A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Molecular docking and simulation studies of outer membrane proteins with piperacillin; a broad-spectrum antibiotic against Pseudomonas aeruginosa

One of the most important public health concerns is the rise of the multi-drug resistance bacteria in the recent years. Pseudomonas aeruginosa is a frequent Gram-negative bacterium prominent in the hospital-acquired illness and is considered as an opportunistic human pathogen responsible for causing nosocomial infections. Numerous burn victims, cystic fibrosis patients, and those with neutropenic malignancy die as a result of it. The current approach involves molecular docking for the predominant recognition of the drug binding site for the designing of the potent inhibitors for inhibiting the membrane protein of Pseudomonas aeruginosa. The present study has targeted 11 outer membrane proteins of Pseudomonas aeruginosa with 12 different FDA approved drugs. Protein modeling has been applied to create the target proteins. As per the results revealed out from the docking perspective, Piperacillin which has been categorized under the broad-spectrum antibiotics has emerged out as one of the forerunners as compared to the other group of antibiotics as it exhibited highest binding energy, i.e. -10.4 kcal/mol. Hence, the compound has been validated using in-silico tools such as ADME and PROTOX-II server which indicates its nontoxic nature. Molecular dynamics simulations were conducted for EGCG-OprP, Piperacillin-OprB, OprP (Apoprotein), and OprB (Apoprotein) complexes to assess their binding efficacy. Statistical parameters such as RMSD, RMSF, h-bond interactions, and % occupancies indicated stability in ligand binding. Protein RMSD values plateaued at approximately 0.5 nm, while ligand RMSD values remained below 0.2 nm, affirming stability in binding OprP and OprB. H-bond analysis revealed stable contacts for EGCG and Piperacillin, and % occupancies indicated specific interactions. Energetics analysis yielded deltaG values of -30.45 for EGCG and -56.66 for Piperacillin, suggesting efficient binding with OprP and OprB. This positioned Piperacillin as a promising candidate for future pharmacological studies, considering its classification as a broad-spectrum antibiotic against P. aeruginosa. The study served as a crucial roadmap for designing drugs to inhibit this formidable pathogen amid rising antibiotic resistance, emphasizing its significance in the ongoing battle against infectious diseases.

Gene expression and characterization of an antimicrobial peptide from Medicago sativa "Sazova" cultivar

In recent years, the discovery of new antimicrobial agents has become necessary because of the increase in antibiotic resistance, the development of herbicides and fungicides resistance. Among the antimicrobial agents, antimicrobial peptides (AMPs) stand out due to their stable structure. In this study, the aim was to identify a thermostable AMP from the seeds of M. sativa "Sazova" cultivar and to analyze gene expression during germination. Antimicrobial tests were performed for the seed peptides after heat treatment (85 °C for 10 min), revealing antimicrobial effects against S. aureus, E. coli, and C. albicans. Subsequently, the peptide band corresponding to the inhibition zone was identified as M. sativa Defensin 2.1 (MsDef2.1, MW: 5.2048 kDa). The gene expression analysis of MsDef2.1 in Sazova cultivar showed that the gene was expressed different plant organs, and the expression was decreased over time. As a result of the gene analysis of two cultivars (Sazova and LegenDairy) it was found that there are 5 base differences in the coding sequence and 3 amino acid differences between the sequences of MsDef2.1 isoforms from the LegenDairy and Sazova cultivars. The physiochemical properties, secondary, and tertiary structure of the Sazova Defensin 2.1 were predicted by using bioinformatic tools. Due to the amino acid substitutions in γ-core structures, the antimicrobial activity of the isoforms is expected to differ from each other. These findings demonstrated that the defensin MsDef2.1 can differ in M. sativa cultivars in respect of the gene and amino acid sequences and has a potential for future applications.

Functional annotation of Candida albicans hypothetical proteins: a bioinformatics approach

Candida albicans is a member of the ascomycetes class of fungi and it is an opportunistic pathogen species responsible for a wide range of fungal infections in humans. Bioinformatics and sequencing analysis of Candida proteomics has disclosed that around 69% proteome is still uncharacterized which needs to be annotated with functions. The NCBI-Genome has termed them as hypothetical proteins (HPs) in the whole proteome of Candida. Interpretation of this substantial portion of the proteome can reveal novel pharmacological targets for markers, drug development, and other therapeutics and so on. In this article, we have assigned functional annotation to these hypothetical proteins using bioinformatics methodologies. The advanced and robust computational models have been used to assign the preliminary functions to these putative HPs with high level of confidence. The findings of this study unveil some novel pharmacological targets for drug therapy and vaccines and it would help to identify novel molecular mechanisms underlying the fungal pathogenesis.