Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis.

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.

Immunoinformatics aided designing of a next generation poly-epitope vaccine against uropathogenic Escherichia coli to combat urinary tract infections.

Urinary tract infections (UTIs) are the second most prevalent bacterial infections and uropathogenic Escherichia coli (UPEC) stands among the primary causative agents of UTIs. The usage of antibiotics is the routine therapy being used in various countries to treat UTIs but becoming ineffective because of increasing antibiotic resistance among UPEC strains. Thus, there must be the development of some alternative treatment strategies such as vaccine development against UPEC. In the following study, pan-genomics along with reverse vaccinology approaches is used under the framework of bioinformatics for the identification of core putative vaccine candidates, employing 307 UPEC genomes (complete and draft), available publicly. A total of nine T-cell epitopes (derived from B-cells) of both MHC classes (I and II), were prioritized among three potential protein candidates. These epitopes were then docked together by using linkers (GPGPG and AAY) and an adjuvant (Cholera Toxin B) to form a poly-valent vaccine construct. The chimeric vaccine construct was undergone by molecular modelling, further refinement and energy minimization. We predicted positive results of the vaccine construct in immune simulations with significantly high levels of immune cells. The protein-protein docking analysis of vaccine construct with toll-like receptors predicted efficient binding, which was further validated by molecular dynamics simulation of vaccine construct with TLR-2 and TLR-4 at 120 ns, resulting in stable complexes' conformation throughout the simulation run. Overall, the vaccine construct demonstrated positive antigenic response. In future, this chimeric vaccine construct or the identified epitopes could be experimentally validated for the development of UPEC vaccines against UTIs.Communicated by Ramaswamy H. Sarma.

Molecular Docking and Molecular Dynamics Studies Reveal Secretory Proteins as Novel Targets of Temozolomide in Glioblastoma Multiforme.

Glioblastoma multiforme (GBM) is a tumor of glial origin and is the most malignant, aggressive and prevalent type, with the highest mortality rate in adult brain cancer. Surgical resection of the tumor followed by Temozolomide (TMZ) therapy is currently available, but the development of resistance to TMZ is a common limiting factor in effective treatment. The present study investigated the potential interactions of TMZ with several secretory proteins involved in various molecular and cellular processes in GBM. Automated docking studies were performed using AutoDock 4.2, which showed an encouraging binding affinity of TMZ towards all targeted proteins, with the strongest interaction and binding affinity with GDF1 and SLIT1, followed by NPTX1, CREG2 and SERPINI, among the selected proteins. Molecular dynamics (MD) simulations of protein-ligand complexes were performed via CABS-flex V2.0 and the iMOD server to evaluate the root-mean-square fluctuations (RMSFs) and measure protein stability, respectively. The results showed that docked models were more flexible and stable with TMZ, suggesting that it may be able to target putative proteins implicated in gliomagenesis that may impact radioresistance. However, additional in vitro and in vivo investigations can ascertain the potential of the selected proteins to serve as novel targets for TMZ for GBM treatment.

Phytochemical profiling of antimicrobial and potential antioxidant plant: Nepeta cataria.

Traditional and phytochemical studies have confirmed the richness and diversity of medicinal plants such as Nepeta cataria (N. cataria), but more studies are needed to complete its metabolite profiling. The objective of this research was to enhance the metabolomic picture and bioactivity of N. cataria for better evaluation. Phytochemical analysis was performed by bio-guided protocols and gas chromatography-mass spectrometry (GC/MS). For this, solvents such as methanol, ethanol, water, acetone, and hexane were used to extract a wide number of chemicals. Antibacterial analysis was performed using the 96-well plate test, Kirby Bauer's disk diffusion method, and the resazurin microdilution test. Antioxidant activity was determined by the DPPH assay and radical scavenging capacity was evaluated by the oxygen radical absorbance capacity (ORAC) assay. GC/MS analysis revealed a total of 247 identified and 127 novel metabolites from all extracts of N. cataria. Water and acetone extracts had the highest identified metabolites (n = 79), whereas methanol extract was the highest in unidentified metabolites (n = 48). The most abundant phytochemicals in methanol extract were 1-isopropylcyclohex-1-ene (concentration = 27.376) and bicyclo [2.2.1] heptan-2-one (concentration = 20.437), whereas in ethanol extract, it was 9,12,15-octadecatrienoic acid (concentration = 27.308) and 1-isopropylcyclohex-1-ene (concentration = 25.854). An abundance of 2 methyl indoles, conhydrin, and coumarin was found in water extracts; a good concentration of eucalyptol was found in acetone extract; and 7,9-di-tert-butyl-1-oxaspiro is the most abundant phytochemicals in hexane extracts. The highest concentration of flavonoids and phenols were identified in hexane and methanol extracts, respectively. The highest antioxidant potential (DPPH assay) was observed in acetone extract. The ethanolic extract exhibited a two-fold higher ORAC than the methanol extract. This examination demonstrated the inhibitory effect against a set of microbes and the presence of polar and non-polar constituents of N. cataria. The results of this study provide a safe resource for the development of food, agriculture, pharmaceutical, and other industrial products upon further research validation.

Anti-COVID-19 multi-epitope vaccine designs employing global viral genome sequences.

BACKGROUND: The coronavirus SARS-CoV-2 is a member of the Coronaviridae family that has caused a global public health emergency. Currently, there is no approved treatment or vaccine available against it. The current study aimed to cover the diversity of SARS-CoV-2 strains reported from all over the world and to design a broad-spectrum multi-epitope vaccine using an immunoinformatics approach. METHODS: For this purpose, all available complete genomes were retrieved from GISAID and NGDC followed by genome multiple alignments to develop a global consensus sequence to compare with the reference genome. Fortunately, comparative genomics and phylogeny revealed a significantly high level of conservation between the viral strains. All the Open Reading Frames (ORFs) of the reference sequence NC_045512.2 were subjected to epitope mapping using CTLpred and HLApred, respectively. The predicted CTL epitopes were then screened for antigenicity, immunogenicity and strong binding affinity with HLA superfamily alleles. HTL predicted epitopes were screened for antigenicity, interferon induction potential, overlapping B cell epitopes and strong HLA DR binding potential. The shortlisted epitopes were arranged into two multi-epitope sequences, Cov-I-Vac and Cov-II-Vac, and molecular docking was performed with Toll-Like Receptor 8 (TLR8). RESULTS: The designed multi-epitopes were found to be antigenic and non-allergenic. Both multi-epitopes were stable and predicted to be soluble in an Escherichia coli expression system. The molecular docking with TLR8 also demonstrated that they have a strong binding affinity and immunogenic potential. These in silico analyses suggest that the proposed multi-epitope vaccine can effectively evoke an immune response.