR001460] domains. Coarse-grained clustering and molecular dynamics simulations (MDS) further validated the stable backbone profile and minimal residue-level fluctuations of the protein-peptide complex that were maintained throughout the simulation timeframe. The present study hypothesised that the combination of sulbactam (βL) with SAAP-148_M15 (βLI) holds immense potential in inhibiting the ESBLs alongside restoration of sulbactam activity. The current in silico findings upon further experimental validations can pave path towards designing of successful therapeutic strategy against XDR strains of A. baumannii.

Impact of PmrB mutations on clinical Klebsiella pneumoniae with variable colistin-susceptibilities: Structural insights and potent therapeutic solutions

Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections continue to impose high morbidity threats to hospitalized patients worldwide, limiting therapeutic options to last-resort antibiotics like colistin. However, the dynamic genomic landscape of colistin-resistant K. pneumoniae (COLR-Kp) invoked ardent exploration of underlying molecular signatures for therapeutic propositions/designs. We unveiled the structural impact of the widespread and emerging PmrB mutations involved in colistin resistance (COLR) in K. pneumoniae. In the present study, clinical isolates of K. pneumoniae expressed variable susceptibilities to colistin (>0.5 μg/mL for resistant and ≤0.25 μg/mL for susceptible) despite mutations such as T157P, G207D and T246A. The protein sequences extracted from in-house sequenced genomes were used to model mutant PmrB proteins and analyze the underlying structural alterations. The mutations were contrasted based on molecular dynamics simulation trajectories, free-energy landscapes and structural flexibility profiles. The altered backbone flexibilities can be an essential factor for mutant selection by COLR K. pneumoniae and can provide clues to deal with emerging mutants. Furthermore, PmrB having high druggability confidence (>0.99), was explored as a potential target for 1396 virtually screened FDA-approved drug candidates. Among the top-10 compounds (scores >70), amphotericin B was found to be potential candidate with high affinity (Binding energy <-8 kcal/mol) and stable interactions (RMSF <0.7 Å) against PmrB druggable pockets, despite the mutations, which encourages future adjunct therapeutic research against COLR-Kp.

Elucidating the molecular role of MUC5B in progressive lung adenocarcinoma: Prospects for early diagnosis

Gel-forming mucin MUC5B is significantly deregulated in lung adenocarcinoma (LUAD), however, its role in tumor progression is not yet clearly understood. Here, we used an integrated computational-pipeline-initiated with gene expression analysis followed by network, functional-enrichment, O-linked glycosylation analyses, mutational profiling, and immune cell infiltration estimation to functionally characterize MUC5B gene in LUAD. Thereafter, clinical biomarker validation was supported by the overall survival (OA) and comparative expression profiling across clinical stages using computational algorithms. The gene expression profile of LUAD identified MUC5B to be significantly up-regulated (logFC: 2.36; p-value: 0.01). Network analysis on LUAD interactome screened MUC5B-related genes, having key enrichment in immune suppression and O-linked glycosylation with serine-threonine-rich tandem repeats being highly glycosylated. Furthermore, positive correlation of mutant MUC5B with immune cells in tumor microenvironment (TME) such as cancer-associated fibroblasts and myeloid-derived suppressor cells indicates TME-mediated tumor progression. The positive correlation with immune inhibitors suggested the enhanced tumor proliferation mediated by MUC5B. Structural stability due to genetic alterations identified overall rigid N-H-backbone dynamics (S2 : 0.756), indicating an overall stable mutant protein. Moreover, the low median OA (<50 months) with a hazard ratio of 1.4 and clinical profile of MUC5B gene showed high median expression corresponding to lymph node (N2) and tumor (T3) stages. Our study concludes by highlighting the functional role of O-glycosylated and mutant MUC5B in promoting LUAD by immune suppression. Further, clinical gene expression validation of MUC5B suggests its potential role as a diagnostic biomarker for LUAD metastasis.

Oncoinformatic screening of the gene clusters involved in the HER2-positive breast cancer formation along with the in silico pharmacodynamic profiling of selective long-chain omega-3 fatty acids as the metastatic antagonists

The HER2-positive patients occupy ~ 30% of the total breast cancer patients globally where no prevalent drugs are available to mitigate the frequent metastasis clinically except lapatinib and neratinib. This scarcity reinforced researchers' quest for new medications where natural substances are significantly considered. Valuing the aforementioned issues, this research aimed to study the ERBB2-mediated string networks that work behind the HER2-positive breast cancer formation regarding co-expression, gene regulation, GAMA-receptor-signaling pathway, cellular polarization, and signal inhibition. Following the overexpression, promotor methylation, and survivability profiles of ERBB2, the super docking position of HER2 was identified using the quantum tunneling algorithm. Supramolecular docking was conducted to study the target specificity of EPA and DHA fatty acids followed by a comprehensive molecular dynamic simulation (100 ns) to reveal the RMSD, RMSF, Rg, SASA, H-bonds, and MM/GBSA values. Finally, potential drug targets for EPA and DHA in breast cancer were constructed to determine the drug-protein interactions (DPI) at metabolic stages. Considering the values resulting from the combinational models of the oncoinformatic, pharmacodynamic, and metabolic parameters, long-chain omega-3 fatty acids like EPA and DHA can be considered as potential-targeted therapeutics for HER2-positive breast cancer treatment.

FN1 and cancer-associated fibroblasts markers influence immune microenvironment in clear cell renal cell carcinoma

BACKGROUND

Altered tumor microenvironment (TME) is characterized in clear cell renal cell carcinoma (ccRCC) as a result of the heterogeneity observed in the TME. Modulations in TME have shown tumor metastasis promotion; hence, identifying TME-based biomarkers can be critical for theranostics application.

METHODS

Here, we performed an integrated systems biology approach utilizing differential gene expression, network metrics and clinical samples cohorts to prioritize the major deregulated genes and their associated pathways specific for metastasis.

RESULTS

The gene expression profiling of 140 ccRCC samples resulted in 3657 differentially expressed genes, from which a network of 1867 up-regulated genes were further computed using network metrics for screening hub-genes. The specific pathways of ccRCC entailed through functional enrichment analysis of the hub-gene clusters indicated the role of the identified hub-genes in the enriched pathways, further validating the functional significance of the hub-genes. The positive correlation of TME cells, namely cancer-associated fibroblasts (CAFs) and its biomarkers (FAP and S100A4) with FN1, signified the role of hub-gene signaling for promoting metastasis in ccRCC. Thereafter, comparative expression, differential methylation, genetic alteration and overall survival analysis were analyzed to validate the screened hub-genes.

CONCLUSIONS

The hub-genes were validated and prioritized by correlating with expression-based parameters, including histological grades, tumor, metastatic and pathological stages (based on median transcript per million; analysis of variance [ANOVA], P ≤ 0.05) from a clinically curated ccRCC dataset to further substantiate the translational benefits of the screened hub-genes as potential diagnostic biomarkers for ccRCC.

WGS-based screening of the co-chaperone protein DjlA-induced curved DNA binding protein A (CbpA) from a new multidrug-resistant zoonotic mastitis-causing Klebsiella pneumoniae strain: a novel molecular target of selective flavonoids

The research aimed to establish a multidrug-resistant Klebsiella pneumoniae-induced genetic model for mastitis considering the alternative mechanisms of the DjlA-mediated CbpA protein regulation. The Whole Genome Sequencing of the newly isolated K. pneumoniae strain was conducted to annotate the frequently occurring antibiotic resistance and virulence factors following PCR and MALDI-TOF mass-spectrophotometry. Co-chaperon DjlA was identified and extracted via restriction digestion on PAGE. Based on the molecular string property analysis of different DnaJ and DnaK type genes, CbpA was identified to be regulated most by the DjlA protein during mastitis. Based on the quantum tunnel-cluster profiles, CbpA was modeled as a novel target for diversified biosynthetic, and chemosynthetic compounds. Pharmacokinetic and pharmacodynamic analyses were conducted to determine the maximal point-specificity of selective flavonoids in complexing with the CbpA macromolecule at molecular docking. The molecular dynamic simulation (100 ns) of each of the flavonoid-protein complexes was studied regarding the parameters RMSD, RMSF, Rg, SASA, MMGBSA, and intramolecular hydrogen bonds; where all of them resulted significantly. To ratify all the molecular dynamic simulation outputs, the potential stability of the flavonoids in complexing with CbpA can be remarked as Quercetin > Biochanin A > Kaempherol > Myricetin, which were all significant in comparison to the control Galangin. Finally, a comprehensive drug-gene interaction pathway for each of the flavonoids was developed to determine the simultaneous and quantitative-synergistic effects of different operons belonging to the DnaJ-type proteins on the metabolism of the tested pharmacophores in CbpA. Considering all the in vitro and in silico parameters, DjlA-mediated CbpA can be a novel target for the tested flavonoids as the potential therapeutics of mastitis as futuristic drugs.

Structure Elucidation and Interaction Dynamics of MefA-MsrD Efflux Proteins in Streptococcus pneumoniae: Impact on Macrolide Susceptibility

Macrolides are empirically used to treat bacterial community-acquired pneumonia (CAP). Streptococcus pneumoniae, being the major pathogen responsible for bacterial CAP with high mortality rates, express MefA-MsrD efflux pumps to hinder macrolide susceptibility. Despite its importance, the structural features of the efflux-protein complex and its impact on macrolide susceptibility have not yet been elucidated explicitly. Therefore, in the present study, combining homology, threading, and dynamics approaches, MefA and MsrD proteins in pathogenic S. pneumoniae were modeled. Both membrane (lipid-bilayer) and cytoplasmic (aqueous) environments were considered to simulate the MefA and MsrD proteins in their ideal cellular conditions followed by dynamics analyses. The simulated MefA structure represented a typical major facilitator superfamily protein structure with 13 transmembrane helices. MefA-MsrD interaction via clustering-based docking revealed low-energy conformers with stable intermolecular interactions. The higher clinical MIC value of azithromycin over erythromycin was reflected upon erythromycin eliciting stronger interactions (dissociation constant or ki = ∼52 μM) with the cytoplasmic ATP-binding MsrD than azithromycin (ki = ∼112 μM). The strong (binding energy = -132.1 ± 9.5 kcal/mol) and highly stable (root-mean-square fluctuation < 1.0 Å) physical association between MefA with MsrD was validated and was found to be unaffected by the antibiotic binding. Higher propensity of the macrolides to interact with MsrD than MefA established the importance of the former in macrolide susceptibility. Ours is probably the first report on the structural arrangements in the MefA-MsrD efflux complex and the macrolide susceptibility in S. pneumoniae. This study provides a novel lead for experimental explorations and efflux-pump inhibitor designs.

Consolidated knowledge-guided computational pipeline for therapeutic intervention against bacterial biofilms - a review

Biofilm-associated bacterial infections attributed to multifactorial antimicrobial resistance have caused worldwide challenges in formulating successful treatment strategies. In search of accelerated yet cost-effective therapeutics, several researchers have opted for bioinformatics-based protocols to systemize targeted therapies against biofilm-producing strains. The present review investigated the up-to-date computational databases and servers dedicated to anti-biofilm research to design/screen novel biofilm inhibitors (antimicrobial peptides/phytocompounds/synthetic compounds) and predict their biofilm-inhibition efficacy. Scrutinizing the contemporary in silico methods, a consolidated approach has been highlighted, referred to as a knowledge-guided computational pipeline for biofilm-targeted therapy. The proposed pipeline has amalgamated prominently employed methodologies in genomics, transcriptomics, interactomics and proteomics to identify potential target proteins and their complementary anti-biofilm compounds for effective functional inhibition of biofilm-linked pathways. This review can pave the way for new portals to formulate successful therapeutic interventions against biofilm-producing pathogens.

Discovery of Small Molecule PARKIN Activator from Antipsychotic/Anti-neuropsychiatric Drugs as Therapeutics for PD: an In Silico Repurposing Approach

Although there is presently no cure for Parkinson's disease (PD), the available therapies are only able to lessen symptoms and preserve the quality of life. Around 10 million people globally had PD as of 2020. The widely used standard drug has recently been revealed to have several negative effects. Additionally, there is a dearth of innovative compounds entering the market as a result of subpar ADMET characteristics. Drug repurposing provides a chance to reenergize the sluggish drug discovery process by identifying new applications for already-approved medications. As this strategy offers a practical way to speed up the process of developing alternative medications for PD. This study used a computer-aided technique to select therapeutic agent(s) from FDA-approved neuropsychiatric/psychotic drugs that can be adopted in the treatment of Parkinson's disease. In the current work, a computational approach via molecular docking, density functional theory (DFT), and pharmacokinetics were used to identify possible (anti)neuropsychiatric/psychotic medications for the treatment of PD. By using molecular docking, about eight (anti)neuropsychiatric/psychotic medications were tested against PARKIN, a key protein in PD. Based on the docking score, the best ligand in the trial was determined. The top hits were compared to the reference ligand levodopa (L-DOPA). A large proportion of the drugs displayed binding affinity that was relatively higher than L-DOPA. Also, DFT analysis confirms the ligand-receptor interactions and the molecular charge transfer. All the compounds were found to obey Lipinski's rule with acceptable pharmacokinetic properties. The current study has revealed the effectiveness of antineuropsychiatric/antipsychotic drugs against PARKIN in the treatment of PD and lumateperone was revealed to be the most promising candidate interacting with PARKIN.

Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB

Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.

Comprehensive analysis on the diagnostic role of circulatory exosome-based miR-92a-3p for osteoblastic metastases in prostate adenocarcinoma

Prostate adenocarcinoma (PRAD) is the second leading cause of death in men and the key factor that attributes to the severity and higher mortality rates is the tumor's ability to promote osteoblastic metastases (OM). Currently, no blood-based biomarkers are present that bridges the crosstalk between PRAD and OM progression. Conversely, circulatory microRNAs (miRNAs) are gaining interest among the scientific community for its potential as blood-based markers for cancer detection. Using computational pipeline, this study screened exosome-based miRNA that is functionally regulating OM in PRAD. We retrieved the expression profile of miRNA, mRNA from PRAD microarray, and RNA-Seq samples deposited in global repositories and identified the differentially expressed miRNAs (DEMs) and differentially expressed genes. Thereafter, the average expression of the miRNAs was identified in extracellular vesicle specifically in exosomes. Survival analysis and clinical profiling identified functionally significant miR-92a-3p to be a key factor in OM. This was further examined by the interactions with various noncoding RNA elements, transcription factors, oncogenes, tumor suppressor genes, and protein kinases regulated by miR-92a-3p. Identifying the expression pattern, nodal metastasis, Gleason score, and hazard ratio deciphered the critical role of the targets regulated by miR-92a-3p. Further, binding association analyzed through energy, seed match and accessibility showed the miRNA-targets involved in cytokine, TGF-β, and Wnt signaling having close regulatory role in promoting OM. Our findings highlight the potent role of miR-92a-3p as blood-based diagnostic biomarker for OM. The comprehensive insights from our study can be elemental in designing diagnostic biomarker for PRAD.

Translational protein RpsE as an alternative target for novel nucleoside analogues to treat MDR Enterobacter cloacae ATCC 13047: network analysis and molecular dynamics study

The pathogenic Enterobacter cloacae subsp. cloacae str. ATCC 13047 has contemporarily emerged as a multi-drug resistant strain. To formulate an effective treatment option, alternative therapeutic methods need to be explored. The present study focused on Gene Interaction Network study of 46 antimicrobial resistance genes to reveal the densely interconnecting and functional hub genes in E. cloacae ATCC 13047. The AMR genes were subjected to clustering, topological and functional enrichment analysis, revealing rpsE (RpsE), acrA (AcrA) and arnT (ArnT) as novel therapeutic drug targets for hindering drug resistance in the pathogenic strain. Network topology further indicated translational protein RpsE to be exploited as a promising drug-target candidate for which the structure was predicted, optimized and validated through molecular dynamics simulations (MDS). Absorption, distribution, metabolism and excretion screening recognized ZINC5441082 (N-Isopentyladenosine) (Lead_1) and ZINC1319816 (cyclopentyl-aminopurinyl-hydroxymethyl-oxolanediol) (Lead_2) as orally bioavailable compounds against RpsE. Molecular docking and MDS confirmed the binding efficacy and protein-ligand complex stability. Furthermore, binding free energy (G_bind) calculations, principal component and free energy landscape analyses affirmed the predicted nucleoside analogues against RpsE protein to be comprehensively examined as a potential treatment strategy against E. cloacae ATCC 13047.

A hypothetical model of multi-layered cost-effective wastewater treatment plant integrating microbial fuel cell and nanofiltration technology: A comprehensive review on wastewater treatment and sustainable remediation

Wastewater management has emerged as an uprising concern that demands immediate attention from environmentalists worldwide. Indiscriminate and irrational release of industrial and poultry wastes, sewage, pharmaceuticals, mining, pesticides, fertilizers, dyes and radioactive wastes, contribute immensely to water pollution. This has led to the aggravation of critical health concerns as evident from the uprising trends of antimicrobial resistance, and the presence of xenobiotics and pollutant traces in humans and animals due to the process of biomagnification. Therefore, the development of reliable, affordable and sustainable technologies for the supply of fresh water is the need of the hour. Conventional wastewater treatment often involves physical, chemical, and biological processes to remove solids from the effluent, including colloids, organic matter, nutrients, and soluble pollutants (metals, organics). Synthetic biology has been explored in recent years, incorporating both biological and engineering concepts to refine existing wastewater treatment technologies. In addition to outlining the benefits and drawbacks of the current technologies, this review addresses novel wastewater treatment techniques, especially those using dedicated rational design and engineering of organisms and their constituent parts. Furthermore, the review hypothesizes designing a multi-bedded wastewater treatment plant that is highly cost-efficient, sustainable and requires easy installation and handling. The novel setup envisages removing all the major wastewater pollutants, providing water fit for household, irrigation and storage purposes.

Mechanistic insights into the role of vitamin D and computational identification of potential lead compounds for Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder that affects dopaminergic neurons in the midbrain. A recent study suggests that Orphan Nuclear Receptor 1 (NURR1) impairment may contribute to PD pathogenesis. Our study found three potent agonists for NURR1 protein based on structural and ligand-based screening methods. The pharmacophore is comprised of a hydrogen bond donor, a hydrophobic group, and two aromatic rings (DHRR). The Pharmacophore screening method screened 3142 compounds, of which 3 were screened using structure-based screening. An analysis of the molecules using Molecular Mechanics-Generalized Born Surface Area (binding free energy) revealed a range of -46.77 to -59.06 Kcal/mol. After that, chemical reactivity was investigated by density functional theory, and molecular dynamics simulation was performed (protein-ligand stability). Based on the computational studies, Lifechemical_16901310, Maybridge_2815310, and NPACT_392450 are promising agonists with respect to NURR1. To confirm the potency of the identified compounds, further validation and experiments must be conducted.

Multi-Epitope Vaccine for Monkeypox Using Pan-Genome and Reverse Vaccinology Approaches

Outbreaks of monkeypox virus infections have imposed major health concerns worldwide, with high morbidity threats to children and immunocompromised adults. Although repurposed drugs and vaccines are being used to curb the disease, the evolving traits of the virus, exhibiting considerable genetic dynamicity, challenge the limits of a targeted treatment. A pan-genome-based reverse vaccinology approach can provide fast and efficient solutions to resolve persistent inconveniences in experimental vaccine design during an outbreak-exigency. The approach encompassed screening of available monkeypox whole genomes (n = 910) to identify viral targets. From 102 screened viral targets, viral proteins L5L, A28, and L5 were finalized based on their location, solubility, and antigenicity. The potential T-cell and B-cell epitopes were extracted from the proteins using immunoinformatics tools and algorithms. Multiple vaccine constructs were designed by combining the epitopes. Based on immunological properties, chemical stability, and structural quality, a novel multi-epitopic vaccine construct, V4, was finalized. Flexible-docking and coarse-dynamics simulation portrayed that the V4 had high binding affinity towards human HLA-proteins (binding energy < -15.0 kcal/mol) with low conformational fluctuations (<1 Å). Thus, the vaccine construct (V4) may act as an efficient vaccine to induce immunity against monkeypox, which encourages experimental validation and similar approaches against emerging viral infections.