Identification and functional annotation of hypothetical proteins of uropathogenic Escherichia coli strain CFT073 towards designing antimicrobial drug targets

Identification of Inhibitors for Flagellar Assembly Protein FliN of Uropathogenic Escherichia coli using Virtual Screening and Molecular Dynamics Simulation Study

Escherichia coli (E. coli) is a gram-negative bacterial pathogen that poses a significant clinical and epidemiologic challenge. The selection pressure brought by the insufficient use of antibiotics has resulted in the emergence of multi-drug-resistant E. coli in the past ten years. Computational and bioinformatics methods for screening inhibitors have significantly contributed to discovering novel antibacterial agents. One possible target for novel anti-virulence drugs is motility. Motility inhibitors are generally effective at concentrations lower than those required for the antibacterial properties of traditional antibiotics, and they are likely to exert less selective pressure than current medicines. Motility may be essential for bacteria to survive, find nutrients, and escape unfavorable environments and biofilm formation. The FliN is a protein forming the bulk of the C ring of the flagella and is present in multiple copies (more than 100) in bacteria. Its absence in mammals makes it an attractive drug target for drug discovery. Two-thousand seven hundred seventy-eight natural compounds from the ZINC library were screened against FliN (PDB ID: 4YXB) using PyRx AutoDock Vina, and the top compounds were selected for secondary screening after sorting the results based on their binding energy. Based on interactional analysis, binding energy (- 7.78 kcal/mol), and inhibition constant (1.98 µM), ZINC000000619481 was the best inhibitor. This compound binds exactly as per the defined active site residues of the receptor protein. Also, molecular dynamics was performed. The eigenvalue of the selected complex was 1.241657e-05. There were no ADME properties outside of the specified range for the identified hit; it fitted exactly to the binding site of the FliN receptor well and was found to be stable in MD simulation studies. Further in vitro and in vivo studies are needed to confirm its anti-bacterial activity and use as a potential antimicrobial drug against urinary tract infections caused by E. coli.

Functional annotation of uncharacterized proteins from Fusobacterium nucleatum: identification of virulence factors

Fusobacterium nucleatum is a gram-negative bacteria associated with diverse infections like appendicitis and colorectal cancer. It mainly attacks the epithelial cells in the oral cavity and throat of the infected individual. It has a single circular genome of 2.7 Mb. Many proteins in F. nucleatum genome are listed as "Uncharacterized." Annotation of these proteins is crucial for obtaining new facts about the pathogen and deciphering the gene regulation, functions, and pathways along with discovery of novel target proteins. In the light of new genomic information, an armoury of bioinformatic tools were used for predicting the physicochemical parameters, domain and motif search, pattern search, and localization of the uncharacterized proteins. The programs such as receiver operating characteristics determine the efficacy of the databases that have been employed for prediction of different parameters at 83.6%. Functions were successfully assigned to 46 uncharacterized proteins which included enzymes, transporter proteins, membrane proteins, binding proteins, etc. Apart from the function prediction, the proteins were also subjected to string analysis to reveal the interacting partners. The annotated proteins were also put through homology-based structure prediction and modeling using Swiss PDB and Phyre2 servers. Two probable virulent factors were also identified which could be investigated further for potential drug-related studies. The assigning of functions to uncharacterized proteins has shown that some of these proteins are important for cell survival inside the host and can act as effective drug targets.

Unsupervised Machine Learning Organization of the Functional Dark Proteome of Gram-Negative "Superbugs": Six Protein Clusters Amenable for Distinct Scientific Applications

Uncharacterized proteins have been underutilized as targets for the development of novel therapeutics for difficult-to-treat bacterial infections. To facilitate the exploration of these proteins, 2819 predicted, uncharacterized proteins (19.1% of the total) from reference strains of multidrug Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa species were organized using an unsupervised k-means machine learning algorithm. Classification using normalized values for protein length, pI, hydrophobicity, degree of conservation, structural disorder, and %AT of the coding gene rendered six natural clusters. Cluster proteins showed different trends regarding operon membership, expression, presence of unknown function domains, and interactomic relevance. Clusters 2, 4, and 5 were enriched with highly disordered proteins, nonworkable membrane proteins, and likely spurious proteins, respectively. Clusters 1, 3, and 6 showed closer distances to known antigens, antibiotic targets, and virulence factors. Up to 21.8% of proteins in these clusters were structurally covered by modeling, which allowed assessment of druggability and discontinuous B-cell epitopes. Five proteins (4 in Cluster 1) were potential druggable targets for antibiotherapy. Eighteen proteins (11 in Cluster 6) were strong B-cell and T-cell immunogen candidates for vaccine development. Conclusively, we provide a feature-based schema to fractionate the functional dark proteome of critical pathogens for fundamental and biomedical purposes.

Genome-wide identification, phylogenetic, and expression analysis under abiotic stress conditions of Whirly (WHY) gene family in Medicago sativa L

The WHY family is a group of plant-specific transcription factors, that can bind to single-stranded DNA molecules and play a variety of functions in plant nuclei and organelles, participating in the regulation of plant leaf senescence. It has been identified and analyzed in many species, however, the systematic identification and analysis of the WHY genes family have not yet been reported in alfalfa (Medicago sativa L.). Therefore, to explore the function of alfalfa the WHY genes, and 10 MsWHY genes were identified and further characterized their evolutionary relationship and expression patterns by analyzing the recently published genome of alfalfa. Comprehensive analysis of the chromosome location, physicochemical properties of the protein, evolutionary relationship, conserved motifs, and responses to abiotic stresses of the WHY gene family in alfalfa using bioinformatics methods. The results showed that 10 MsWHY genes were distributed on 10 chromosomes, and collinearity analysis showed that many MsWHYs might be derived from segmental duplications, and these genes are under purifying selection. Based on phylogenetic analyses, the WHY gene family of alfalfa can be divided into four subfamilies: I-IV subfamily, and approximately all the WHY genes within the same subfamily share similar gene structures. The 10 MsWHY gene family members contained 10 motifs, of which motif 2 and motif 4 are the conserved motifs shared by these genes. Furthermore, the analysis of cis-regulatory elements indicated that regulatory elements related to transcription, cell cycle, development, hormone, and stress response are abundant in the promoter sequence of the MsWHY genes. Real-time quantitative PCR demonstrated that MsWHYs gene expression is induced by drought, salt, and methyl jasmonate. The present study serves as a basic foundation for future functional studies on the alfalfa WHY family.